Influence Of Factors Research Articles

Spatiotemporal variations of surface albedo in Central Asia and its influencing factors and confirmatory path analysis during the 21st century

Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 °C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.

Nitrogen fertilization and sowing date as wheat climate change adaptation tools under Mediterranean conditions

In the current situation, climate change has substantially disturbed precipitation occurrence in the Mediterranean region, by increasing its variability and decreasing the total annual amount, which both negatively affect rainfed crop productivity. We hypothesize that a simple cost-effective method for enhancing crop adaptation to new climate conditions would consist of modifying the crop sowing date. Traditional nitrogen (N) fertilization rates could also be adjusted to the current situation given the interdependent water/N relation in plant nutrition. Based on this hypothesis, during a 4-year field experiment with bread wheat (Triticum aestivum L., var. Pistolo), the effects of three sowing dates (October, November, February) and three N fertilization rates (54kgN ha-1, 27kgN ha-1, 0kgN ha-1) on crop development, yield, grain quality, soil N content and N use efficiency were analyzed. The results showed that water scarcity was the predominant limiting factor, because it outweighed N deficiency with half-fertilized crops being as productive as fully fertilized treatments. Nevertheless, sowing date was the most influential factor, with up to a 30% yield increase noted for the November-sown wheat compared to that sown in October, while delaying wheat sowing to February decreased crop yields. Grain protein content remained the same between the November- and October-sown crops, but increased in the February one crops. Optical sensor measurements showed that an optimal assessment of the current water/N nutritional status of crops can be achieved with these tools.

Predictive Factors of State Licensure Board Disciplinary Actions in Occupational Therapy.

One primary function of occupational therapy state licensure boards (SLBs) is the discipline of ethical misconduct by licensed occupational therapy practitioners. However, SLB sanctioning is poorly understood by practitioners, regulators, and the public. To identify predictors of occupational therapy practitioner sanctioning outcomes in the United States. Retrospective study; all public final consent orders and database entries provided online by SLBs were analyzed. Supervised gradient boosting machine learning, logistic regression, and contingency tables were used to generate odds ratios for variables associated with each sanctioning outcome. Multinomial testing was used to identify attribute overrepresentation among cases and national practitioner distributions. A total of 2,400 cases were analyzed across 47 states and Washington, DC. None. Numerous complaint and respondent attribute variables were collected from final consent orders and database entries. Complaint reason, practice setting, and complaint source had the highest influence on predicting sanction outcome; geographic region, number of complaints in a given case, and length of investigation in months were secondarily influential. Being male or a certified occupational therapy assistant was associated with higher odds of severe sanctioning outcomes. Disciplinary actions against occupational therapy practitioners were determined by numerous contextual factors; however, the most influential factors were complaint reason, practice setting, and complaint source. These results provide direction for exploring factors that predict sanctioning outcomes in the United States and also provide occupational therapy practitioners and SLBs a basis of applied outcomes that may improve implementation and education regarding clinical practice ethics. Plain-Language Summary: Occupational therapy state licensure boards (SLBs) are responsible for disciplining licensed occupational therapy practitioners for ethical misconduct. SLB sanctioning is poorly understood by practitioners, regulators, and the public. In this study, we identify the factors that predict the sanctioning outcomes of occupational therapy practitioners. The results may help state regulators, educators, and national associations more effectively act in a way that protects the public faith in occupational therapy services by providing contextualized information on practitioner behaviors that result in specific sanctioning outcomes. The study findings also provide occupational therapy practitioners and SLBs a basis of applied outcomes that may improve the implementation of and education regarding clinical practice ethics.

Iranian farmers' response to the drought crisis: How can the consequences of drought be reduced?

Climate change (CC) is an undeniable global phenomenon, impacting various regions, including Iran. Key components of CC, including the increase in greenhouse gases, rising temperatures, and fluctuations in precipitation patterns, are expected to significantly reduce agricultural crop yields in the near future. In response, identifying effective adaptation strategies is critical for mitigating these adverse effects. This study investigates the role of environmental values, risk perception, and psychological distance in shaping Iranian farmers’ adaptation strategies to CC. A sample of 390 farmers from Shushtar County in southwestern Iran was selected through a multi-stage stratified sampling method. Using structural equation modeling (SEM), the analysis revealed complex interrelationships between environmental values (biospheric, altruistic, and egoistic), beliefs, risk perception, psychological distance, and farmers' adaptation responses to CC. Furthermore, the results indicated that the study variables explain 67.6% of the variance in farmers' adaptive behaviors, with belief in CC emerging as the most influential factor. These findings not only enrich the current body of literature but also provide actionable insights for policymakers to foster adaptive strategies among farmers.

