Analysis Of Influencing Factors Research Articles

Quantification of multiscale links of key factors with watershed nitrogen and sediment exports based on a Bayesian modelling approach

The identification of key influencing factors of nonpoint source pollution is important to control such pollution in watersheds. The choice of spatial scale is vital in influencing factor analysis. However, many previous analyses were only carried out on a specific scale or evaluated different topics on different scales, which could not integrate various information of different scales. In this study, a multiscale approach based on Bayesian belief networks (BBNs), which can quantify the links between watershed nitrogen and sediment exports and their key factors, was developed. The main results indicated that influencing factors have relatively higher level of importance, i.e. higher degree of interpretation, at town scale or subcatchment scale compared with 1 km2 scale. Key factor set based on the nesting of town scale and subcatchment scale (i.e., town_sub scale) predict nitrogen and sediment exports better than those based on three separate scales (1 km2 scale, subcatchment scale and town scale), which implies that multiscale nesting reflects more comprehensive information about watershed processes. Moreover, different nitrogen and sediment reduction targets were achieved through land use changes and resulting economic benefits or losses were compared across three scales (subcatchment scale, town scale and town_sub scale). A relatively more appropriate scale with the lowest economic loss was determined. The decreased cultivated land and increased woodland and waterbody areas mostly contributed to the reductions in nitrogen and sediment exports and the economic loss of each reduction target. When achieving the same nitrogen and sediment reduction targets, the economic loss resulting from the land use changes at the subcatchment scale was lowest, followed by the town_sub and town scales. This multiscale approach attempted to determine how key factors with the highest level of importance at different scales and watershed nonpoint source pollution can be connected, which would better inform the management of watershed nonpoint source pollution.

Spatial interaction effects on the relationship between agricultural economic and planting non-point source pollution in China.

Solving the contradiction between agricultural economic growth and agricultural environmental problems is a difficult problem in regional environmental governance. Based on the panel data of 31 provinces, municipalities, and autonomous regions in China from 2000 to 2019, spatial Dubin model (SDM) is used to analyze the influence of agricultural economic growth and other factors on planting non-point source pollution. Innovate from the perspective of research objects and research methods, and the research results show (1) In the past 20years, the amount of fertilizer applied and crop straw yield increased continuously. Through the fertilizer and farmland solid waste discharge of ammonia nitrogen (NH3-N), total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD), calculation of the equal-standard discharges of planting non-point source pollution shows that China's planting non-point source pollution is serious. Among the investigated areas in 2019, the equal-standard discharges of planting non-point source pollution in Heilongjiang Province were the highest and have reached 24.35 × 1010 m3. (2) The global Moran index of 20years in the study area shows obvious spatial aggregation and diffusion characteristics, and has a significant positive global spatial autocorrelation, indicating that planting non-point source pollution discharges of the study area have potential interdependence in space. (3) SDM time-fixed effect model showed that the equal-standard discharges of planting non-point source pollution had a significant negative spatial spillover effect, and the spatial lag coefficient was - 0.11. Among the influencing factors, agricultural economic growth, technological progress, financial support to agriculture level, consumption capacity, industrial structure, and risk perception have significant spatial spillover effects on planting non-point source pollution. The results of effect decomposition show that the positive spatial spillover effect of agricultural economic growth on adjacent areas is greater than the negative effect on the local area. Based on the analysis of significant influencing factors, the paper provides direction guidance for the formulation of planting non-point source pollution control policy.

A readiness assessment framework for the adoption of 5G based smart-living services

The subject of this article is to analyze the users’ attitude towards new, 5G-enabled smart living services before their commercial launch. The goal is to offer a framework for the analysis and evaluation of influential factors in the early adoption of 5G residential services. Additionally, the paper examines how mobile operators can leverage their existing infrastructure and services to boost the acceptance of both 5G as a technology and the provided smart-living services. To ascertain the potential impact that mobile operators can have on the adoption of such services, loyalty programs were taken into account as a separate factor in the acceptance study. The study was conducted in Serbia in the form of a survey. The analysis of the results yielded some notable conclusions such as trust in technology playing the leading role in influencing the behavior intention, while loyalty programs showed that they can influence attitudes towards individual smart living services. The presented results can be used to shape any future implementation of 5G-based services in Serbia, or any other country whose 5G infrastructure and services for the residential customer segment are yet to be established.

