Quantitative analysis of geological ore-controlling factors and stereoscopic quantitative prediction of concealed ore bodies

To address the issues for assessing and prospecting the replaceable resource of crisis mines, a geological ore-controlling field model and a mineralization distribution field model were proposed from the viewpoint of field analysis. By dint of solving the field models through transferring the continuous models into the discrete ones, the relationship between the geological ore-controlling effect field and the mineralization distribution field was analyzed, and the quantitative and located parameters were extracted for describing the geological factors controlling mineralization enrichment. The method was applied to the 3-dimensional localization and quantitative prediction for concealed ore bodies in the depths and margins of the Daehang mine in Guangxi, China, and the 3-dimensional distribution models of mineralization indexes and ore-controlling factors such as magmatic rocks, strata, faults, lithology and folds were built. With the methods of statistical analysis and the non-linear programming, the quantitative index set of the geological ore-controlling factors was obtained. In addition, the stereoscopic located and quantitative prediction models were set up by exploring the relationship between the mineralization indexes and the geological ore-controlling factors. So far, some concealed ore bodies with the resource volume of a medium-sized mineral deposit are found in the deep parts of the Dachang Mine by means of the deep prospecting drills following the prediction results, from which the effectiveness of the predication models and results is proved.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Risk factors for hepatocellular carcinoma in cirrhosis:A comprehensive analysis from a decade-long study

BACKGROUND Cirrhosis is a significant risk factor for the development of hepatocellular carcinoma(HCC).Variability in HCC risk among patients with cirrhosis is notable,particularly when considering the diverse etiologies of cirrhosis.AIM To identify specific risk factors contributing to HCC development in patients with cirrhosis.METHODS This retrospective study analyzed data from cirrhotic patients at Beijing Youan Hospital from January 1,2012 to September 30,2022 with at least 6 mo of followup.Patient demographics,medical histories,etiologies,and clinical characteristics were examined.Cox regression analysis was used to analyze correlations of the above parameters with hepatocarcinogenesis,while competing risk regression was used to estimate their adjusted hazard ratios accounting for death.The cumulative incidence was plotted over time.RESULTS Overall,5417 patients with cirrhosis(median age:54 years;65.8%males)were analyzed.Hepatitis B virus(HBV)was the most common etiology(23.3%),with 25%(n=1352)developing HCC over a 2.9-year follow-up period.Patients with multiple etiologies had the HCC highest incidence(30.3%),followed by those with HBV-related cirrhosis(29.5%).Significant risk factors included male sex,advanced age,hepatitis C virus(HCV)infection,elevated blood ammonia,and low platelet count.Men had a higher 5-year HCC risk than women(37.0%vs 31.5%).HBV,HCV,and HBV/HCV co-infected patients had 5-year risks of HCC of 45.8%,42.9%,and 48.1%,respectively,compared to 29.5%in nonviral hepatitis cases,highlighting the significant HCC risk from viral hepatitis,especially HBV,and underscores the importance of monitoring these high-risk groups.CONCLUSION In conclusion,HBV-related cirrhosis strongly correlates with HCC,with male sex,older age,viral hepatitis,elevated blood ammonia,and lower albumin and platelet levels increasing the risk of HCC.

Analysis of anxiety and depression status and their influencing factors in patients with diabetic retinopathy

