Liaoning Province Research Articles

Development of fully automated models for staging liver fibrosis using non-contrast MRI and artificial intelligence: a retrospective multicenter study

Accurate staging of liver fibrosis (LF) is essential for clinical management in chronic liver disease. While non-contrast MRI (NC-MRI) yields valuable information for liver assessment, its effectiveness in predicting LF remains underexplored. This study aimed to develop and validate artificial intelligence (AI)-powered models utilizing NC-MRI for staging LF. A total of 1726 patients from Shengjing Hospital of China Medical University, registered between October 2003 and October 2022, were retrospectively collected, and divided into development (n=1208) and internal test (n=518) cohorts. An external test cohort consisting of 337 individuals from six centers, registered between June 2015 and November 2022, were also included. All participants underwent NC-MRI (T1-weighted imaging, T1WI; and T2-fat-suppressed imaging, T2FS) and liver biopsies. Two classification models (CMs), named T1 and T2FS, were trained on respective image types using 3D contextual transformer networks and evaluated on both test cohorts. Additionally, three CMs-Clinic, Image, and Fusion-were developed using clinical features, T1 and T2FS scores, and their integration via logistic regression. Classification effectiveness of CMs was assessed using the area under the receiver operating characteristic curve (AUC). A comparison was conducted between the optimal models (OMs) with highest AUC and other methods (transient elastography, five serum biomarkers, and six radiologists). Fusion models (i.e., OM) yielded the highest AUC among the CMs, achieving AUCs of 0.810 for significant fibrosis, 0.881 for advanced fibrosis, and 0.918 for cirrhosis in the internal test cohort, and 0.808, 0.868, and 0.925, respectively, in the external test cohort. The OMs demonstrated superior performance in AUC, significantly surpassing transient elastography (only for staging≥F2 and ≥ F3 grades), serum biomarkers, and three junior radiologists for staging LF. Radiologists, with the aid of the OMs, can achieve a higher AUC in LF assessment. AI-powered models utilizing NC-MRI, including T1WI and T2FS, accurately stage LF. National Natural Science Foundation of China (No. 82071885); General Program of the Liaoning Provincial Department of Education (LJKMZ20221160); Liaoning Province Science and Technology Joint Plan (2023JH2/101700127); the Leading Young Talent Program of Xingliao Yingcai in Liaoning Province (XLYC2203037).

Epidemiology of Hand, Foot, and Mouth Disease and Genetic Characterization of Coxsackievirus A16 in Shenyang, Liaoning Province, China, 2013–2023

Hand, foot, and mouth disease (HFMD), a common childhood infection caused by enterovirus, poses a serious public health concern in China. We collected and analyzed epidemiological data on 62,133 HFMD cases in Shenyang City, Liaoning Province, from 2013 to 2023. The average annual incidence was 76.12 per 100,000 person-years; 99.45% of cases were mild, while 0.55% were severe. Only one patient died. HFMD infections peaked annually in July. Children in kindergartens and scattered children accounted for 44.6% and 42.2% of cases, respectively. Real-time RT-PCR detection of enteroviruses in 5534 patient samples revealed 3780 positives, of which 25.1% were CVA16-positive. Positives were randomly sampled, yielding 240 VP1 sequences of CVA16. Phylogenetic tree results showed that all VP1 sequences belonged to the B1 sub-genogroup. However, the sub-genogroup prevalence varied over time: from 2013 to 2014 and 2019 to 2021, the predominant sub-genogroup was B1a, while it was B1b from 2015 to 2018. Further phylogenetic analyses showed substantial divergence between B1a branches in CVA16, suggesting possible turnover of the B1a sub-genogroup in CVA16 due to evolution. This study provides epidemiological data on HFMD in Shenyang, and provides a phylogenetic analysis of CVA16, offering a theoretical basis for preventing and controlling HFMD in Shenyang City.