Elderly people’s preferences for healthcare facilities in Shanghai: gender features and influencing factor analysis

BackgroundChina has one of the fastest paces of the growing aging population, High-level policymakers have recently recognized the aging population presents significant challenges to the Chinese healthcare system. In this context, the healthcare-seeking behaviors of the elderly population have become an essential field of study. It is necessary to understand their access to health services and to improve their quality of life, as well as to help policymakers to formulate healthcare policy. The study empirically investigates the factors influencing the elderly population’s healthcare-seeking behaviors in Shanghai, China, especially in choosing the quality of healthcare facilities to visit.MethodsWe designed a cross-sectional study. The data of this study were derived from the “Shanghai elderly medical demand characteristics questionnaire” in the middle of November to early December 2017. A total of 625 individuals were included in the final sample. Logistic regression was adopted to investigate the differences in healthcare-seeking behaviors between elderly people when suffer from mild illness, severe illness and follow-up treatment. Next, the differences in gender were also discussed.ResultsFactors affecting the healthcare-seeking behaviors of the elderly differ in mild illness and severe illness situations. For mild illness, demographic factors (gender and age) and socioeconomic factors (income and employment) play an important role in elderly healthcare choices. Female and older elderlies are more likely to choose local, lower-quality facilities, whereas those with high income and private employment are more likely to choose higher-quality facilities. For severe illness, socioeconomic factors (income and employment) are important. Furthermore, individuals with basic medical insurance are more likely to choose lower-quality facilities.ConclusionThis study has shown that the affordability of public health services should be addressed. Medical policy support may be an important way to reduce the gap in access to medical services. We should pay attention to the gender differences in the elderly’s choice of medical treatment behavior, consider the differences in the needs of male and female elderly. our findings are only for elderly Chinese participants in the greater Shanghai area.

Association between serum uric acid levels of patients with gout and their complications and examination fees: A cross-sectional analysis.

Correlation influence factor analysis of gout patients' serum uric acid (SUA) levels, their examination fees, and various complications were explored. From January 2017 to December 2021, 17 666 patients with gout were obtained. Conduct quartile grouping according to gout patients' SUA levels was used to compare the differences between groups in terms of examination fees and complications. Kernel density estimation method was adopted to analyze the data distribution, Spearman and Mantel-Haenszel χ2 tests were used to analyze the correlation between SUA levels and examination fees and complications. Binary logistic regression analysis was used to analyze the correlation influence factor between SUA levels and complications. Of the 17 666 gout cases, 85.46% were male. Among them, 7637 (43.23%) were inpatients and 10029 (56.77%) were outpatients. Compared with outpatients, age, SUA levels, and examination fees were significantly higher, and there were more complications among inpatients (P < 0.05). Correlation analysis revealed that outpatients and SUA levels of patients with gout were positively correlated with examination fees, cardiovascular diseases, pulmonary diseases, liver diseases, and kidney diseases (P < 0.01). Binary logistic regression analysis showed that SUA level is an independent influence factor for cardiovascular diseases, pulmonary diseases, liver diseases, and kidney diseases (odds ratio [95% confidence interval]: 1.002 [1.002-1.002], 1.001 [1.000-1.001], 1.003 [1.002-1.003], and 1.001 [1.001-1.002], respectively). As SUA levels increased, examination fees, cardiovascular disease, pulmonary disease, liver disease, and kidney disease complications increased. SUA level is an independent influence factor for the combination of gout with cardiovascular diseases, pulmonary diseases, liver diseases, and kidney diseases.

Analysis of the Most Influential Factors on Customer Satisfaction

Purpose – This paper seeks to determine factors which more influenced to customer satisfaction at PT Pantara Wisata Jaya Seribu Islands Resort? These factors were price, and service quality. Researcher have a tested to price on customer satisfaction partially, and service quality on customer satisfaction partially, including price and services quality on customer satisfaction simultaneously. Methodology/approach – This research used associative quantitative methods by using SPSS 26 to process the research data. The sample collection technique used simple random sampling technique. The sample was calculated by using the Slovin formula where 92 respondents were selected.Findings –The results of simultaneous test (f- test) of price and service quality have a significant influence on customer satisfaction. Service quality factor more influenced on customer satisfaction as per t-test resulted. Researcher found that 45% of independent variables price and service quality on customer satisfaction , and 55% was influenced by other variables which not examined. Novelty/value – As customer satisfaction has been an important factor in resort business, especially for Indonesia to increase economic growth, it is vital to understand how to maintain customer satisfaction in resort business.