BACKGROUND Diabetic retinopathy(DR)is a common complication of diabetes and the leading cause of visual impairment and blindness.It has a serious impact on the mental and physical health of patients.AIM To evaluate the anxiety and depression status of patients with DR,we examined their influencing factors.METHODS Two hundred patients with DR admitted to the outpatient and inpatient departments of ophthalmology and endocrinology at our hospital were selected.A questionnaire was conducted to collect general patient information.Depression and anxiety were assessed using the Patient Health Questionnaire-9 and Sevenitem Generalized Anxiety Disorder scale,respectively.The diabetes specific quality of life scale and Social Support Rating Scale were used to assess the quality of life of patients with DR and their social support,respectively.Logistic regression analysis was used to assess the correlations.RESULTS The prevalence of depression and anxiety were 26%(52/200)and 14%(28/200),respectively.Regression analysis revealed that social support was associated with depression[odds ratio(OR)=0.912,95%confidence interval(CI):0.893-0.985]and anxiety(OR=0.863,95%CI:0.672-0.994).Good quality of life(diabetes specific quality of life scale score<40)was a protective factor against anxiety(OR=0.738,95%CI:0.567-0.936)and depression(OR=0.573,95%CI:0.4566-0.784).Visual impairment significantly increased the likelihood of depression(OR=1.198,95%CI:1.143-1.324)and anxiety(OR=1.746,95%CI:1.282-2.359).Additionally,prolonged diabetes duration and history of hypertension were significant risk factors for both conditions,along with a family history of diabetes.CONCLUSION Key factors influencing anxiety and depression in patients with DR include social support,quality of life,visual impairment,duration of diabetes,family history of diabetes,and history of hypertension.

Logistic Regression Analysis of Catheter Fixation Defects and Their Influencing Factors

[Objectives] To analyze the influencing factors of fixed defects in patients with catheter fixation in clinical nursing work, in order to provide the best catheter fixation nursing plan for patients.[Methods] 176 inpatients with indwelling catheter from surgical system of Taihe Hospital in Shiyan City from August 2022 to March 2023 were selected. Using a retrospective analysis method, the influencing factors of catheter fixation defects in the study subjects were divided into two categories based on objective characteristics: type I non modifiable influencing factors and type II modifiable influencing factors. Using the standard for catheter fixation defects, whether the patient had catheter fixation defects was determined. After classified and statistically analyzed item by item, binary Logistic multiple regression analysis was used to identify the influencing factors.[Results] The occurrence of catheter fixation defects in patients with catheter fixation was related to factors such as whether the patient was evaluated before fixation, whether the fixation method was standardized and systematic, whether there was sufficient communication between nurses and patients, and the patient s knowledge of catheter fixation. It was also influenced by factors such as the patient s age, catheterization site, catheterization number, catheterization duration, where there was a consciousness disorder, educational level, and external environmental temperature.[Conclusions] Early attention to the key factors affecting patients with catheter fixation defects can effectively prevent adverse factors and provide patients with the best catheter fixation nursing plan to improve nursing quality.

Comparative Analysis of the Factors Influencing Metro Passenger Arrival Volumes in Wuhan, China, and Lagos, Nigeria: An Application of Association Rule Mining and Neural Network Models

This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.

Analysis of the Factors That Cause Environmental Degradation of Lake Santa Maria Tasi Tolu Dili Timor-Leste

This research aims to understand more closely the damage to the lake environment and the factors that cause pollution in Lake Santa Maria are the first factor of increasing urbanization, the use of the land around the lake as a place to live, the absence of maximum control from the local government this case, the Dili municipal authority. Types of solid waste consist of iron from car accidents, motorcycles, used building materials, plastic, used drink bottles and clothes, mosquito nets, food scraps from household waste, as well as old fishing nets from residents. In addition, household waste such as bath and bath, dishwashing, detergents, and waste from tempeh and tofu factories, including burnt oil from cars and motorcycles, are thrown into the lake. Municipal waste management is based on environmental standards to determine the quality of waste management in Dili Municipality. It is possible to identify the composition of waste and waste, as well as predict its environmental impact. Human (Anthropic) factors Domestic Liquid Waste, Domestic Solid Waste: Composed of organic and inorganic waste. Synthetic Waste, Disposal of Used Oil, Disposal of Domestic Animal Waste, Shallow Drains and Septic Tanks, Mountain Garbage, Garbage Thrown by Visitors, Natural Factors, Climate change, Prolonged drought, Low rainfall, El Niño and La Niña factors, Wind speed, Heat (high daily temperature pressure), Greater water evaporation, Dry wind. The occurrence of contamination necessarily implies an ecological imbalance. The impact introduced by residual compounds and waste that may be associated with the toxicity.