Factors influencing dementia patients' participation in advance care planning: A meta-analysis

ObjectiveA meta-analysis was conducted based on the available evidence to determine the influencing factors associated with the participation of people with dementia in advance care planning. MethodsA keyword search was performed in seven databases, Web of Science, PubMed, Embase, Cochrane Library, CINAHL, Scopus, and Void, to search for eligible studies published from the time of library construction up to February 1, 2024, to examine the factors influencing the participation of dementia patients in advance care planning and its effects. The quality of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS) and the assessment criteria of the Agency for Healthcare Research and Quality (AHRQ). After literature search, data extraction and quality assessment were completed independently by two researchers, meta-analysis was performed using Stata software 15.0 to pool the odds ratios (OR) and 95% confidence intervals (CI). Heterogeneity between studies was assessed using the Cochran chi-square test (Cochran 's Q) and I2 values. ResultsA total of 19 studies were included in this study, and Meta-analysis showed that 8 of the 16 influencing factors were statistically significant: Patients' gender (OR=1.17; 95%: 1.13–1.2), age (OR=1.07; 95%: 1.03–1.1), education (OR=1.98; 95%: 1.65–2.38), race (OR=2.61; 95%: 1.67–4.08), the severity of the dementia (OR=1.46; 95%: 1.34- 1.58), ability to perform activities of daily living (OR=0.99; 95%: 0.97–1.0), religious affiliation (OR=2.24; 95%: 1.23–4.06), and patient income(OR=2.10; 95%: 1.47–2.98) were associated with participation in advance care planning. ConclusionsThe participation of dementia patients in advance care planning is influenced by gender, age, education, race, dementia severity, ability to perform activities of daily living, religious affiliation and patient income. The results of the study can inform the development of targeted interventions for dementia patients, thereby reducing overtreatment of dementia patients at the end of life and improving patient adherence to hospice care.

A Novel Multi-compartment Rotating Bioreactor for Improving ADSC-Spheroid Formation and its Application in Neurogenic Erectile Dysfunction.

The aim of this study was to construct a multicompartment synchronous rotating bioreactor (MCSRB) for batch-production of homogenized adipose-derived stem cell (ADSC) microspheres and treat neurogenic erectile dysfunction (ED). Firstly, an MCSRB was constructed using a centrifugal device and hinged trays. Secondly, influence factors (density, rotational speed) on the formation of ADSC-spheroids were explored. Finally, a neurogenic ED model was established to verify the effectiveness and safety of ADSC-spheroids for ED treatment. An MCSRB promoted ADSCs to gather microspheres, most of which were 90-130 μm in diameter. Supernatant from three-dimensional culture led to a significant increase in cytokine expression in ADSCs and migration rate in human umbilical vein endothelial cells (HUVECs) compared to control groups. The erectile function and pathological changes of the penis were improved in the ADSC-spheroids treatment group compared to the traditional ADSCs treatment group (p < 0.01). Efficient, batch, controlled and homogenized production of ADSC stem cell microspheres, and effective improvement of erectile dysfunction in neurogenic rats can be achieved using the MCSRB device.

Analysis of Canopy Interception Characteristics and Influencing Factors in Typical Artificial Forest in the Loess Plateau Semi-Arid Region

