Influence Of External Factors Research Articles

How Good Corporate Governance, Financial Performance and External Factors Influence Company Value

How Good Corporate Governance, Financial Performance and External Factors Influence Company Value

ST-D3DDARN: Urban traffic flow prediction based on spatio-temporal decoupled 3D DenseNet with attention ResNet.

Urban traffic flow prediction plays a crucial role in intelligent transportation systems (ITS), which can enhance traffic efficiency and ensure public safety. However, predicting urban traffic flow faces numerous challenges, such as intricate temporal dependencies, spatial correlations, and the influence of external factors. Existing research methods cannot fully capture the complex spatio-temporal dependence of traffic flow. Inspired by video analysis in computer vision, we represent traffic flow as traffic frames and propose an end-to-end urban traffic flow prediction model named Spatio-temporal Decoupled 3D DenseNet with Attention ResNet (ST-D3DDARN). Specifically, this model extracts multi-source traffic flow features through closeness, period, trend, and external factor branches. Subsequently, it dynamically establishes global spatio-temporal correlations by integrating spatial self-attention and coordinate attention in a residual network, accurately predicting the inflow and outflow of traffic throughout the city. In order to evaluate the effectiveness of the ST-D3DDARN model, experiments are carried out on two publicly available real-world datasets. The results indicate that ST-D3DDARN outperforms existing models in terms of single-step prediction, multi-step prediction, and efficiency.

Forecasting Corn Futures Prices Using the LSTM Model

The central government's No. 1 document introduced new requirements for “maintaining the stability of agricultural product prices.” However, recent years have seen significant fluctuations in corn prices in China, highlighting the importance of exploring the trends of corn futures prices for stabilizing spot corn prices. Given the increasingly complex financial market environment, traditional linear econometric methods and machine learning approaches face inherent limitations in price forecasting. This study utilizes extensive data and applies the Long-Short Term Memory (LSTM) deep learning model to forecast corn futures prices. During the model training process, historical corn futures data were used as hidden input feature variables, along with additional indicators such as spot corn prices, real-time quotes from corn deep processing enterprises, downstream product prices in the corn industry chain, prices of similar substitutes, and the Baidu Search Index for “corn prices.” The model was trained and fine-tuned with hyperparameters to assess its predictive accuracy under different time windows, learning rates, and iteration counts. Experimental results indicate that incorporating external influencing factors significantly enhances the model's predictive accuracy compared to using only historical price data. The model with a learning rate of 0.01, 50 iterations, a time window of 5, and 4 hidden layers achieved the highest accuracy. The findings demonstrate that integrating external factors and optimizing hyperparameters substantially improve the LSTM model's predictive precision, outperforming models that rely solely on historical data. The study provides policy recommendations on promoting advanced technology, enhancing data collection and information sharing, and improving market transparency and fairness. Additionally, the conclusion discusses the extensive application potential and promising development prospects of the LSTM model in corn futures price forecasting. This model enables market participants to obtain more accurate market trend forecasts, facilitating more informed investment decisions. The research also offers new insights and methodological references for scholars in financial forecasting, contributing to the further advancement of this field.Funding: This study was supported by the 2024 Key Research Project of Higher Education Institutions of the Henan Provincial Department of Education [Project Number 24B790006], the Henan Provincial Department of Education [Project Number 2021GGJS120], and the Henan Provincial Department of Education [Project Number 2021SJGLX478]. Additionally, this study received support from the Xinxiang City Federation of Social Sciences [Project Number SKL-2024-157].