Latent profile analysis of perceived stress and influencing factors in colorectal cancer patients

Objective:To understand the latent categories of perceived stress in colorectal cancer patients and analyze the characteristics of different categories of patients.Methods:A total of 255 colorectal cancer patients receiving treatment in the gastrointestinal surgery and oncology depar tments of a ter tiary Grade A hospital in Sichuan Province,from January 2023 to June 2023,were selected as the study subjects.General information questionnaire,Chinese version of the Perceived Stress Scale(CPSS),and Comprehensive Score Table for Patient-Repor ted Outcome Measures of Economic Toxicity(COST-PROM)were used for data collection.Results:Perceived stress in colorectal cancer patients was classified into 3 latent categories:C1“Low stress-stable type”(19.2%),C2“Moderate stress-uncontrolled type”(23.9%),and C3“High stress-anxious type”(56.9%).The average score of perceived stress was(34.07±5.08).Compared with C1 type,patients with a monthly household income of≤3000 RMB were more likely to belong to the C2 and C3 types(P<0.05),and patients without a stoma were less likely to belong to C3 type(P<0.05).Compared with C2 type,male patients were more likely to belong to C3 type(P<0.05),and patients without a stoma were less likely to belong to C3 type(P<0.05).Compared with C3 type,patients with higher economic toxicity scores were more likely to be classified into C1 and C2 types(P<0.05).Conclusions:Perceived stress in colorectal cancer patients exhibits distinct categorical features.Male gender,lower income,presence of a stoma,and higher economic toxicity are associated with higher levels of perceived stress in colorectal cancer patients.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Correlation Analysis between Fruit Cracking and Influencing Factors in Apricot

In this study, 14 representative apricot cultivars in the production were selected as the experimental materials, and their fruit cracking characteristics, as well as the correlations between fruit cracking and influencing factors （e.g., pedcarp structure, mineral elements contents, DW/FW ratio and soluble sugar content） were analyzed to provide some reference for systematic study on fruit cracking mecha- nism of apricot. The results showed the cultivars with small orderly-and compactlyarranged epidermal cells were difficult to crack, while the cultivars with big disorderly-and loosely-arranged epidermal cells were easy to crack. There was no significant correlation between pericarp thickness and cracking index. The correlations between cracking and mineral elements contents of apricot fruit were in the order as Ca 〉 Zn 〉 Mn 〉 Fe 〉 K 〉 Mg 〉 Cu. The cracking index of apricot fruit was significantly negatively correlated with Ca content, was weakly correlated with Zn and Mn contents, and was uncorrelated with Fe, K, Mg and Cu contents. Ca deficiency was the main factor affecting the fruit cracking in apricot. Under the same conditions, the higher the water content is, the lower the cracking index is; and the higher the soluble sugar content is, the higher the cracking index is.

Grey Relational Analysis between Chlorophyll a and Environmental Factors in ShaHu Lake

[Objective] The aim was to explore effects of environmental factors on the content of Chlorophyll a in ShaHu Lake.[Method] Based on the data in Shahu Lake from November in 2007 to September in 2008,the relationship between chlorophyll a and environmental factors like water temperature,pH,secchi-depth （SD）,total nitrogen,total phosphorus and potassium permanganate index was studied by grey relational analysis method.[Result] The main environmental factors affecting the content of Chlorophyll a in ShaHu Lake were in order of water temperature potassium permanganate index 〉total nitrogen 〉pH〉 total phosphorus 〉SD.[Conclusion] The research provides reference for the control of eutrophication and the reasonable development and utilization of Shahu Lake.