Estimation of fatigue life of welded structures incorporating importance analysis of influence factors: A data-driven approach

The fatigue life prediction of welded joints with different specifications under different conditions was a challenging issue due to the quite complex influence. Specifically, the current fatigue life prediction methods lacked comprehensive analysis of multiple influence factors and reasonable incorporation of physical models. So, the analysis of factors influencing the fatigue life of welded joints and the fatigue life prediction were critical to the safety and reliability of engineering structures. In this study, a prediction approach for fatigue performance was proposed based on influence factor analysis using data-driven methods. The fatigue performance dataset was processed via physical models to realize the physics-based analysis of the factors affecting fatigue performance. The weights of the physics-informed influence factors on the fatigue life were analyzed using the extreme gradient boosting (XGBoost) algorithm and verified by cross-validation. The prediction results extracted from the SN curves predicted by the deep convolutional neural network (DCNN) model incorporating the weight analysis of influence factors exhibited better accuracy and stability than direct prediction and other existing prediction models. Because of the advantages of DCNN in avoiding over fitting and local optimization, the proposed approach can better describe and estimate the fatigue performance of welded structures.

Interpretable machine learning for maximum corrosion depth and influence factor analysis

We have employed interpretable methods to uncover the black-box model of the machine learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines. Ensemble learning (EL) is found to have higher accuracy compared with several classical ML models, and the determination coefficient of the adaptive boosting (AdaBoost) model reaches 0.96 after optimizing the features and hyperparameters. In this work, the running framework of the model was clearly displayed by visualization tool, and Shapley Additive exPlanations (SHAP) values were used to visually interpret the model locally and globally to help understand the predictive logic and the contribution of features. Furthermore, the accumulated local effect (ALE) successfully explains how the features affect the corrosion depth and interact with one another.

RETRACTED ARTICLE: Analysis of Influence Factors of Marine Fishery Industry Structure Optimization on Carbon Emission Efficiency Based on Depth Feedforward Model

We, the Editor and Publisher of the Journal of Experimental Nanoscience, have retracted the following article, which is part of the Special Issue titled Adaptive Nanotechnology for Environmental Sustainability: Dayong Chen (2023) analysis of influence factors of marine fishery industry structure optimization on carbon emission efficiency based on depth feedforward model, Journal of Experimental Nanoscience, 18:1, DOI: 10.1080/17458080.2023.2174696 Following publication, concerns were raised about the peer review and decision-making processes for this special issue. After an investigation by the Taylor & Francis Publishing Ethics & Integrity team, in full cooperation with the Editor-in-Chief, it was confirmed that the article was not reviewed appropriately, in line with the Journal’s peer review standards and policy. As the stringency of the peer review process is core to the integrity of the publication process, the Editor and Publisher have decided to retract the article. The authors have been informed of this decision. We have been informed in our decision-making by our editorial policies and the COPE guidelines. The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’.

