Establish Regression Equations Research Articles

Design and Parameter Optimization of a Combined Rotor and Lining Plate Crushing Organic Fertilizer Spreader

To address the inefficient crushing of fertilizer during the mechanized spreading process caused by the caking of high-humidity organic fertilizer, a fertilizer spreader with a combined rotor and lining plate crushing mechanism was proposed in this paper. With the introduction of the basic structure and working principle of the spreader, a particle group model for an organic fertilizer consisting of both caked and bulk fertilizer was built, based on the Hertz–Mindlin model with bonding and the Hertz–Mindlin model with JKR contact, in EDEM to construct an organic fertilizer-crushing-and-spreading model. With the rotor speed, the axial distance of the hammer, and the number of circumferential hammer groups as the experimental factors and the maximum broken bond rate of the caked organic fertilizer and the minimum coefficient of variation of spreading uniformity as the experimental indices, the Box–Behnken test method was employed to establish regression equations for response surface analysis and multi-objective optimization of the test results. The results indicated that, when the rotor speed was 6.47 Hz, the axial distance of the hammer was 90.30 mm, the number of circumferential hammer groups was five, the broken bond rate reached 90.86%, and the coefficient of variation was 21.45%. Verification tests under these conditions showed a broken bond rate of 90.03% and a coefficient of variation of 22.12%, which were consistent with the optimization results. Therefore, our research provides a reference for the structural design of an organic fertilizer spreader and the optimization of its working parameters.

Combined preparation and application of geopolymer pavement materials from coal slurry-slag powder-fly ash mining solid waste: A case study

The solid waste treatment problem generated in the process of coal mining has always been an important factor restricting safe and environmentally friendly production, and the coal slurry from the coal mine road surface is a new type of mine solid waste, so it is of great significance to treat and efficiently utilize the coal slurry. Currently, a common method of solid waste utilization is to add modifying reagents to prepare functional materials. Select coal slurry, slag powder and fly ash as raw materials, and sodium sulfate and sodium hydroxide were used as alkali exciters to prepare coal slurry based geopolymer pavement material (CSGPM). Response surface methodology was used to establish regression equations between the design optimization objectives (coagulation time, compressive strength) and the variables (mass fraction, mass ratio of slag powder to fly ash, mass ratio of sodium sulfate to sodium hydroxide). The effects of two-by-two interactions of the factors on the optimization objective were explored, and the use of different raw materials was obtained. Under the optimal proportioning parameters, the coagulation time of CSGPM was 33 min and the compressive strength of 24 h of curing was 11.20 MPa. In addition, the generation mechanism of AFt and C-S-H gel substances inside the specimen was explained with the help of microscopic scanning. CSGPM showed good mechanical properties in both load-bearing numerical simulations and acoustic emission tests. Numerical simulation was used to establish the relationship between the design objective of the roadbed (maximum subsidence of the roadbed after bearing) and the design variable (thickness of CSGPM paving). Comparative analyses yielded an optimal subgrade surface layer design thickness of 5 cm, with a maximum subsidence of 0.0033 m after bearing vehicles. Synchronization of roadbed material and concrete damage in combined specimen acoustic emission tests with uniform load transfer. The final coal mine pavement was successfully paved and the total cost of CSGPMD is 63.2 per cent of C30 concrete. Those results are important for the preparation of new pavement functional materials.

Estimation of human height using ulnar length in the Muslim community of Golbazar Municipality, Siraha, Nepal

Calculating an individual's height based on bone measurements is critical in identifying unknown bodies, body parts, or skeletal remains. Anthropologists, anatomists, and forensic experts have used a variety of anthropometric approaches to forecast stature from skeletal remains. Although few studies have been conducted to understand ulnar length and height, it has not been conducted in a few ethnic communities of Nepal. This study aimed to analyze the relationship between human height and ulnar length in Muslim communities of Golbazar Municipality, Siraha, Nepal. Two hundred people (male 100 and female 100) aged 20 to 40 years were purposively selected from Golbazaar, Siraha, Nepal. Ulnar length was measured as the distance between the tip of the Olecranon process and the styloid process with the elbow fully flexed. Height was measured from the top of the head to the floor while the participants stood upright in the anatomical position with their heads in the Frankfort plane. Statistical techniques, such as linear regression analysis and correlation coefficients, were used to determine a correlation between ulna length and height. The population's mean ulna length was 26.53 cm (SD = 2.06), and the mean height was 159.59 cm (SD = 9.72). The correlation between ulna length and height was stronger in males (0.46) than in females (0.36). The study established regression equations for height estimation based on ulna length for different age groups, with the strongest correlations found in the 31–35 years age group and weaker ones in the 20–25 years and 26–30 years age groups. The study suggests that ulna length could be a reliable predictor of height, especially when direct measurement is challenging or impossible. However, additional study is required to explore potential differences based on age, ethnicity, and gender and to validate the findings in more extensive and more diverse populations.