Response of Ecosystem Service Value Based on Land Use Changes and Analysis of its Driving Factors in Typical Hilly Region with Red Soil

The contribution rate of ecosystem service value variation was used to analyze the effects of land use changes on the changes of ecosystem service value in Xingguo County during 1996-2005.Grey integrated correlation was employed to explore the contribution level of the indicators such as total population,urbanization level,proportion of primary industry and investment of social fixed assets on ecosystem service value,and the correlation analysis was also carried out.The results showed that the ecosystem service value in Xingguo County during 1996-2005 mainly was woodland,and the decrease of woodland area was the major reason for the sustained reduction of ecosystem service value.With the further increase of market demand and the incentives of local government,the garden area rapidly increased during 2001-2005,and the influence degree of garden towards the changes of ecosystem service value was only second to woodland,ranking No.2.Four socio-economic indicators had different correlation degree with ecosystem service value during the different research periods.Total population,urbanization level and proportion of primary industry had high correlation degree with ecosystem service value,whereas the influence degree of various socio-economic indicators on ecosystem service value was equal with each other day by day.Urbanization level,investment of social fixed assets and total population had significant negative correlation with ecosystem service value,while the proportion of primary industry had positive correlation with ecosystem service value.

Analysis on Fuji Apple Tree Structures and Related Factors under Different Pruning Modes

To determine the correlations between the tree structuresof Fuji apple with different pruning modes and each factor, the data about 3 tree structures which were free spindle short shoot, free spindle long shoot and slenderspindle short shoot in Xingtang County of Hebai Province were investigated, then by SPSS anal- ysis, the correlations between the taperingness and each growth factor of inserted small branch were compared. The results showed that the taperingness of central trunk of free spindle dwarf-shoot Fuji apple treeshad negative correlations with each factor of inserted small branch, while the taperingness of central trunk of free spin- dle long-shoot Fuji apple treeshad positive correlations with each factor of inserted small branch, the taperingness of central trunk of slenderspindle short-shootFuji ap- ple treeshad negative correlation with total thickness of inserted small branch, but had positive correlations with other factors. This study can provide a scientifictheo- retical basis for the pruning technology of high-density planting trees grafting by dwarfing self-rooted rootstock.

Path Analysis on the Meteorological Factors Impacting Soil Respiration Rate of Wheat Field

[Objective]The experiment aimed to study the effects of meteorological factors under different weather conditions on soil respiration. [ Method] The path analysis was used to analyze meteorological factors which influenced soil respiration of wheat field under different weather condition and at jointing stage. [ Result] In sunny day, the correlations between ground temperature at 5 cm, solar radiation, air relative humidity, air temperature and soil respiration were all at significant level while solar radiation and ground temperature at 5 cm were the major factors which influenced soil respiration. In cloudy day, solar radiation was a major factor which influenced soil respiration.[ Conclusion] The soil respiration and surplus path coefficient in sunny day were all higher than these in cloudy day, which demonstrated that except influenced by ground temperature, air temperature, solar radiation and air relative humidity, the soil respiration was also influenced by other factors especially biological factor.

Identifying the best common factor model via exploratory eactor analysis

Currently,there is no solid criterion for judging the quality of the estimators in factor analysis.This paper presents a new evaluation method for exploratory factor analysis that pinpoints an appropriate number of factors along with the best method for factor extraction.The proposed technique consists of two steps:testing the normality of the residuals from the fitted model via the Shapiro-Wilk test and using an empirical quantified index to judge the quality of the factor model.Examples are presented to demonstrate how the method is implemented and to verify its effectiveness.

A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data

High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable requirements.However, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational efficiency.Hence, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.