FORECASTING THE WORK RESOURCE OF THE RAILS IN DIFFERENT CONDITIONS OF OPERATION OF THE RAILWAY TRACK

In different operating conditions of the railway track, the service life of the rails is different. This indicates that there are external factors that have a significant impact on the process of rail wear. In the work, the analysis of influential factors was carried out and their degree of influence was determined in comparison with each other and in the statistical population.&#x0D; To study this problem, the most difficult section of the Slavsko-Lavochne-Beskid-Volovets track on the regional branch of Lviv Railway was chosen. The collection and processing of statistical data was carried out, measurements of the rail track and measurements of rail wear were carried out.&#x0D; The process of lateral wear of the rail depends on various factors, among which it is possible to single out those that are the same for the entire curve, and those that are different for different intersections of the curve. For the entire curve, the tonnage passed, the radius, the set speed, the rise of the outer rail, the longitudinal slope, the type of rails and the binding are the same. These parameters can be called global for the curve, and the wear that depends on them is global. Along the curve, there are local irregularities, that is, deviations in the plan, profile, pattern and inclination of the rail in the middle of the track. These parameters can be called local for the curve, and the wear that depends on them is local. Local wear is additional. The total side wear can be manifested to a greater or lesser extent depending on external conditions: lubrication, sanding of rails, excessive impact of wheels, which is taken into account by the coefficient of external conditions.&#x0D; The results of track measurements show that when a horizontal unevenness appears on a curved section, the bending radius increases, and in such places, there is an increase in lateral wear. When the width of the track in the curves exceeds the established norms, there is also an increase in the amount of wear. Over-inflating causes the wheelset to slide to the inner rail. At the same time, the larger rolling circle is not on the outer wheel, but on the inner one. The vertical force transmitted from the wheel to the rail is also greater along the inner thread. This leads to slipping of the wheel on the outer thread, which increases the lateral wear of the rail. As the measurements showed, when the slope of the rail increases from 1:20 to 1:10, the amount of lateral wear increases. The use of lubricators that lubricate the side surface of the rail head can increase its service life by 3 times. An increase in the surface roughness of the rail by 20 μm leads to a decrease in wear resistance by 20-25%. Based on the received empirical data, a mathematical model of lateral wear of the rail head based on 16 parameters was created.&#x0D; Based on the norms of permissible wear of the rails and the created mathematical model, the service life of the rails is determined in the work depending on the curvature of the track. Forecasting the resource of rails allows to implement resource-saving in railway transport.

Analysis of main influencing factors of energy dissipation and flow diversion effects of rough-strip energy dissipators in curved spillways based on Plackett–Burman design

Abstract Rough-strip energy dissipators (R-SEDs) at the bottom of spillway bends have energy dissipation and flow diversion effects on bend flow. In this paper, twelve Plackett-Burman tests were conducted. Energy dissipation rate and coefficient of variation of superelevation were used as evaluation indices. Influencing factors (i.e., relative height, height ratio, spacing, angle and thickness of R-SEDs as well as centerline radius, width, angle and bottom slope of the bend) of R-SEDs' energy dissipation and flow diversion effects were analyzed using Minitab 21.1 in combination with the entropy weight method and the TOPSIS method. Relative height of R-SED and bend angle were significant factors affecting energy dissipation effects; height ratio of R-SED and centerline radius of the bend were significant factors affecting flow diversion effects; the coefficient of variation of superelevation had a larger weight (0.549) than the energy dissipation rate (0.451), indicating that R-SEDs' flow diversion effects were larger than their energy dissipation effects; height ratio of R-SED, centerline radius of the bend and bend angle were significant factors affecting overall energy dissipation and flow diversion effects and selected as key factors for further steepest climbing tests and response surface design.

Effects of installing concrete deck on noise radiation of steel box girders: Mechanisms, modeling, and analysis of influential factors

Steel–concrete composite box girder (SCC BG) is widely used in engineering because it can make full use of the tensile properties of steel and the compressive properties of concrete. However, research on the vibrational transmission and vibroacoustic response of the SCC BG is still relatively rare. In this study, a laboratory hammering test was performed to obtain the dynamic characteristics of a scaled specimen of an SCC BG before and after installing a concrete deck. The experimental results revealed that the vibroacoustic response was greatly reduced after the installation of concrete deck due to a reduction in the transmission of on-deck vibrations to the steel box girder. Following this, we introduce a model to predict the structural vibroacoustic response of the SCC BG based on the hybrid finite element–boundary element–statistical energy analysis method, and verify its accuracy through experiments. The accurately calibrated model is then used to study the characteristics of vibration transmission between plates of the SCC BG. The influences of the thickness of the concrete deck, concrete material, and degree of shear connection on vibroacoustic responses of the SCC BG are also discussed.