Application of the Data-Driven Method and Hydrochemistry Analysis to Predict Groundwater Level Change Induced by the Mining Activities: A Case Study of Yili Coalfield in Xinjiang, Norwest China

As the medium of geological information, groundwater provides an indirect method to solve the secondary disasters of mining activities. Identifying the groundwater regime of overburden aquifers induced by the mining disturbance is significant in mining safety and geological environment protection. This study proposes the novel data-driven algorithm based on the combination of machine learning methods and hydrochemical analyses to predict anomalous changes in groundwater levels within the mine and its neighboring areas induced after mining activities accurately. The hydrochemistry analysis reveals that the dissolution of carbonate and evaporite and the cation exchange function are the main hydrochemical process for controlling the groundwater environment. The anomalous change in the hydrochemistry characteristic in different aquifers reveals that the hydraulic connection between different aquifers is enhanced by mining activities. The continuous wavelet coherence is used to reveal the nonlinear relationship between the groundwater level change and external influencing factors. Based on the above analysis, the groundwater level, precipitation, mine water inflow, and unit goal area could be considered as the input variables of the hydrological model. Two different data-driven algorithms, the Decision Tree and the Long Short-Term Memory (LSTM) neural network, are introduced to construct the hydrological prediction model. Four error metrics (MAPE, RMSE, NSE and R2) are applied for evaluating the performance of hydrological model. For the NSE value, the predictive accuracy of the hydrological model constructed using LSTM is 8% higher than that of Decision Tree algorithm. Accurately predicting the anomalous change in groundwater level caused by the mining activities could ensure the safety of coal mining and prevent the secondary disaster of mining activities.

Natural Factors of Microplastics Distribution and Migration in Water: A Review

Microplastics are widely present worldwide and are of great concern to scientists and governments due to their toxicity and ability to serve as carriers of other environmental pollutants. The abundance of microplastics in different water bodies varied significantly, mainly attributed to the initial emission concentration of pollutants and the migration ability of pollutants. The migration process of microplastics determines the abundance, fate, and bioavailability of microplastics in water. Previous studies have proved that the physicochemical properties of water bodies and the properties of microplastics themselves are important factors affecting their migration, but the change in external environmental conditions is also one of the main factors controlling the migration of microplastics. In this paper, we focus on the effects of meteorological factors (rainfall, light, and wind) on the distribution and migration of microplastics and conclude that the influence of meteorological factors on microplastics mainly affects the inflow abundance of microplastics, the physical and chemical properties of water, and the dynamics of water. At the same time, we briefly summarized the effects of aquatic organisms, water substrates, and water topography on microplastics. It is believed that aquatic organisms can affect the physical and chemical properties of microplastics through the physical adsorption and in vivo transmission of aquatic plants, through the feeding behavior, swimming, and metabolism of animals, and through the extracellular polymers formed by microorganisms, and can change their original environmental processes in water bodies. A full understanding of the influence and mechanism of external environmental factors on the migration of microplastics is of great theoretical significance for understanding the migration law of microplastics in water and comprehensively assessing the pollution load and safety risk of microplastics in water.

FORMATION OF A COMPETITIVENESS MANAGEMENT MECHANISM TO ENSURE SUSTAINABLE DEVELOPMENT OF ENTERPRISES

The article is devoted to the study of approaches to the formation of a mechanism for managing the competitiveness of enterprises. The main factors ensuring the formation of effective competitiveness in modern conditions, as well as ways and methods of increasing the competitiveness of enterprises are identified. The key aspects of the enterprise's competitiveness are considered, taking into account modern operating conditions and the influence of internal and external factors on the sustainability of its development. The influence of the war on the activities of domestic enterprises is analyzed. It is substantiated that in market conditions the efficiency of enterprises is largely determined by their financial and economic prospects, profitability and competitiveness. It is competitiveness that determines the ability of an enterprise to sell such goods or services, the consumer attractiveness of which is higher than similar ones offered by competitors. Factors with the help of which it is advisable to assess the level of competitiveness of an enterprise in the market have been identified. A number of measures have been proposed to increase the level of competitiveness of an enterprise in conditions of instability. The main problems of increasing the level of competitiveness of an enterprise are identified, related, first of all, to the development of a competitiveness management system, the main element of which is the competitive strategies of the enterprise. Management of an enterprise's competitiveness should be aimed at neutralizing, overcoming and limiting the influence of negative, destructive factors of the influence of the external environment on the level of competitiveness. Forming a defense against them, using positive external influences to build up and implement a system of competitive advantages and enterprise strategies. It is noted that the competitive strategies of an enterprise must be adapted to the peculiarities of the structure of the competitive environment, as well as to the peculiarities of market dynamics