Interception loss (IL) is an important process in the hydrological cycle within semi-arid forest ecosystems, directly affecting the amount of effective rainfall. However, the factors influencing IL during individual rainfall events remain to be quantified. This study collected rainfall, vegetation, and interception data during the 2022 and 2023 growing seasons in a typical black locust forest within the Zhifanggou watershed. It employed the Random Forest Regression (RFR) and back-propagation neural network (BPNN) methods to quantitatively evaluate the contribution rates of various factors to the IL and interception loss percentage (ILP). The IL among the 48 effective rainfall events was 172.05 mm, accounting for 19.54% of the rainfall amount. IL and ILP increased as the distance from the trunk decreased. During all rainfall events, both IL and ILP were significantly negatively correlated with the leaf area index (LAI) and canopy cover (CC); IL is significantly positively correlated with total rainfall (TR) and rainfall intensity (RI), while ILP is significantly negatively correlated with TR, RI, and rainfall duration (RD). The BPNN and RFR results indicated that rainfall, canopy, and tree characteristics contributed 43.06%, 44.79%, and 12.15% to IL, respectively, and 57.27%, 34.09%, and 8.63% to ILP, respectively. TR, CC, and LAI represented the primary influencing factors. Rainfall and canopy characteristics were the main factors affecting IL (ILP). As rainfall event magnitude increases, canopy contributions to IL and ILP decrease. In semi-arid areas, managing forest canopies to control IL helps address water imbalances in ecosystems.

Employing stable isotopes to reveal temporal trajectories of water travelling through the soil–plant-atmosphere continuum

The spatiotemporal patterns of water travelling through the soil–plant-atmosphere continuum (SPAC) have received much attention due to the frequency of extreme weather and water scarcity. However, the interconnections and transboundary transport of specific compartments within the hydrologic cycle are poorly understood. We portrayed the propagation paths of water isotope signals by analyzing isotopes of precipitation, soil water, and xylem water. The isotope sine curves analysis method was improved to quantify water transfer efficiency, mean transmission time from precipitation to soil (MTT1), mean transmission time from soil to trees (MTT2), mean residence time within soil (MRTSW), and mean residence time within tree xylems (MRTXY). The temporal trajectory of water traveling through SPAC was depicted, and its influencing factors and intrinsic mechanisms were explored. Our results showed that (1) water isotopes were blocked when crossing water pools (precipitation, soil water, and xylem water) and the transfer efficiency was progressively weaker (85.5 %→13.5 %). (2) The MTT1 was significantly and positively correlated with soil porosity (Spearman correlation coefficient, 0.551). Its spatiotemporal pattern (0.8–15.9d) indicated that the transport and mixing of soil water involved two modes: displacement flow and bypass flow. The MTT2 (−13.2d–4.3d) of Platycadus orientalis was in general smaller than that of Quercus variabilis (−4.7d–11.5d). (3) The MRT (35.2d–343.8d) was influenced by a combination of soil physicochemical properties, root distribution, and tree morphological traits. Our study shows that connectivity between pools is better reflected with transfer efficiency. Comparing MTT and MRT of P. orientalis and Q. variabilis, tree hydrodynamic processes were quantified, and P. orientalis was more sensitive to seasonal moisture variability. Additionally, our study improved the understanding of the “black box” within the hydrological interface of plant-soil interactions.

A New Test for Evaluating the Psychological Impact of COVID-19 in Nurses

Introduction During the COVID-19 pandemic, many health care workers were involved and suffered significant physical and psychological strain, and nursing was one of the main players. Clearly and objectively establishing the psychological impact on nurses during the pandemic is necessary for long-term recovery and to be prepared for new outbreaks in the future. Aim The aims of this study were to evaluate the perceived impact on nurses at risk of psychological stress at work during a major health care crisis and determine the psychological impact and its influencing factors. Methods An online questionnaire was designed and distributed between April 9 and April 19, 2020, in Spain. The comprehensive self-conducted questionnaire included demographic information and the Psychological Stress and Adaptation at work Score. For the analysis, descriptive statistics, logistic regressions, and receiver operating characteristic curves were determined. Results A total of 825 nurses (33% working in intensive care units and emergency departments) answered the questionnaire. A logistic regression analysis revealed that nurses with higher psychological stress scores experienced more physical overload (P = .02), higher psychological overload (P &lt; .01), poor teamwork (P = .02), more distress due to new circumstances (P &lt; .01), more personal impact of how society responded to COVID-19 (P &lt; .01), anticipation of negative future consequences (P &lt; .01), and worse balance between family and work (P &lt; .01). The area under the curve for the cutoff point of Psychological Stress and Adaptation at work Score 40 was 0.82 (95% confidence interval, 0.79-0.91), with 70% sensitivity and 81% specificity. The positive predictive value was 72%, and the negative predictive value was 80%. Conclusion Psychological Stress and Adaptation at work Score is a rapid and accurate test for evaluating the psychological well-being of health care staff that can be used when crisis prevents the use of conventional stress diagnosis methods. Higher psychological impact was observed in nurses who worked in the intensive care unit and in the hospital ward.