Investigating the Fouling Models of the Microfiltration Mixed Matrix Membranes-Based Oxide Nanoparticles Applied for Oil-in-Water Emulsion Separation

Membrane fouling is a major problem encountered in the use of microfiltration (MF) processes to separate the emulsified oil from water. This work involves assessing the efficacy of removing oil-in-water emulsion (O/W emulsion), and evaluating fouling resistance by studying the membrane morphology before and after fouling, and after washing with different cleaning solutions via field emission scanning electron microscopy (FESEM) analysis. Also, the fundamental mechanism involved in the flux drop during crossflow MF has been assessed using models such as the Hermia blocking models and the modified model by Field. The standard and intermediate pore blocking models provided the best prediction for experimental behavior when analyzing the decay in the flux with time for the bio silicon oxide/polyvinylchloride (B-SiO2/PVC) membrane and the stannic oxide/polyvinylchloride (SnO2/PVC) membrane. This research established regression equations of the flux for both membranes in which these equations are highly correlated with R2 of 98.33% for B-SiO2/PVC and R2 of 99.52% for SnO2/PVC using the surface response methodology (RSM). The high flux recovery ratio (FRR) is indicative of the improved antifouling feature of the manufactured membranes where it was 96.8% for B-SiO2/PVC and 94.6% for SnO2/PVC. The results obtained by Hermia and Field were in good agreement with RSM analysis supporting the standard pore-blocking mechanism.

Design and Optimization of Cross-Corrugated Triangular Ducts with Trapezoidal Baffles Based on Response Surface Methodology and CFD

Plate heat exchangers are widely used in the Heating, Ventilation, and Air Conditioning (HVAC) field. Cross-corrugated triangular ducts are commonly employed in plate heat exchangers. Inserting baffles into the cross-corrugated triangular ducts can improve the heat transfer performance of the plate heat exchangers. This study focuses on intricate interdependencies among the flow channel apex angle, the trapezoidal baffle inclination angle, baffle position, and Reynolds number (Re) on heat transfer and pressure drop using response surface methodology (RSM) and computational fluid dynamic (CFD). To identify the factors that maximize the Nusselt number (Nu) and minimize friction factor (f), the RSM is used to design factors, conduct numerical studies, and establish regression equations. The results show that the apex angle, baffle angle, X-direction position, and Re have significantly affected Nu and f. Compared to a non-baffled channel with the same apex angle and Re conditions, the optimized channel enhances heat transfer by 1.54 times and has an almost identical pressure drop. The inclined baffle significantly enhances comprehensive performance at low Re. The synergistic effect of the heat transfer and pressure drop is most optimal when the apex angle of the flow channel is 90°, the trapezoidal baffle inclination angle is 52.5°, and the Re is 1000, with the baffle position at 0.625H in the X-direction.

Correlation between echocardiographic estimation of right atrial pressure and invasive measurement of central venous pressure in postoperative pediatric patients with congenital heart disease: a prospective observational study

BackgroundRight atrial pressure plays a critical role as a hemodynamic parameter in diagnosing pulmonary hypertension and other cardiac diseases, as well as guiding the treatment and prognosis of various cardiac disorders. If there is no obstruction between the inferior or superior vena cava (SVC) as central veins and the right atrium, the pressures in these veins could be considered equal to the right atrial pressure. This study aimed to examine the correlation between echocardiographic methods for estimating right atrial pressure and invasive measurements of central venous pressure (CVPi) in infants and children with congenital heart disease during the 48 h after cardiac surgery and to establish regression equations for echocardiographic estimation of central venous pressure (CVPe).ResultsWe prospectively enrolled 43 infants and children, ranging in age from 6 months to 16 years, including 20 males and 23 females. We found a significant correlation between CVPi and the ratio of the maximal diameter of IVC to the maximal diameter of the descending aorta ratio (IVCmax/DAOmax) (r = 0.529, P < 0.001), SVCS/D velocity ratio (SVCS/D) (r = 0.462, P = 0.006), right atrial vertical diameter (RAVD) (r = 0.409, P = 0.01), area (r = 0.384, P = 0.014), and tricuspid valve A wave acceleration rate (TVAAR) (r = 0.315, P = 0.048). Multiple regression analysis yielded an equation for estimating central venous pressure using four parameters related to the IVC, SVC, tricuspid valve, and right atrium. The equation is as follows: estimated CVP = 4.36 + (2.35 × IVCmax/DAOmax) + (1.06 × SVCS/D) + (0.059 × RAVD) + (0.001 × TVAAR). This equation is strongly correlated with CVPi (Pearson r = 0.698, P = 0.002).ConclusionsThe estimation of central venous pressure through a multi-parametric equation that included the ratio of the maximal diameter of the inferior vena cava to the maximal diameter of the descending aorta, the ratio of S to D velocity of the superior vena cava, the vertical diameter of the right atrium, and the acceleration rate of the A wave of the tricuspid valve demonstrated a robust correlation with invasively measured central venous pressure. To assess the accuracy of predicted pressures by this equation, further investigations are required to apply this innovative multi-parametric formula to a prospective population of pediatric patients with congenital heart disease.