The Minimum Wage Under the Pressure of Some Internal and External Factors of Influence

The Minimum Wage Under the Pressure of Some Internal and External Factors of Influence

Study on current carrying capacity calculation model for dynamic capacity increase of carbon fiber reinforced composite core conductor

Abstract With the “dual-carbon” as the goal of the new power system construction gradually in-depth, transmission lines must have energy-saving capacity for the direction of development. A new type of large-capacity overhead transmission conductor is the carbon fiber reinforced composite core (CFCC) conductor. The conductor has high capacity, low loss, high-temperature resistance, low high-temperature sag, and other characteristics. It is one of the key technologies and equipment applied to the transformation of old overhead transmission lines to enhance its capacity. At the same time, it can also realize the dynamic transmission capacity regulation of the overhead line. The application of the prospect is very promising. The accurate assessment and calculation model for the conductor’s allowable current carrying capacity is the key core technical problem of the overhead transmission line dynamic capacity increase capability. The paper establishes a maximum allowable current capacity calculation model for carbon fiber-reinforced composite core conductors based on Morgan’s formula. The results of the load flow calculation are compared with the actual load flow test results to verify the calculation model, and the maximum error is 3.59%, which proves the reliability of the calculation model. On this basis, the influence of external environmental factors (ambient temperature, sunlight intensity, wind speed, and direction) on the maximum allowable current capacity of the conductor is discussed. The correlation coefficient of the model is analyzed.

Exploration of Risk Factors for Hemorrhoids in the Zhuang Population of Guangxi: A Case-Control Study

Background The prevalence of hemorrhoids in Chinese urban and rural residents is very high. However, the factors affecting the occurrence of hemorrhoids are not very clear, which is disadvantageous to the prevention of hemorrhoids. Objective: To explore the external environment and behavioral influencing factors of hemorrhoidsin the Zhuang population of Guangxi, China, and provide a basis for the prevention of hemorrhoids. Methodology: A case-control study method was used to collect hemorrhoid patients and non-hemorrhoid patients from the same hospital and department as the case group and control group. A self-made questionnaire was used to investigate the education level, family income, alcohol consumption, diet, taste, work position, and other information of the two groups of patients, and logistic regression was used to analyze the correlation between various exposure factors and hemorrhoids. Result: A total of 11 variables were analyzed in this study, and it was found that education level, constipation, chronic gastritis, and dietary taste were associated with hemorrhoids (OR=2.02, 95% CI: 1.16, 3.52; OR=2.70, 95% CI: 1.50, 4.87; OR=1.96, 95% CI: 1.14, 3.36; OR=0.50, 95% CI: 0.28, 0.89). Conclusion Education level, constipation, and chronic gastritis can increase the risk of hemorrhoids, while bland diet can reduce the risk of hemorrhoids.

Complexity of CEO compensation packages

This paper examines complexity in CEO compensation contracts. We develop a measure of compensation complexity and provide empirical evidence that complexity has increased substantially over time. We document that complexity results not only from factors reflecting efficient contracting, but also from external pressures from compensation consultants, institutional investors, proxy advisors, and attempts to benchmark to peers, with these external factors having greater impact in more recent years. Examining consequences of contract complexity, we find an association with lower future firm performance that is related to the influence of external factors on compensation design. We further find this relation is partially mitigated when a contract's performance metrics are more highly correlated, consistent with information processing costs hampering decision-making. Collectively, these findings confirm concerns raised by investors and the media regarding compensation complexity and can inform boards in their design of CEO pay packages.