Coupling and coordination of food security and agricultural carbon emission efficiency: Changing trends, influencing factors, and different government priority scenarios

Seeking a balance between food security and carbon mitigation is key to achieving sustainable agricultural development. This study evaluates the coupling coordination degree (CCD) between the food security index (FSI) and agricultural carbon emission efficiency (ACEE) in China from 2010 to 2021 using the coupled coordination model. By adjusting the model coefficients, different government priority scenarios are simulated to explore their impact on CCD. The Geodetector method is employed to identify the influencing factors of CCD, investigate their interactions, and assess the differences in these factors across various government priority settings. The average CCD between FSI and ACEE exhibits a notable upward trend, rising from 0.4583 in 2010 to 0.6595 in 2021. Furthermore, regional disparities are widening, particularly in the major production areas. Catch-up effects exist within regions. Policy simulations showed staged interactions between food security and agricultural carbon efficiency, shifting from food security to balanced production and ecology, then to prioritizing low-carbon production for food security. Adjusting policy priorities can effectively improve coupling coordination in the short term, with increasing impact as priority shifts. CCD is influenced by policy, technology, economy, and society, varying with policy priorities. In the baseline scenario, key factors for CCD include the urban-rural income gap, technological advancement, urbanization, and farmers' education level. When the government prioritizes food security, the impact of narrowing income gaps and agricultural industry agglomeration becomes more pronounced. Conversely, emphasizing carbon emission efficiency enhances the influence of technological advancements and urbanization on CCD. Tailoring agricultural production strategies to local conditions and emphasizing interactive effects among factors is crucial for achieving environmentally friendly and high-quality agricultural development goals.

Gender-specific factors of suicidal ideation among high school students in Yunnan province, China: A machine learning approach.

Suicidal ideation (SI) assumes a pivotal role in predicting suicidal behaviors. The incidence of SI among high (junior and senior) school students is significantly higher than that of other age groups. The aim of this study is to explore the gender differences in SI among high school students in Yunnan Province. A total of 6180 students in grades 7-12 in Yunnan province, China from May 2021 to May 2022 participated in this survey. Univariate analysis was employed to describe the influencing factors of male and female students' SI. Subsequently, data were stratified by gender. Adopting machine learning technique, including Least Absolute Shrinkage and Selection Operator (Lasso) and Boruta algorithm, and logistic regression model to estimate the direction and effect magnitude of the influencing factors. The prevalence of SI was significantly higher for females (31.34%) than males (16.73%). The logistic regression model was established using the variables screened by Boruta algorithm, indicated that anxiety, depression, suffering emotion abuse or emotion neglect in childhood, non-suicidal self-injury, evening chronotype are common risk factors for SI in male and female students. Notably, female students who exhibited aggressive behavior, have experienced bullying, and were in the junior high school learning stage were more likely to report SI than their male counterparts. Females showed more vulnerability to SI than males especially among females in junior high school, reporting aggressive behavior and bullying experiences. Tailored prevention strategies, informed by these gender-related distinctions, should be developed and implemented.

Technocratic reason in hard times: the mobilisation of economic knowledge and the discursive politics of Brexit

ABSTRACT In the context of the debate surrounding and following the Brexit referendum in June 2016, credentialed economic expertise did not enjoy a privileged position within the political and policy debate. Using the contrasting cases of the Office for Budget Responsibility and Economists for Brexit/Free Trade, this paper explores the mobilisation of economic expertise within the discursive politics of Brexit under conditions of pervasive radical uncertainty. It argues that politicisation is an important factor in side-lining technocratic influence over policy choice, but that the particular type of politicisation in play (plebiscitary) meant that the input of technocratic experts was downgraded. It is a politics conducted in another register to the reasoned, evidence-based vernacular of accredited experts and the policy discourses that they work with and through. We also argue that the basic unknowability of the post-Brexit economy further impaired expert input. These limitations were acknowledged by accredited experts themselves, reducing their traction within the policy debate. This unknowability was exploited by forms of counter-expertise mobilised by the Leave campaign. The radical uncertainties of Brexit allowed in heterodox assumptions and approaches to compete on a level playing field with an approximation of what could be presented as prudent best practice.