Standardization of PTH measurement by LC-MS/MS: a promising solution for interassay variability

Parathyroid hormone measurement is critical in managing chronic kidney disease-mineral bone disorders. However, there are several commercially available immunoassays with interassay variability. To address this, Cavalier etal. developed standardization of parathyroid hormone measurement by establishing regression equations of each assay against the liquid chromatography coupled to tandem mass spectrometry method. The recalibration successfully reduced interassay variability, allowing for more consistent interpretation. The proposed approach may pave the way for accurate interpretation of parathyroid hormone in clinical practice.

Linear Cutting Performance Tests and Parameter Optimization of Poplar Branches Based on RSM and NSGA-II

To reduce the cutting force and cutting energy consumption during the operation of tree-climbing pruning machines for poplar trees, a linear cutting test bench device for branches was designed according to the growth characteristics of poplar branches and pruning forestry requirements in this study. Firstly, the cutting mechanical analysis of poplar branches was carried out to explore the significance parameters affecting the cutting force, and then the cutting performance test and parameter optimization of poplar branches was carried out through the response surface method (RSM). The test results indicated that cutting speed, tool edge angle and tool back angle had significant effects on the ultimate shear stress, cutting power consumption per unit area, and the branch damage rate of poplar branches, and the established regression equation demonstrated high goodness of fit. Meanwhile, a second-order regression mathematical model was developed between ultimate shear stress, cutting the power consumption per unit area of the cut and the branch damage rate, and the significance parameter. The non-dominated Sorting Genetic Algorithm II (NSGA-II) was used for multi-objective optimization computation to obtain the optimal combination of cutting parameters as 3.02 m/s for cutting speed, 15° for tool edge angle, and 3° for tool back angle. In this case, the ultimate shear stress, cutting power consumption per unit area, and branch damage rate of poplar branches were small, which were 346.63 kPa, 9.35 mJ/mm2, and 12.36%, respectively. Through the test verification, it can be seen that the relative error between the verification test and the predicted value of model was less than 7%. Moreover, under a cutting tool edge angle of 15°, the ultimate shear stress, cutting power consumption per unit area, and branch damage rate were, respectively, reduced by 17.29%, 14.98%, and 34.21% compared with those under a cutting tool edge angle of 20°, which verifies the validity and reliability of the test results and the research method. This study can provide data support and reference for the research and development of energy-efficient poplar tree-climbing pruning equipment and related branch-cutting performance tests.

Model for Wastage Allowance and Strength Properties of Pipe Piles Exposed to Marine Corrosion

The study’s objective is to analyze the mechanical properties of steel pipe piles as a part of a trestle bridge subjected to five years of natural marine corrosion degradation. Sixteen tensile specimens are extracted from the steel pipe piles in the splash, tidal, and immersion zones. The experimental tensile test results are used to establish regression equations defining the elastic modulus, yield strength, strain hardening index, and strength coefficient for the true stress–strain curves of the three regions. A non-linear time-dependent mathematical model is exploited to identify the corrosion degradation, using the data from one single corrosion degradation measurement campaign. The analysis indicates that the splash zone is experiencing the most severe corrosion degradation, and there are progressive losses in the mechanical properties of each zone as the corrosion degradation progresses. The established relationships of the mechanical properties, as a function of the ratio of corroded plate thickness to the as-built one, can be used as a fast-engineering approach to identify the mechanical properties of severely corroded piles. The corrosion degradation allowance is also defined using the first-order reliability method, accounting for existing uncertainties covered by the partial safety factors. By examining the impact of marine corrosion on the mechanical properties of marine structures and developing predictive models to assess the corrosion’s effect on material strength and corrosion allowance, the study aims to improve offshore structures’ safety, design, and maintenance.