Buoy‐Based Detection of Low‐Energy Cosmic‐Ray Neutrons to Monitor the Influence of Atmospheric, Geomagnetic, and Heliospheric Effects

AbstractCosmic radiation on Earth responds to heliospheric, geomagnetic, atmospheric, and lithospheric changes. In order to use its signal for soil hydrological monitoring, the signal of thermal and epithermal neutron detectors needs to be corrected for external influencing factors. However, theories about the neutron response to soil water, air pressure, air humidity, and incoming cosmic radiation are still under debate. To challenge these theories, we isolated the neutron response from almost any terrestrial changes by operating a bare and a moderated neutron detector in a buoy on a lake in Germany from July 15 to 02 December 2014. We found that the count rate over water has been better predicted by a theory from Köhli et al. (2021, https://doi.org/10.3389/frwa.2020.544847) compared to the traditional approach from Desilets et al. (2010, https://doi.org/10.1029/2009wr008726). We further found strong linear correlation parameters to air pressure (β = 0.0077 mb−1) and air humidity (α = 0.0054 m3/g) for epithermal neutrons, while thermal neutrons responded with α = 0.0023 m3/g. Both approaches, from Rosolem et al. (2013, https://doi.org/10.1175/jhm‐d‐12‐0120.1) and from Köhli et al. (2021, https://doi.org/10.3389/frwa.2020.544847), were similarly able to remove correlations of epithermal neutrons to air humidity. Correction for incoming radiation proved to be necessary for both thermal and epithermal neutrons, for which we tested different neutron monitor stations and correction methods. Here, the approach from Zreda et al. (2012, https://doi.org/10.5194/hess‐16‐4079‐2012) worked best with the Jungfraujoch monitor in Switzerland, while the approach from McJannet and Desilets (2023, https://doi.org/10.1029/2022wr033889) was able to adequately rescale data from more remote neutron monitors. However, no approach was able to sufficiently remove the signal from a major Forbush decrease event on 13 September, to which thermal and epithermal neutrons showed a comparatively strong response. The buoy detector experiment provided a unique data set for empirical testing of traditional and new theories on Cosmic‐Ray Neutron Sensing. It could serve as a local alternative to reference data from remote neutron monitors.

Literature Review on Experimental Analysis of Domestic Refrigerator

Abstract: This literature review paper delves into the experimental analysis of the performance of domestic refrigerators, a cornerstone of modern household appliances. The review synthesizes a broad spectrum of studies that examine the efficiency, energy consumption, cooling capacity, and overall performance of various domestic refrigerator models. Key focus areas include the impact of different refrigerants, advancements in compressor technology, insulation materials, and the role of smart technologies in enhancing refrigerator performance. The review highlights experimental methodologies employed to assess refrigerator performance, such as standardized testing protocols, real-world usage simulations, and advanced diagnostic techniques. It also discusses the influence of external factors like ambient temperature, door opening frequency, and load variability on refrigerator efficiency. Comparative analyses within the literature reveal trends in energy efficiency improvements, driven by regulatory standards and consumer demand for environmentally friendly appliances. The integration of alternative refrigerants, such as R600a (isobutane), is examined for its environmental benefits and performance implications. The paper concludes by identifying gaps in current research and suggesting directions for future experimental studies. Emphasis is placed on the need for continued innovation in refrigeration technologies to meet growing energy efficiency and environmental sustainability requirements. Overall, this literature review provides a comprehensive overview of the experimental evaluation techniques and findings related to domestic refrigerator performance, offering insights that can guide future research and development in this vital field.

Effects ofAs8structure formation on the surface morphology and internal microstructure of GaAs thin films.

Gallium arsenide (GaAs) materials have the advantages of high electron mobility, electron saturation drift rate, and other irreplaceable semiconducting properties. They play an important role in the electronics, solar and other fields. However, during GaAs film sedimentary growth, As atoms can undergo segregation to formAs8clusters because of the influence of external factors, which affect the surface morphology and internal structure of these films. In this study, a series of investigations on the deposition and growth of GaAs crystal films were performed. Additionally, the deposition and growth of GaAs thin films were simulated using molecular dynamics. The influence of As8clusters on the surface morphology and internal structure of GaAs films at different incidence angles, velocities and substrate temperatures was studied by using 'defect analysis technology' and 'diamond structure identification' in open source software, along with surface roughness and radial distribution function. Results show that with increasing incident angle, the number ofAs8clusters decreases and film density increases. Increasing incident velocity increases the irregular movement ofAs8clusters in air, and their deposition on the film surface affects the morphology of the film, and the surface roughness increases first and then decreases. Additionally, we investigated the effect of different substrate temperatures on the film surface. Results show that at a substrate temperature of 1173 K, the number ofAs8clusters in the film decreases or the As8clusters disappear, heterogeneous nucleation occurs in the film, and the crystallization rate increases. Although the dislocation line associated with nucleation may affect the mechanical and optical properties of the film, it considerably reduces the annealing effort after the deposition and growth.