Unveiling trends in migration of iron-based nanoparticles in saturated porous media

Nanoscale zero-valent iron (nZVI) particles are routinely used for environmental remediation, but their transport dynamics in different settings remain unclear, hindering optimization. This study introduces a novel approach to predicting nZVI transport in saturated porous model environment. The method employs advanced long column devices for real-time monitoring via controlled magnetic susceptibility measurements. Numerical modeling with a modified version of the MNMs 2023 software was then used to predict nZVI and its derivatives mobility in field-like conditions, offering insights into the radius of influence (ROI) and shape factor (SF) of their distribution. A standard nZVI precursor was compared with its four major commercial derivatives: nitrided, polyacrylic acid-coated, oxide-passivated, and sulfidated nZVI. All these iron-based nanoparticles exhibited identical particle sizes, morphologies, surface areas, and phase compositions, isolating surface properties, dominated by charge, as the sole variable affecting their mobility. The study revealed optimal transport when the surface charge of nZVI and its derivatives was strongly negative, while rapid aggregation of nZVI derivatives due magnetic attraction reduced their mobility. Modeling predictions based on column scale-up, indicated that detectable concentrations of 20 g L⁻1 were found at distances ranging from 0.4 to 1.1 m from the injection well. Slightly sulfidated nZVI traveled farther than the nZVI precursor and ensured more homogenous particle distribution around the well. Organically modified nZVI migrated the longest distances but showed particle accumulation close to the injection point. The findings suggest that minimal sulfidation combined with organic modification of nZVI surfaces may effectively enhance radial and vertical nZVI distribution in aquifers. Such improvements increase the commercial viability of modified nZVI, reduce their adverse impacts, and boosts their practical applications in real-world scenarios.

Impacts of root exudates on the toxic response of Chrysanthemum coronarium L. to the co-pollution of nanoplastic particles and tetracycline

Nano polystyrene (PS) particles and antibiotics universally co-exist, posing a threat to crop plants and hence human health, nevertheless, there is limited research on their combined toxic effects along with major influential factors, especially root exudates, on crop plants. This study aimed to investigate the response of Chrysanthemum coronarium L. to the co-pollution of nanoplastics and tetracycline (TC), as well as the effect of root exudates on this response. Based on a hydroponic experiment, the biochemical and physiological indices of Chrysanthemum coronarium L. were measured after 7 days of exposure. Results revealed that the co-pollution of TC and PS caused significant oxidative damage to the plants, resulting in reduced biomass. Amongst the two contaminants, TC played a more prominent role. PS could enter the root tissue, and the uptake of TC and PS by plant roots was synergetic. Malic acid, oxalic acid, and formic acid could explain 65.1% of the variation in biochemical parameters and biomass of the roots. These compounds affected the photosynthesis and biomass of Chrysanthemum coronarium L. by gradually lowering root reactive oxygen species (ROS) and leaf ROS. In contrast, the impact of rhizobacteria on the toxic response of the plants was relatively minor. These findings suggested that root exudates could alleviate the toxic response of plants to the co-pollution of TC and PS. This study enhances our understanding of the role of root exudates, providing insights for agricultural management and ensuring food safety.

Global spatial and temporal dynamics of the green water coefficient and analysis of factor from 1992 to 2020