Exploring the Teaching Mode of College Students’ Mental Health Education under Artificial Intelligence Technology Guided by Cognitive Behavioral Theory

Abstract This study pioneers a mental health education model for college students, merging cognitive-behavioral theory with artificial intelligence (AI) technology. By employing mathematical statistics to analyze teaching variables, we establish regression equations that elucidate the relationship between cognitive-behavioral based mental health education and its impact on students’ psychological well-being and psychological capital. Our findings highlight the significant mediating roles of cognitive behavioral instruction on positive emotion regulation (0.161), subjective happiness (0.348), sadness and frustration management (0.412), and anger control (0.376), confirming the efficacy of this approach. The application of cognitive behavioral therapy (CBT) in student psychoeducation has shown promising results in improving cognitive abilities, reducing emotional disturbances, and enhancing cognitive functions, offering valuable insights for advancing mental health education in higher education institutions.

Study on design and impact energy absorption of Voronoi porous structure with tunable Poisson's ratio

As the inner core of crash box, the porous structure could cushion impact load through its own deformation. The aims of this study were to propose a series of Voronoi porous structures with tunable Poisson's ratio (VP-VPS) by using the periodic array of unit cells based on Voronoi-Tessellation and to develop crash boxes filled with porous structures for strong crashworthiness and high energy absorption. VP-VPS structures through the periodic arrays of unit cells were constructed according to 4 independent unit cell design factors. The quasi-static and dynamic compressive mechanical responses of VP-VPS structures prepared by selective laser melting (SLM) were studied through the combinations of mechanical test and simulation. Relationships between VP-VPS unit cell design factors and mechanical properties of structures were determined by establishing regression equations using the response surface method (RSM). Finally, the energy absorption of new crash boxes filled with VP-VPS structures was investigated through simulation. Results showed that VP-VPS structures had high load-bearing capacities and energy absorption under quasi-static and dynamic compressive conditions. Regression equations based on RSM could well predict mechanical properties of structures. The mechanical properties of VP-VPS structures were enhanced with the increase of global strain rate, which showed different deformation modes at low and high global strain rates. Compared with typical crash boxes filled with negative Poisson's ratio (NPR) inner cores, new type VP-VPS crash boxes had stronger impact resistance and higher energy absorption. This investigation provided a feasible design solution and theoretical basis for the construction and engineering application of impact resistance protective structures.

Exposure and effects of synthetic enhanced oil recovery polymers on the Norwegian Continental Shelf

Synthetic polymers are planned to be used for more efficient oil recovery from offshore oil reservoirs. Using synthetic polymers offshore may lead to these being released into the marine environment through produced water (PW) discharges, thereby causing environmental impacts in the ecosystem. In this study, we assess the impacts of discharging synthetic polymers on the Norwegian Continental Shelf (NCS). We use a numerical model called the Dose-related risk and effects assessment model (DREAM) to simulate discharges of polymers into the sea. DREAM assesses impact in terms of environmental impact factor (EIF) values of individual chemicals present in the PW. Two approaches are used: first, using a standard short-time/small-scale/near-field simulation procedure (50 by 50 km); second, using a non-standard long-term/large-scale/far-field simulation procedure (1200 by 1800 km). For the near-field simulations, the impact is assessed by estimating EIF values resulting from the discharge of 200 and 8000 kilodaltons (kDa) molecular weight fractions of Anionic Polyacrylamide (APAM) from a North Sea oil field. The results show higher EIF values for 8000 kDa compared to 200 kDa APAM. Far-field simulations are used because polymers appear to be resistant to microbial degradation and are thus expected to have long residence times in the sea. An increase in concentrations to harmful levels for aquatic species due to repeated discharges from multiple oilfields is thus possible. The results from the far-field simulations are used to establish relationships between the amount of polymer released annually and the resulting highest values of 100- and 75-percentile concentrations. The results indicate that polymers are not expected to build-up on the NCS and there is a significant margin between the expected polymer concentrations and the lowest concentrations at which toxic effects are observed. The established regression equations can be used to indicate maximum expected concentration values for future release scenarios.