The link between fear of disease progression and health promotion behaviors in patients with obstructive sleep apnea hypoventilation syndrome (OSAHS): the mediating role of social support

ObjectiveThis study aims to assess the levels of social support, fear of disease progression (FOP) and health promotion behaviors in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS), and to examine the associations between FOP, social support, and health promotion behaviors in OSAHS patients, with a focus on exploring the mediating role of social support. The findings aim to provide insights for enhancing health promotion behaviors among OSAHS patients in China and to offer a theoretical foundation for healthcare professionals in devising intervention strategies to promote health behaviors in individuals with OSAHS.MethodsThis cross-sectional study included 307 patients diagnosed with OSAHS in Jinzhou City, Liaoning province. The survey instruments utilized included the Demographic Characteristics Questionnaire, Social Support Rating Scale (SSRS), Fear of Disease Progression Scale (Fop-Q-SF), and Health-Promoting Lifestyle Scale (HPLP II). Pearson correlation analysis was employed to assess correlations, while multiple linear regression and structural equation modeling were utilized to explore potential mediation effects.ResultsIn the OSAHS patient population, FOP (r=-0.55, p<0.001) and social support (r = 0.60, p<0.001) were found to be significantly correlated with health promotion behaviors. In the mediated effects model, social support was identified as a partial mediator in the association between FOP and health promotion behaviors among OSAHS patients, accounting for 59.00% of the total effect.ConclusionFOP demonstrates a direct relationship with health promotion behaviors in patients with OSAHS, with social support playing a mediating role in this connection. Healthcare professionals are advised to underscore the significance of social support in promoting the health of OSAHS patients to mitigate FOP and consequently improve health promotion behaviors.

Development and validation of a dynamic nomogram for high care dependency during the hospital-family transition periods in older stroke patients

BackgroundThis research aimed to develop and validate a dynamic nomogram for predicting the risk of high care dependency during the hospital-family transition periods in older stroke patients.Methods309 older stroke patients in the hospital-family transition periods who were treated in the Department of Neurology outpatient clinics of three general hospitals in Jinzhou, Liaoning Province from June to December 2023 were selected as the training set. The patients were investigated with the General Patient Information Questionnaire, the Care Dependency Scale (CDS), the Tilburg Frailty Inventory (TFI), the Hamilton Anxiety Rating Scale (HAMA), the Hamilton Depression Rating Scale-17 (HAMD-17), and the Mini Nutrition Assessment Short Form (MNA-SF). Lasso-logistic regression analysis was used to screen the risk factors for high care dependency in older stroke patients during the hospital-family transition period, and a dynamic nomogram model was constructed. The model was uploaded in the form of a web page based on Shiny apps. The Bootstrap method was employed to repeat the process 1000 times for internal validation. The model’s predictive efficacy was assessed using the calibration plot, decision curve analysis curve (DCA), and area under the curve (AUC) of the receiver operator characteristic (ROC) curve. A total of 133 older stroke patients during the hospital-family transition periods who visited the outpatient department of Neurology of three general hospitals in Jinzhou from January to March 2024 were selected as the validation set for external validation of the model.ResultsBased on the history of stroke, chronic disease, falls in the past 6 months, depression, malnutrition, and frailty, build a dynamic nomogram. The AUC under the ROC curves of the training set was 0.830 (95% CI: 0.784–0.875), and that of the validation set was 0.833 (95% CI: 0.766-0.900). The calibration curve was close to the ideal curve, and DCA results confirmed that the nomogram performed well in terms of clinical applicability.ConclusionThe online dynamic nomogram constructed in this study has good specificity, sensitivity, and clinical practicability, which can be applied to senior stroke patients as a prediction and assessment tool for high care dependency. It is of great significance to guide the development of early intervention strategies, optimize resource allocation, and reduce the care burden on families and society.

Construction, assessment, and protection of green infrastructure networks from a dynamic perspective: A case study of Dalian City, Liaoning Province, China

The green infrastructure (GI) network, an important nature-based solution (NBS) strategy, is pivotal for sustainable urban development. However, current research perspectives focus on constructing a static GI network, and research on evaluating and protecting GI networks in the context of spatiotemporal changes has been limited. This research aims to comprehensively characterise the spatio-temporal changes in the GI network and protect its efficiency. We selected Dalian City as a case study and applied the Future Land-use Simulation (FLUS) model to predict its land use for 2030 and 2040. Based on predicted and historical land-use data, the 1990–2040 GI network of Dalian City was constructed utilising the Integrated valuation of ecosystem services and trade-offs (InVEST), morphological spatial pattern analysis (MSPA) and minimum cumulative resistance (MCR) model, while its spatiotemporal changes were evaluated. The results revealed that the hub area exhibited positive growth over time, whereas the link lengths showed an opposite trend. Furthermore, the overall position of the GI network shifted toward the southwest. The flatness indicator detected that the direction of the GI network shape gradually became less pronounced. Consequently, the structure of the GI network shifted from multi-centre to mono-centre. Additionally, priority protection for hubs is mainly in the northeast, while links are primarily in the coastal regions. The urgency of protection for both increases over time. This research developed a dynamic GI network construction and assessment method, providing a scientific basis and reference for future rational GI network planning, ecological protection planning, and related land policy formulation.