Impact of climate factors on runoff in the Kaidu River watershed:path analysis of 50-year data

Runoff formation is a complex meteorological-hydrological process impacted by many factors,especially in the inland river basin.Based on the data of daily mean air temperature,precipitation and runoff during the period of 1958-2007 in the Kaidu River watershed,this paper analyzed the changes in air temperature,precipitation and runoff and revealed the direct and indirect impacts of daily air temperature and precipitation on daily runoff by path analysis.The results showed that mean temperature time series of the annual,summer and autumn had a significant fluctuant increase during the last 50 years（P 0.05）.Only winter precipitation increased significantly（P 0.05） with a rate of 1.337 mm/10a.The annual and winter runoff depthes in the last 50 years significantly increased with the rates of 7.11 mm/10a and 1.85 mm/10a,respectively.The driving function of both daily temperature and precipitation on daily runoff in annual and seasonal levels is significant in the Kaidu River watershed by correlation analysis.The result of path analysis showed that the positive effect of daily air temperature on daily runoff depth is much higher than that of daily precipitation in annual,spring,autumn and winter,however,the trend is opposite in summer.

Geological Characteristics and Ore-controlling Factors of the Beiya Gold–Polymetallic Ore Deposit, Northwestern Yunnan Province

Based on comprehensive petrological, geochronological, and geochemical studies, this study analyzed the relationships between the Beiya gold-polymetallic skarn deposit and quartz syenite porphyries, and discussed the source（s） and evolution of magmas. Our results suggest that syenite porphyries（i.e. the Wandongshan, the Dashadi, and the Hongnitang porphyries）, which formed between the Eocene and the early Oligocene epochs, are the sources for the gold-polymetallic ores at the Beiya deposit. Carbonate rocks（T2 b） of the Triassic Beiya Formation in the ore district provide favorable host space for deposit formation. Fold and fault structures collectively play an important role in ore formation. The contact zone between the porphyries and carbonates, the structurally fractured zone of carbonate and clastic rocks, and the zone with well-developed fractures are the ideal locations for ore bodies. Four types of mineralization have been recognized： 1） porphyry-style stockwork gold–iron（copper） ore, 2） skarn-style gold-iron（copper and lead） ore in the near contact zone, 3） strata-bound, lense-type lead–silver–gold ore in the outer contact zone, and 4） distal vein-type gold–lead–silver ore. Supergene processes led to the formation of oxide ore, such as the weathered and accumulated gold–iron ore, the strata-bound fracture oxide ore, and the structure-controlled vein-type ore. Most of these ore deposits are distributed along the axis of the depressed basin, with the hypogene ore controlling the shape and characteristics of the oxide ore. This study provides critical geology understanding for mineral prospecting scenarios.

Mining Weights of Land Evaluation Factors Based on Cloud Model and Correlation Analysis

The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.

Analysis of risk factors for central venous port failure in cancer patients

AIM: To analyze the risk factors for central port failure in cancer patients administered chemotherapy, using univariate and multivariate analyses. METHODS: A total of 1348 totally implantable venous access devices (TIVADs) were implanted into 1280 cancer patients in this cohort study. A Cox proportional hazard model was applied to analyze risk factors for failure of TIVADs. Log-rank test was used to compare actuarial survival rates. Infection, thrombosis, and surgical complication rates (χ2 test or Fisher's exact test) were compared in relation to the risk factors. RESULTS: Increasing age, male gender and openended catheter use were signifi cant risk factors reducing survival of TIVADs as determined by univariate and multivariate analyses. Hematogenous malignancy decreased the survival time of TIVADs; this reduction was not statistically signifi cant by univariate analysis [hazard ratio (HR) = 1.336, 95% CI: 0.966-1.849, P = 0.080)]. However, it became a signifi cant risk factor by multivariate analysis (HR = 1.499, 95% CI: 1.079-2.083, P = 0.016) when correlated with variables of age, sex and catheter type. Close-ended (Groshong) catheters had a lower thrombosis rate than open-ended catheters (2.5% vs 5%, P = 0.015). Hematogenous malignancy had higher infection rates than solid malignancy (10.5% vs 2.5%, P < 0.001). CONCLUSION: Increasing age, male gender, openended catheters and hematogenous malignancy were risk factors for TIVAD failure. Close-ended catheters had lower thrombosis rates and hematogenous malignancy had higher infection rates.