In recent years, the impacts of climate change have variably affected the global ecological environment, exacerbating water scarcity and related issues. Meantime, as part of soil evapotranspiration and plant transpiration in water resources, green water is of great significance in stabilizing the global water cycle and promoting the sustainable development of agriculture. Therefore, the green water coefficient in this study calculates the conversion rate of precipitation to green water, which is important for the balance between blue and green water and the stability of the ecological environment. Based on trend analysis methods and Geodetector, this study analyses the spatial and temporal characteristics and driving mechanisms of the green water coefficient on the globe and on each land-use type from 1992 to 2020. The findings revealed that: (1) The global green water coefficient is clearly spatially differentiated, showing certain latitudinal distribution differences, with the lowest near the equator. The areas with higher green water coefficients are mainly in northern and southern Africa, central Asia, Oceania and northern and western North America, while the areas with lower green water coefficients are concentrated in northern South America and Southeast Asia. (2) The global average value of green water coefficient decreases before increasing. Except for water, the green water coefficient of other land use types (crop land, forest land, grassland, urban land, unused land) changes significantly and there are fewer abrupt change points. Areas where the green water coefficient is too low and changes drastically are not suitable for rainfed agriculture. (3) Different influential factors act on the green water coefficients of different land use types, and there is a two-factor enhancement and non-linear enhancement relationship between them, with a combination of factors affecting the green water coefficient. By studying the characteristics of the green water coefficient globally and across different land use types, we quantified the influence of climate factors such as precipitation, temperature, wind speed, evapotranspiration, radiation, etc., on the green water coefficient, thereby providing some information for future global rain-fed agriculture and water resources management.

Photocatalytic ZnIn2S4 for 2-Mercaptobenzothiazole Degradation: Facile Synthesis, Influencing Factors and Mechanism

The development of an efficient, stable and environmentally friendly semiconductor photocatalyst is great research significance in the field of environment and energy. In this paper, ZnIn2S4 semiconductor photocatalysts with flower-like hierarchies were prepared by simple and environmentally friendly method. The influence of ZnIn2S4 dosage, pH and different inorganic salt ions on the photocatalytic degradation of 2-mercaptobenzothiazole (MBT) under visible light was investigated in detail. The results showed that the photocatalyst dosage was 0.05 g, and the photocatalytic degradation efficiency of MBT was the highest in the weakly acidic environment with pH was five. Meanwhile, the addition of some inorganic anions has a significant inhibitory effect on the photocatalytic activity of ZnIn2S4 semiconductor photocatalyst, while cations have less effect. Moreover, the ZnIn2S4 semiconductor photocatalyst had excellent stability and recyclability, and its photodegradation mechanism had been deeply studied. This work provides a theoretical and experimental foundation for exploring the different influencing factors of photocatalytic degradation of organic pollutants in wastewater by other semiconductors.

Influential factors in the consumption of water by schoolchildren in Mexico

Purpose Based on the assumptions of the social ecological theory (SET), this study aims to identify the factors that influence water consumption by the schoolchildren segment in urban communities in Mexico, to further develop a community-based social marketing intervention. Design/methodology/approach This study was formative research, quantitative and qualitative in nature, consisting of a survey, focus groups and in-depth interviews. It was conducted in public and private elementary schools in central Mexico (five states), during 2023. Findings It was identified that parents are aware of the benefits of drinking water for their children’s health. However, various factors in the sociocultural environment, perceptions, customs and habits were noted as barriers to water consumption. Consequently, children’s behaviors are influenced by their family context as the strongest environment. Likewise, the school environment and the social environment are identified as other influential factors. Each system acts as a motivator or barrier in the child’s behavior, creating and supporting consumption behaviors learned from an early age. Originality/value Interventions on water consumption should target the most influential SET systems; the microsystem and the mesosystem, achieving the participation and co-responsibility of stakeholders in changing the environment and thus behavior.

Investigation of mechanical properties in FFF- produced PLA samples using the Erichsen test: application of definitive screening and RSM

Purpose This study aims to investigate how printing parameters affect the mechanical properties of specimens produced through fused filament fabrication, using the Erichsen test to assess deformation characteristics and material durability under stress. Design/methodology/approach Polylactic acid (PLA) specimens were printed and tested in accordance with the ISO 20482 standard. Definitive screening was conducted to identify the most influential process parameters. This study examined the effects of four key process parameters – number of layers, layer height, crossing angle and nozzle diameter – on force, distension, peak energy and energy to break. Each parameter was assessed at three levels and a large number of required experiments was managed by using response surface methodology (RSM). Findings This study revealed that the number of layers, layer height and crossing angle are the most significant factors that influence the mechanical properties of 3D-printed materials. The number of layers had the greatest impact on the peak force, contributing 44.25%, with thicker layers typically enhancing material strength. The layer height has a significant effect on energy absorption and deformation, with greater layer heights generally improving these properties. Nozzle diameter contributed only 1.10%, making it the least influential factor; however, its impact became more pronounced in interactions with other parameters. Originality/value This paper presents a comprehensive experimental investigation into the effects of process parameters on the crack strength and behavior of 3D-printed PLA specimens using the RSM method. The documented results can be used to develop optimization models aimed at achieving desired mechanical properties with reduced variation and uncertainty in the final product.