Spatial distribution and risk assessment of heavy metal pollution from enterprises in China

Heavy metal pollution (HMP) directly affects the safety of agricultural products, thereby impacting human health. Industrial emissions, as the main source of soil HMP in China, require in-depth research on their pollution risks. Based on national heavy metal (HM) enterprise data, this paper analyzes the spatial distribution characteristics of key enterprises involved in the HMP across the country. It constructs the risk assessment index system of enterprise HMP based on the “source-pathway-receptor” (SPR) process of the HMP, evaluates and partitions the risk of the HMP from enterprises nationwide. The results show that: (1) Enterprises and pollutant discharge outlets are mainly distributed in the eastern and southeastern coastal regions. Jiangxi, Yunnan, Guangdong, and Hunan Province are the main distribution regions of smelting enterprises, with the most types of HM pollutants. The hazard of pollution sources shows a spatial distribution pattern of higher risk in the southwest and north, and lower risk in the central region. Counties with high-risk pollution sources are mainly distributed in Yunnan, Hunan, Guangdong, Inner Mongolia, and Jiangxi Province. (2) The hazard of pollutant transmission pathways shows a spatial distribution pattern of higher risk in the southeast and lower risk in the central region. About 31.5 % of counties are at extremely high risk, mainly distributed in the southeastern coastal regions of Guangdong, Jiangsu, Zhejiang, Jiangxi, Shandong, and Fujian Province. (3) The vulnerability of the receptors shows significant clustering characteristics in the northeast and central regions. About 3.3 % of counties have a receptor vulnerability level of “extremely high,” mainly distributed in Inner Mongolia, Jilin, Heilongjiang, Liaoning Province in the northeast, as well as Hubei and Jiangsu Province. (4) About 1.55 % of counties nationwide have a comprehensive risk level of the HMP classified as “extremely high,” mainly distributed in Guangdong Province and Inner Mongolia. Additionally, some counties in Yunnan, Hunan, Jiangsu, Jiangxi, and Zhejiang Province have a risk of exceeding pollution standards, requiring further preventive measures to reduce pollution risks in the future. This paper can provide a scientific basis for the prevention and control (P&C) of the HMP in China.

Self-management behavior preferences and influencing factors in Chinese patients with recurrent gout: A qualitative study

ObjectiveThis study aimed to explore the preferences and influencing factors of self-management behaviors in patients with recurrent gout and provide a theoretical basis for developing targeted strategies to improve self-management preferences. MethodsA total of 10 patients with recurrent gout were recruited from the gout specialist outpatient clinic at a tertiary hospital in Shenyang, Liaoning Province, China. Semi-structured interviews were conducted with these patients, and the Kawakita Jiro (KJ) method was used to analyze the interview data. ResultsAfter four rounds of screening by five researchers, 35 codes were selected from an initial 132. After three rounds of discussion and induction, the KJ method identified seven domains of self-management behavior preferences in patients with recurrent gout: 1) extensive knowledge of gout, yet difficulty in distinguishing between accurate and inaccurate information; 2) a passive attitude of “no pain, no management”; 3) the challenge of changing entrenched daily habits; 4) the optimistic but unrealistic belief of “self-delusion”; 5) a tendency to seek medical attention late due to hopelessness of cure and familiarity with recurrences; 6) preference for analgesics for gout recurrences while neglecting long-term urate-lowering therapy (ULT); and 7) gout-related stigma. ConclusionThe results of this study showed that the self-management behavior of patients with recurrent gout could be improved, especially in the aspects of medical seeking behavior, medication compliance, daily management and emotional management. At the same time, we found that gout stigma, difficulty in distinguishing true and false knowledge of gout and negative attitude of “ignoring pain” were significantly associated with self-management behavior.