Influencing Factors Analysis and Optimization of Land Use Allocation: Combining MAS with MOPSO Procedure

The rural land use preferences of multiple agents are crucial for optimizing land-use allocation. Taking Guanlin Town, Yixing City, China as an example, this study analyzed the factors by agents effecting rural land use conversion probability, identified the objectives and the constraints within the optimization of rural land-use allocation, and simulated the optimal land-use allocation for 2030 by combining MAS with an MOPSO procedure. The results showed that the preferences and decisions of main actors effected the optimal land-use allocation. The Government determined the conversion between land-use types. The preferences of the entrepreneurs resulted in the distribution of industrial land. Town residents made a high contribution to the configuration of the town residential land by considering some factors. Rural families influenced land-use allocation by considering the quality of cultivated soils, and the optimal spatial location of aquaculture systems. Four optimization objectives were identified. The most relevant constraints were the upper and lower limits of each land-use type. The land-use types in Guanlin town in 2015 had a low intensification and an unreasonable structure. The modeling results indicated a tendency for concentrated spatial distributions of rural land. The results of the present study can provide useful support for decision-making within land planning and consequent management.

Analysis of Birth Rate and Regional Economic Influencing Factors in Western China

Excluding the effect of the epidemic, the factors influencing the birth rate in western China were studied based on a VAR model through the analysis of time series data from 2011-2019. And on this basis, realistic explanations and policy recommendations are given.

Oxidation of ciprofloxacin by the synergistic effect of DBD plasma and persulfate: reactive species and influencing factors analysis

A synergistic system of water falling film dielectric barrier discharge (DBD) plasma and persulfate (PS) was set up and used for oxidizing ciprofloxacin (CIP) in water. Results of reactive species formation in the DBD-only system as well as the DBD–PS system verified the PS activation in the DBD system. Influencing factors on CIP degradation and the degradation process were also been studied. The obtained results showed that the presence of PS could greatly improve the degradation and mineralization of CIP and that the degradation efficiency could reach 97.73% after only 40 min treatment with 4 mM PS addition. The increase of PS concentration, the lower CIP concentration, the acidic solution pH and the addition of metal ions (Fe2+ and Cu2+) enhanced the CIP degradation, while the existence of Cl− and HC had a negative effect. The experiments related to scavenger addition confirmed the contribution of the main reactive species to the CIP oxidation. Three probable degradation pathways were proposed by analyzing the inorganic ions and organic byproducts formed during the CIP degradation. The toxicity evaluation results of the CIP and its intermediates confirmed the effectiveness of the DBD–PS synergistic system.

The Evaluation of Comprehensive Teaching and Research Efficiency and Its Key Influencing Factors Analysis of “Double First-Class” Universities in China

An evaluation index system is established in order to evaluate the comprehensive teaching and research efficiency of “Double First-Class” universities in China, using the Joint Data Envelopment Analysis method. The influence of the parameters in the model is analyzed and the algorithmic steps are given. The key factors of the system are identified by the Grey Correlation Analysis method. The comprehensive teaching and research efficiency of “Double First-Class” Universities in China in 2019 has thereby been calculated as an empirical study. The results show that: (1) It is effective and feasible to construct an evaluation method based on joint DEA, for the evaluation of comprehensive teaching and research efficiency of “Double First-Class” Universities in China. (2) The key factors are the number of cited papers, the annual budget, and the salaries of graduates. Based on those factors, suggestions have been put forward to improve their efficiency. (3) The comprehensive teaching and research efficiency of China’s “Double First-Class” Universities are high, and the comparison between research efficiency and teaching efficiency shows that 69.2% of the “Double First-Class” Universities have higher research efficiency than teaching efficiency. Most of those universities allocate a higher proportion of shared input to research.

Bayesian-Based Approaches to Exploring the Long-Term Alteration in Trace Metals of Surface Water and Its Driving Forces.