Hacking Profits in Real Estate: The Influence of Capital Structure, Liquidity, and External Factors

This study seeks to empirically examine the influence of capital structure, liquidity, firm value, firm size, and external factors on profitability within companies operating in the property and real estate sector listed on the Indonesia Stock Exchange, utilizing sample data from 2018 to 2022. Through purposive sampling, 10 companies were selected as research subjects, employing panel data regression analysis. The findings indicate that liquidity and company size have a negative and significant impact on profitability. Conversely, inflation exerts a positive and significant influence on profitability. However, neither capital structure nor firm value significantly affect profitability. These results contribute to understanding the factors influencing the profitability of property and real estate sector companies within the Indonesian capital market context.

A Review on Research of Impulse Purchases Influencing Factors in Generation Z

With the development of society and technological progress, Generation Z has become one of the focuses of business and social attention. In-depth research on the influencing factors of impulse purchase in the Generation Z group. This study mainly focuses on internal and external factors that affect impulsive consumption, including self-concept, education level & income, and delayed gratification; External influencing factors include external environment and marketing strategies. The full text used the literature analysis method to search and read relevant materials and literature. The advantage of this research method lies in its ability to systematically analyze existing literature and research methods, providing a theoretical and empirical basis for research. The research findings of this study indicate that impulse purchase is influenced by both internal and external factors. In terms of internal influencing factors, Generation Z consumers are self-centered, focus on personal image and social status, and are easily influenced by emotions. Consumers with higher income and education levels are more likely to make an impulse purchase, while the trend of delayed gratification makes Generation Z more inclined to immediately satisfy shopping needs. Among the external influencing factors, the Internet era and the prevalence of consumerism are considered important factors. Generation Z grew up on the Internet and is vulnerable to the impact of digital media, while pricing and packaging in marketing strategies will also impact impulse buying.

Photosynthetic productivity of soybean (Glycine max L.) crops under various fertilization options and pre-sowing seed treatment

The objective of the research is to determine the impact of basic fertilization options, foliar feeding with organo-mineral fertilizer during critical periods of soy plant development, pre-sowing seed treatment with mycorrhizal biofertilizer, and mycorrhizal inoculant in combination with a fungicide on the dynamics of dry matter accumulation by the plants and the net productivity of photosynthesis in the soy crop. Methods. Field (for studying the interaction of the research object with biotic and abiotic factors); morphophysiological (for biological monitoring of productivity elements development during organogenesis stages); statistical (statistical analysis of research results). Results. The article presents research findings on the accumulation of dry matter by soy plants and the net productivity of photosynthesis in the crop across different growth and development stages. Equations have been calculated to establish the relationship between soy seed yield and the indicators of dry mass accumulation by the plants during the pod-filling phase. Conclusions. In modern agricultural practices aimed at achieving maximum seed yield, cultivation technology should include agronomic measures directed towards meeting the biological needs of the plant throughout the vegetation period and reducing the influence of adverse external factors. The highest levels of dry matter accumulation by plants in the study — 26.8–29.2 g/plant, were noted during the pod filling phase in variants with the application of N15P45K60+N30 fertilization, sowing seeds treated with mycorrhizal biopreparation and fungicide, and foliar feeding with organo-mineral fertilizers during the budding and flowering phases. The maximum indicators of net photosynthetic productivity of the crop in the study (8.52–11.29 g/m2×day compared to 5.46 g/m2×day in the absolute control) were observed during the interphase period of flowering and pod filling in variants with N45P45K60 fertilization. For the optimal seed yield of soybean variety Muza observed in the study, the optimal conditions were provided by a cultivation technology involving the application of N15P45K60+N30 fertilizers, pre-sowing seed treatment with mycorrhizal inoculant in combination with fungicide, as well as foliar feeding with organo-mineral fertilizers during the branching or budding phases, when the plants are forming flowers, pods, and seeds within the pods. Through the combination of these agronomic measures, plants accumulate dry matter during the pod filling phase at 25.9–27.4 g/plant, ensuring the net photosynthetic productivity of the crop during this developmental period at 5.60–6.10 g/m2×day, compared to 20.8 g/plant and 5.46 g/m2×day observed in the absolute control, respectively.