Research on Countermeasures for Promoting the Digital Transformation and Development of Agriculture in Liaoning Province

The digital economy is a new driving force for promoting high-quality economic development at present. Against the backdrop of rapid development of the digital economy, agricultural modernization has entered a new stage of development, bringing unprecedented opportunities and challenges to the digital transformation of agriculture in Liaoning Province. This article aims to systematically analyze the current situation and challenges faced by the digital transformation of agriculture in Liaoning Province, and propose corresponding countermeasures and suggestions, in order to provide practical experience that can be referenced for Liaoning Province and other regions in the country.

A new procercopid froghopper (Hemiptera: Cicadomorpha: Procercopidae) from the Lower Cretaceous Jiufotang Formation, western Liaoning Province, NE China

ABSTRACT A new procercopid species Stellularis kazuoensis sp. nov. is established and described from the Lower Cretaceous Jiufotang Formation in the Kazuo Basin, western Liaoning Province, NE China. It is characterised by the tegmen with singular RA, RP and M veins; vein M+CuA about half length of vein R; vein RA curved in apical area; and crossvein m-cua apicad of CuA2 end but basad of ir and r-m. The new species not only increases the diversity of Procercopidae but also provides more tegminal information of the genus Stellularis. The venational distinctions on tegmen between S. kazuoensis sp. nov. and the other species of Stellularis are schematically shown and discussed. The record of fossil insects from the Jiufotang Formation is also summarised.

Analysis of Spatial Distribution of Ecosystem Services and Driving Factors in Northeast China

Northeast China is an important ecological barrier in China, and an in-depth understanding of the spatial distribution in ecosystem services （ESs）, and the driving factors is crucial for realizing the subsequent management and protection of ESs. In the study, we quantitatively assessed the characteristics of spatial distribution in ESs in Northeastern China using the InVEST, RWEQ, and RUSLE models and identified the driving factors of ESs spatial distribution in conjunction with the geodetector based on meteorological data, remote sensing data, and socio-economic data. The results showed that the spatial distribution of ESs in Northeast China had obvious spatial heterogeneity. The high values of habitat quality （HQ）, carbon sequestration （CS） services, and soil conservation （SC） services were mainly distributed in the northern part of the four eastern leagues of the Inner Mongolia Autonomous Region, the northern part of Heilongjiang Province, and the eastern part of Northeast China, which were high in fraction vegetation cover, and low values were mainly found in southwestern and eastern Heilongjiang Province, western Jilin Province, and western Liaoning Province. The high values of the water yield （WY） service and wind prevention and sand fixation （WPSF） service were distributed in the east of the Inner Mongolia Autonomous Region and the east of Liaoning Province. The high values of WY services and WPSF services were distributed in the eastern part of Northeast China and the four eastern provinces of the Inner Mongolia Autonomous Region. According to the geodetector results, slope had the strongest explanatory power for the spatial distribution of SC services with a q-value of 0.31, land use/cover change had the strongest explanatory power for the spatial distribution of HQ and CS services with q-values of 0.64 and 0.52, respectively, and fraction vegetation coverage and annual precipitation had the strongest explanatory power for the spatial distribution of WPSF and WY services with q-values of 0.24 and 0.64, respectively, and there were interactions among all the driving factors. The spatial distribution of ESs in Northeast China was mainly influenced by natural factors. The results will provide a scientific basis for subsequent management and enhancement of ESs in Northeast China.

Effects of Industrial Structure on the Green Utilization Efficiency of Urban Land: A Case Study of the Bohai Rim Region, China

The green utilization of urban land is a critical component of regional high-quality development. Enhancing the green utilization efficiency of urban land (GUEUL) is of great significance to improving the quality of ecological environment and achieving a green lifestyle and low-carbon production. With the process of urbanization, the industrial structure is constantly adjusted, which has an impact on the structure and efficiency of urban land utilization. Taking 43 cities in the Bohai Rim region as an example, the super-efficiency slack-based measure model with undesirable outputs (super-SBM-undesirable model) was employed to evaluate the GUEUL from 2006 to 2021, and the panel quantile model was used to explore the impact of industrial structure on GUEUL. The results showed that the GUEUL in the Bohai Rim region appeared a fluctuating upward trend from 0.664 in 2006 to 0.837 in 2021. High-value zones shifted from western Liaoning province and southern Shandong province to a “C”-shaped belt around the coastline and expanded continuously, while low-value zones decreased significantly. Furthermore, the influence of industrial structure on GUEUL was significantly positive, but there were significant differences among different efficiency levels. Industrial structure upgrading exerted the most significant effect on GUEUL improvement in low-value zones, while industrial structure rationalization was dominant in high-value zones, and the influence of industrial structure technologization was more significant in medium-low-value zones. Therefore, differentiated industrial structure adjustment policies should be formulated based on the actual condition of each city to improve GUEUL.