Research on Factors Influencing Housing Price based on Principle Component Analysis and Polynomial Regression

Housing price is influenced by natural, social, economic and other factors. Only by understanding and conducting specific research on these influencing factors can people grasp the laws of housing price movements. Focusing on this issue, this paper chooses the average unit housing prices and their influencing factors of 11 cities in Zhejiang Province in 2022 as the research objects, then establishes a model reflecting the quantitative relationship between housing price and influencing factors. Firstly, relevant data is collected from official websites, including housing prices and 10 main influencing factor indicators of above cities. Secondly, principal component analysis is used for data preprocessing, and five prominent indicators are selected by calculating the relative contribution rate of each factor. Then, by drawing functional images and solving correlation coefficients, a qualitative analysis is conducted on the basic algebraic structure of the regression model. The results indicate that all independent variables include independent terms and cross-terms. Subsequently, through polynomial regression, data matrices for both dependent variable and independent variables are set to solve the coefficients of constant term, linear terms, quadratic independent terms and quadratic cross-terms respectively. Therefore, a model of factors influencing housing price is established. Finally, residuals sum of squares, mean square error, regression sum of squares and determination coefficient are calculated in sequence for the regression model. It turns out that all the statistics are within the ideal range, indicating high precision of data fitting and verifying the accuracy and reliability of the model.

Spatiotemporal Variations in Gross Ecosystem Product and Its Relationship with Economic Growth in Ecologically Vulnerable Watershed Areas: A Case Study of Yongding River Basin

Ecosystem service value is crucial for balancing economic growth and ecological preservation in ecologically vulnerable watershed areas. Although Gross Ecosystem Product (GEP) has received significant attention, most existing studies have focused on how to measure it. Few studies have explored spatiotemporal variations in GEP and how land-use changes affect these variations regarding ecological restoration at the river basin level. Additionally, while many studies have examined the relationship between ecosystem service value and economic growth, there is little research on how components of GEP influence economic growth. Analyzing the spatiotemporal structure of GEP and its components could offer new insights into optimizing ecological restoration strategies and promoting sustainable development in vulnerable watershed regions. In this study, we used ArcGIS, InVEST, SPSS, and Python to analyze spatiotemporal variations in GEP in the Yongding River Basin within the Beijing–Tianjin–Hebei Economic Region from 1995 to 2020. Moran’s Index and variance decomposition were applied to analyze the spatiotemporal structure. The grey prediction model forecasted GEP trends from 2025 to 2035. The random forest model was used to assess land-use changes’ impacts on GEP. Paired T-tests were used to compare GEP and GDP, and a dynamic panel model was used to examine how ecosystem service value factors influenced economic growth. The results show the following: (1) Regarding values, GEP accounting and variance decomposition results indicated that ecosystem cultural service value (ECV) and ecosystem regulating service value (ERV) each contributed about half of the total GEP. Ecosystem provisioning service value (EPV) showed an upward trend with fluctuations. Regarding the spatial distribution, Moran’s I analysis showed significant positive spatial correlations for EPV and ERV. The grey prediction model results indicated significant growth in GEP from 2025 to 2035 under current ecological restoration policies, especially for ERV and ECV. (2) In terms of the influence of land-use changes, random forest analysis showed that the forest land area was consistently the most influential factor across GEP, EPV, and ERV. Unused land area was identified as the most significant factor for ECV. (3) Before 2010, GEP was larger than GDP, with significant differences between 1995 and 2000. From 2010 onwards, GDP surpassed GEP, but the differences were not statistically significant. Dynamic panel regression further showed that the water conservation value significantly boosted GDP, whereas the water purification value significantly reduced it. This study highlights the importance of integrating GEP into ecological restoration and economic development to ensure the sustainability of ecologically vulnerable watershed areas.