Molecular and radiocarbon constraints on the fate of sedimentary organic carbon in a human-impacted river-dominated ocean margin

Organic carbon (OC) burial in river-dominated ocean margins plays a pivotal role in the global carbon cycle, impacting atmospheric CO2 levels over the long term. Despite its significance, uncertainties persist regarding the influence of external environmental factors and intrinsic properties on sedimentary OC. In this study, we conducted a comprehensive analysis of surface sediments from the East China Sea, examining geochemical properties (including total OC content [TOC], Δ14C, δ13C, and C/N ratio), terrestrial biomarkers (n-alkanes), and mineral properties (such as specific surface area, Al/Si ratio, and mineral composition). Our aim was to shed light on the fate of sedimentary OC.The surface sediment's Δ14C values displayed significant spatial heterogeneity, delineating four distinct sub-regions. Strong positive correlations (all p < 0.01) were found between the ∆14C values and fine-grained sediments, specific surface area, and clay minerals, suggesting the potentially pivotal role of mineral protection in shaping the fate of sedimentary OC. The proportion of terrestrial OC gradually decreased towards the south, while marine OC proportion increased, corresponding to the enrichment of Δ14C. The co-variation of Δ14C values, mineral properties, and OC source proportions suggests that terrestrial OC may undergo progressive replacement by marine OC during southward transport. Temporal variations in ∆14C values indicated that seabed erosion led to a significant increase in ∆14C values (p < 0.01) in the coastal mud belt, a phenomenon likely common in river-dominated ocean margins globally due to the new sediment cycle during the Anthropocene.

Air Traffic Flow Prediction with Spatiotemporal Knowledge Distillation Network

Air Traffic Flow Prediction with Spatiotemporal Knowledge Distillation Network

ВЫБОР ПАРАМЕТРОВ ТЕХНИЧЕСКОГО СОСТОЯНИЯ ЭЛЕМЕНТОВ ПОГЛОЩАЮЩЕГО АППАРАТА, ОПРЕДЕЛЯЮЩИХ ЕГО БЕЗОТКАЗНОСТЬ

The problems to plan and ensure a given level of reliability of mechanical systems at all stages of their design and operation occupy an important place in the problem of ensuring the quality of machine-building products. With a significant number of scientific methods and approaches to solving theoretical and applied issues of reliability theory, one of the key directions is to determine the reliability indicators of technical systems and their elements, in particular a wide range of products including sliding friction pairs with periodic impacts. The study of failure origins, from the point of view of physical-mechanical processes occurring in surface layers of elements, under the influence of external factors, allows selecting parameters characterizing the functional state of the pair, and, as a result, its reliability. For example, for sliding friction pairs with periodic impacts, such a parameter is the geometric dimensions of the conjugate elements. The decrease in the geometric dimensions of conjugate elements, due to wear, characterizes the rate of change of the initial parameter values to the maximum permissible ones determining the failure, and can be approximated by linear, power, exponential and other dependencies obtained from actual measurements. According to the obtained functional dependencies of parameter changes over operating time, it makes possible to determine the norm for the parameter regulating their pre-failure state, beyond which failure prediction is possible with varying probability, and, as a result, the reliability of the system as a whole. The use of this method to reliability forecasting through the determination of the pre-failure state of the system can be projected onto technical objects, which performance indicators are geometric parameters that ensure the performance, first of all, of the functions of the elements themselves and the entire technical system, and worn out during operation.

Legal basis of defense standardization of the European Union

Legal basis of defense standardization of the European Union