Analysis of the Development and Influencing Factors of the County Economy in Liaoning Province

County economy is an important component of China’s national economy, and its development helps promote new urbanization and narrow the urban-rural economic gap. Liaoning Province relies on developing its county-level economy to promote industrial upgrading, poverty alleviation, rural revitalization and social development. In recent years, the development level of the county economy in Liaoning Province has significantly improved, but there are still problems, such as uneven economic development. Studying the development path of the county-level economy in Liaoning Province has practical significance. Based on the background of the new normal of China’s economy, this article analyzes the current development status, influencing factors and problems and challenges faced by the county-level economy in Liaoning Province and proposes countermeasures and suggestions for further promoting the development of the county-level economy.

Coordinated analysis of groundwater spatiotemporal chemical characteristics, water quality, and potential human health risks with sustainable development in semi-arid regions.

The emergence of large-scale time-series data and advancements in computational power have opened new avenues for analyzing the spatiotemporal evolution of groundwater chemistry, water quality, and human health risks. This paper utilizes hydrogeochemical methods to elucidate the controlling factors of water chemical components based on the test results of 124 groundwater samples collected from 31 monitoring wells in Fuxin City, Liaoning Province, China, from 2018 to 2021. By integrating the Random Forest and Enhanced Water Quality Index methods for water quality assessment and employing the Human Health Risk Assessment (HHRA) model to analyze human health risks, our findings indicate that the groundwater is mildly alkaline, with SO4·Cl-Ca·Mg and HCO3-Ca·Mg as the dominant hydrochemical types, primarily derived from the dissolution of carbonate and silicate minerals such as dolomite, limestone, and andesite, and cation exchange reactions. The EI_RF water quality evaluation model reveals that the overall water quality in the study area is poor, with Class I and II water quality zones mainly located in the northeastern and central parts of the study area, showing a gradual transition from Class I and II in the northeast to Classes IV and V in the southwest, significantly influenced by NO3-, TH, TDS, and SO42-. The HHRA model results indicate that the potential non-carcinogenic risk of groundwater nitrates has a severe impact on infants, with the spatial distribution being low in the northeast and high in the southwest. Due to industrial activities, agricultural practices, and population growth, certain areas in developing countries such as China and India exhibit nitrate concentrations significantly higher than those in most international regions, highlighting global environmental and public health challenges. This underscores the importance of enhancing groundwater monitoring and implementing measures to mitigate pollution. These research outcomes hold significant implications for the government in formulating rational protection and management measures to ensure the sustainable utilization of groundwater resources.

DECNet: Left Atrial Pulmonary Vein Class Imbalance Classification Network.

In clinical practice, the anatomical classification of pulmonary veins plays a crucial role in the preoperative assessment of atrial fibrillation radiofrequency ablation surgery. Accurate classification of pulmonary vein anatomy assists physicians in selecting appropriate mapping electrodes and avoids causing pulmonary arterial hypertension. Due to the diverse and subtly different anatomical classifications of pulmonary veins, as well as the imbalance in data distribution, deep learning models often exhibit poor expression capability in extracting deep features, leading to misjudgments and affecting classification accuracy. Therefore, in order to solve the problem of unbalanced classification of left atrial pulmonary veins, this paper proposes a network integrating multi-scale feature-enhanced attention and dual-feature extraction classifiers, called DECNet. The multi-scale feature-enhanced attention utilizes multi-scale information to guide the reinforcement of deep features, generating channel weights and spatial weights to enhance the expression capability of deep features. The dual-feature extraction classifier assigns a fixed number of channels to each category, equally evaluating all categories, thus alleviating the learning bias and overfitting caused by data imbalance. By combining the two, the expression capability of deep features is strengthened, achieving accurate classification of left atrial pulmonary vein morphology and providing support for subsequent clinical treatment. The proposed method is evaluated on datasets provided by the People's Hospital of Liaoning Province and the publicly available DermaMNIST dataset, achieving average accuracies of 78.81% and 83.44%, respectively, demonstrating the effectiveness of the proposed approach.