Trace metal pollution poses a serious threat to the aquatic ecosystem. Therefore, characterizing the long-term environmental behavior of trace metals and their driving forces is essential for guiding water quality management. Based on a long-term data set from 1990 to 2019, this study systematically conducted the spatiotemporal trend assessment, influential factor analysis, and source apportionment of trace elements in the rivers of the German Elbe River basin. Results show that the mean concentrations of the given elements in the last 30 years were found in the order of Fe (1179.5 ± 1221 μg·L-1) ≫ Mn (209.6 ± 181.7 μg·L-1) ≫ Zn (52.5 ± 166.2 μg·L-1) ≫ Cu (5.3 ± 5.5 μg·L-1) > Ni (4.4 ± 8.3 μg·L-1) > Pb (3.3 ± 4.4 μg·L-1) > As (2.9 ± 2.3 μg·L-1) > Cr (1.8 ± 2.4 μg·L-1) ≫ Cd (0.3 ± 1.1 μg·L-1) > Hg (0.05 ± 0.12 μg·L-1). Wavelet analyses show that river flow regimes and flooding dominated the periodic variations in metal pollution. Bayesian network suggests that the hydrochemical factors (i.e., TOC, TP, TN, pH, and EC) chemically influenced the metal mobility between water and sediments. Furthermore, the source apportionment computed by the Bayesian multivariate receptor model shows that the given element contamination was typically attributed to the geogenic sources (17.5, 95% confidence interval: 13.1-17.6%), urban and industrial sources (22.1, 18.0-27.2%), arable soil erosion (24.2, 16.4-31.5%), and historical anthropogenic activities (35.2, 32.8-43.3%). The results provided herein reveal that both the hydrochemical influence on metal mobility and the chronic disturbance from anthropogenic activities caused the long-term variation in trace metal pollution.

本科护生灵性健康现状调查及影响因素分析

本科护生灵性健康现状调查及影响因素分析

Control of Space Utilization in Urban Coastal Area, Case Study in Sapolohe Village, Bontobahari District, Bulukumba Regency

The establishment of the Bontobahari Sub-district as the center of a coastal tourism area, especially the Bira Coastal area, has an impact on the increasing number of traffic activities and infrastucture development in several areas. One of them is the coastal area in Sapolohe Village. The objective of this research is to identify the forms of discrepancies in space utilization, to determine the factors that cause the discrepancies in space utilization, and to identify the management of control over the space utilization. This research was conducted from August to October 2020 in Sapolohe Village, Bontobahari District, Bulukumba Regency. The data were obtained from literature studies, field observations, questionnaires, interviews, visual materials or documentations, and map overlays. The analysis was carried out through map overlay or spatial analysis, influence factors analysis through statistical analysis in the form of multiple linear regression tests, and descriptive analysis. The results of the study explain that there are various forms of discrepancies in the use of space in the research location, where there are 288 buildings that breach the road boundary line, 564 buildings that breach the coastal boundary line, and 4 buildings that violate the existing IMB (Building Construction Permit) function. The occurrence of discrepancies in space utilization in the research location is influenced by the results of planning that is not properly socialized, the use of space that is not in accordance with the results of the planning, and the lack of control over space utilization by the local government. Meanwhile, the management of controlling the use of space in the coastal area of Sapolohe Village is related to planning, space utilization and control of space utilization.

Thermal performance analysis and multi-objective optimization of thermal energy storage unit with cascaded packed bed in a solar heating system

• Established the CPBTES’s continuous solid phase simplified model and exergy analysis model. • The numerically predicted temperatures match well with the experimental measurements. • Compared the thermal performance of CPBTES and PBTES in the solar heating system. • The regression model of main influencing factors and evaluation indexes was established by the response surface method, • Obtained the optimal parameter combination of multi-objective optimization. The capacity expansion and optimal design of the TES has an important impact on the operational efficiency of the solar heating system. In this study, a CPBTES system with a three-stage PCM was designed for a solar heating system. A one-dimensional, two-phase model based on thermal resistance analysis was established, and the adaptability of the model was verified by different experiments. A multi-objective evaluation system was established, and the response surface methodology was used to carry out the influence factor analysis and multi-objective optimization. The result showed that in the same operating conditions, CPBTES had a more uniform temperature distribution than single-stage TES, which was the key factor to improve the exergy efficiency. CPBTES improved the ideal charging completion time and the exergy efficiency by 7% and 5%, respectively, and reduced the effective TES capacity by 4% compared to single-stage TES. The optimal combination of parameters after multi-objective optimization was aspect ratio of 1.97, dimensionless diameter of 0.03, void ratio of 0.24, and intermediate filling ratio of 0.66. The multi-objective optimization result and method in this study can contribute to new ideas for similar engineering problems.