Psychometric properties of the chinese version of the value-based stigma inventory (VASI): a translation and validation study

ObjectiveThis study aimed to develop a culturally adapted Chinese version of the Value-based Stigma Inventory (VASI) and to evaluate its psychometric properties, including reliability and validity, among the general Chinese population.MethodsThis study is a cross-sectional study. Convenience sampling was used to recruit 708 general citizens from Shenyang City, Liaoning Province, China. The VASI’s internal consistency, split-half reliability, and test–retest reliability were tested to assess the translated scale’s reliability. Several validity tests were performed, including expert consultation, exploratory factor analysis, and confirmatory factor analysis. Data were analyzed using SPSS 25.0 (IBM Corp., Armonk, NY, United States) and AMOS 23.0 (IBM Corp., Armonk, NY, United States).ResultsThe Chinese version of the VASI showed good reliability, with a Cronbach’s α value of 0.808, and the dimensions ranged from 0.812 to 0.850. Test–retest reliability showed good temporal stability with a value of 0.855, and the split-half reliability value was 0.845, indicating a high degree of consistency. The scale also demonstrated good content validity with a content validity index of 0.952. After conducting exploratory factor analysis, a five-factor structure was identified, including factors of self-realization, personal enrichment, reputation, meritocratic values, and security. In the confirmatory factor analysis, all recommended fit indicators were found to be within the acceptable range, including χ2/DF = 1.338, GFI = 0.960, AGFI = 0.940, RMSEA = 0.031, TLI = 0.985, CFI = 0.989, IFI = 0.989, PGFI = 0.640, and PNFI = 0.729.ConclusionThe Chinese version of the VASI is valid and reliable among the Chinese general public. The five-factor structured scale effectively assessed public stigma against mental illness, including the value orientations associated with personal stigma. Given the harsh and widespread public stigma against mental illness, the findings from the questionnaire may inform the development of future public health education programs. Public health education is needed to reduce the stigma of mental illness, increase public awareness of mental health issues, and mitigate the continued stigmatization of mental illness.

Study on the relationship between net primary productivity and site quality in Japanese larch plantations in mountainous areas of eastern Liaoning.

Plantation forests enhance carbon storage in terrestrial ecosystems in China. Larix kaempferi (Lamb.) Carrière (Lamb.) (Larix olgensis Henry) is the main species for afforestation in the eastern Liaoning Province. Therefore, it is important to understand the correlation between the site class and carbon sink potential of Larix kaempferi plantations in Liaoning Province for afforestation and carbon sink in this area. The model was fitted using three classical theoretical growth equations: the Richards model, the Korf model, and the Hossfeld model. This study used the forest resource inventory data for management in Liaoning Province in 2011 to build six dynamic height-age models for a Larix kaempferi plantation in Dandong City regardless of base-age. The optimal model derived by the generalized algebraic difference approach (GADA) method was compared with the model derived by the algebraic difference approach (ADA) method. The superiority of GADA was demonstrated by comparison. The Levenberg-Marquardt algorithm was used to fit the model. The statistical and biological characteristics were considered synthetically when comparing the models. The best model was screened out by statistical analysis and graphic analysis. The results show that the differential height-age model derived from Richards equation can well explain the growth process of Larix kaempferi in Dandong City, Liaoning Province under different conditions. The site index model based on Richards equation and derived by GADA was used to calculate the site class of a Larix kaempferi plantation in Dandong City. The net primary productivity (NPP) value from the past ten years was extracted from the MOD17A3HGF data set. Spearman correlation analysis and Kendall correlation analysis were used to show that there is a significant positive correlation between NPP value and site class of Larix kaempferi plantation in Dandong City. Among them, the highest growth occurred in 2016; NPP increased by about 3.914 gC/m2/year for every two increases in height-age grade; the lowest increase in NPP was in 2014; NPP increased by about 2.113 gC/m2/year for every two increases in height-age grade; and for every two increases in height-age grade in the recent ten years, the average NPP value increased by about 2.731 gC/m2/year.

Analysis of the Characteristics and Mechanism of Spatial and Temporal Changes in Net Primary Productivity (NPP) in Northwest Liaoning Province

Analysis of the Characteristics and Mechanism of Spatial and Temporal Changes in Net Primary Productivity (NPP) in Northwest Liaoning Province

Ginkgoites manchurica from the Lower Cretaceous Shahezi Formation of Liaoning, China, and its palaeoclimate implications

The extreme greenhouse climate during the period of oceanic anoxic events (OAEs) in the Cretaceous is recognized based on marine stratigraphy, whereas the palaeoclimate remains poorly understood based on the terrestrial record due to the limitations of quantitative methods. The nearest living equivalent method, such as using the stomatal index of Ginkgo as a proxy, provides insight into reconstructing the terrestrial palaeoclimate during OAEs. However, due to the lack of well-preserved fossils with epidermal features and applicable quantitative methods, there are still controversies regarding the classification and nomenclature of species in the genus Ginkgoites, which have been assigned to Baiera, Ginkgo, or Ginkgoites. Here, we report well-preserved Ginkgoites fossil leaves from the Lower Cretaceous Shahezi Formation in Changtu County, Liaoning Province, Northeast China. The fossil dry leaf mass per area (LMA) was estimated as a quantitative morphological and ecological proxy. The LMA results of 192–241 g/m2 for different specimens are very close, suggesting that these homonyms should be assigned to the same species. Therefore, combining the detailed epidermal features and a quantitative morphological proxy (LMA), we summarized and amended the previously described fossils into Ginkgoites manchurica. Moreover, using the stomatal index of G. manchurica, the palaeo-atmospheric CO2 concentration was calculated at 1270 ppmv using the Barclay SI-pCO2 curve during the middle to late Aptian, indicating a typical greenhouse climate, which may be associated with the OAE global temperature increase event.

Prediction model for the quantity and density of first-order branches of Larix kaempferi in eastern area of Liaoning Province, China.

As an important branch characteristic factor, the quantity of branches could influence crown structure, tree growth, and wood quality. Taking Larix kaempferi plantation in Dagujia Forest Farm, Qingyuan County, Liao-ning Province as the research object, we developed a mixed effect prediction model of the first-order branches quantity of L. kaempferi including sprouting branches based on the negative binomial distribution model, and a mixed effect prediction model of the first-order branches density of L. kaempferi including sprouting branches based on the negative exponential model. The results showed that the mixed effect model considering sample level as the random effect effectively decreased the heteroscedasticity and autocorrelation. The fitting goodness was better than the traditional model. The quantity of the first-order branches increased with increasing crown ratio. The mixed effect model with the basic model intercept of the first-order branches quantity as the random effect parameter was determined as the optimal model, with Ra2=0.552 and the RMSE=7.242. As for the density of the first-order branches, the heteroscedasticity and autocorrelation were also reduced when the random effect was added. The density of the first-order increased with increasing crown ratio. The mixed effect model with the basic model intercept of the first-order branches density model and branch depth as random effects was determined as the optimal model, with Ra2=0.792 and the RMSE=4.447. The model for branch quantity and density of L. kaempferi constructed would lay an important foundation for making scientific forest management plans and improving wood quality.

Risk Factors of Mariculture Supply Chain Based on Green Development: A Case Study of Changhai County in China

China is a global leader in aquaculture, and mariculture has become an important part of Chinese agriculture and one of the important growth points of the rural economy. However, environmental changes and industrial restructuring have brought new risks to the aquaculture supply chain. Recently, people have also paid more and more attention to the marine environment because a good marine environment is the foundation of the healthy development of mariculture. This study analyses the risks in the aquaculture supply chain from the perspective of the marine environment, using Changhai County, Liaoning Province, as an example. The study identified marine environmental issues such as over-sized aquaculture, irrational aquaculture structure, resource integration gaps, nuclear wastewater discharge and offshore oil pollution. Recommendations included restructuring aquaculture, professional training, establishing cooperative mechanisms, and improving seafood quality testing and marine environment monitoring. Addressing these challenges is essential to ensure the stable and healthy development of seafood markets and the sustainability of the aquaculture industry.