Optimisation of free-abrasive assisted lapping process with vitrified bonded diamond plates for sapphire substrates

To improve the processing performance of vitrified bonded diamond fixed-abrasive lapping plates for processing sapphire substrates, a free-abrasive was added to the lapping slurry to enhance the self-dressing ability of the lapping plate to achieve efficient and high-quality processing of sapphire substrates. The processing effectiveness and mechanism of a free-abrasive assisted fixed-abrasive lapping plates (FAAFALP) lapping process for sapphire substrates were analysed and revealed via a single-factor experiment. To optimise the lapping process of the FAAFALP of sapphire substrates with good overall performance (high material removal rate (MRR), minor surface roughness (Ra) and big lapping plate wear ratio (η)), the effects and the optimal parameters combination of the lapping pressure, lapping speed and free-abrasive concentration on MRR, Ra and η of lapping-processed sapphire substrates were investigated using orthogonal experiments. Furthermore, the experimental results were combined with process parameters to establish a regression model. The multi-evaluation index optimisation problem was transformed into a single-index optimisation problem via the grey relational analysis (GRA) to evaluate each parameter's performance comprehensively. The results revealed that an MRR increased by 22.2 % to 2.48 μm/min, the smallest surface roughness Ra of 0.141 μm, and the lapping plate wear ratio η relatively increased to 14.88 was obtained when a free-abrasive of SiO2 with a particle size of 14 μm was added into lapping slurry. Compared with no free-abrasive lapping process, free-abrasive can significantly improve the lapping plate's self-dressing ability and enhance the sapphire substrates' processing effect. The lapping speed, lapping pressure and free-abrasive concentration had different influence degrees on MRR, Ra and η. The established regression equations predicted the response values of MRR, Ra and η to be 99.87 %, 99.06 % and 98.59 %, respectively, and the relative errors between the predicted and actual measured values were <12 %. With increased lapping speed, MRR initially decreased but subsequently increased, and Ra and η gradually decreased. MRR and η continuously increased with increased lapping pressure, whereas Ra decreased. With increased free-abrasive concentration, MRR, Ra and η initially increased but subsequently decreased. Comparing the optimised results obtained by intuitive analysis, the parameters optimised via the GRA were used to obtain sapphire substrates lapping with an MRR of 3.81 μm/min, Ra of 0.133 μm and η of 20.4, and the overall lapping performance was better 42.92 %, 102.90 % and 43.60 % than that of intuitive analysis for MRR, Ra and η. Therefore, combining orthogonal experiments and GRA can provide new ideas for optimising the FAAFALP lapping process for sapphire substrates.

Multivariate nonlinear regression analysis of hydraulic fracturing parameters based on hybrid FEM–DEM

PurposeThis paper aims to employ a multivariate nonlinear regression analysis to establish a predictive model for the final fracture area, while accounting for the impact of individual parameters.Design/methodology/approachThis analysis is based on the numerical simulation data obtained, using the hybrid finite element–discrete element (FE–DE) method. The forecasting model was compared with the numerical results and the accuracy of the model was evaluated by the root mean square (RMS) and the RMS error, the mean absolute error and the mean absolute percentage error.FindingsThe multivariate nonlinear regression model can accurately predict the nonlinear relationships between injection rate, leakoff coefficient, elastic modulus, permeability, Poisson’s ratio, pore pressure and final fracture area. The regression equations obtained from the Newton iteration of the least squares method are strong in terms of the fit to the six sensitive parameters, and the model follow essentially the same trend with the numerical simulation data, with no systematic divergence detected. Least absolutely deviation has a significantly weaker performance than the least squares method. The percentage contribution of sensitive parameters to the final fracture area is available from the simulation results and forecast model. Injection rate, leakoff coefficient, permeability, elastic modulus, pore pressure and Poisson’s ratio contribute 43.4%, −19.4%, 24.8%, −19.2%, −21.3% and 10.1% to the final fracture area, respectively, as they increased gradually. In summary, (1) the fluid injection rate has the greatest influence on the final fracture area. (2)The multivariate nonlinear regression equation was optimally obtained after 59 iterations of the least squares-based Newton method and 27 derivative evaluations, with a decidability coefficient R2 = 0.711 representing the model reliability and the regression equations fit the four parameters of leakoff coefficient, permeability, elastic modulus and pore pressure very satisfactorily. The models follow essentially the identical trend with the numerical simulation data and there is no systematic divergence. The least absolute deviation has a significantly weaker fit than the least squares method. (3)The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.Originality/valueThe nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

Estimation of Secondary Metabolites in Gliricidia Sepium from Primary Compounds and Regrowth Age

The objective is to estimate the content of secondary metabolites in Gliricidia Sepium from the age and content of primary compounds (nitrogen, fructose, glucose, and sucrose). The present study was developed following a randomized block design, with three treatments (60, 120 and 180 days) and n repetitions. Nitrogen (N), glucose (Glu), fructose (Frut) and sucrose (Suc) content were evaluated for validation. In addition, mathematical models were validated for the estimation of secondary metabolites from the primary ones and regrowth age. To establish the functional relationship between age and primary metabolites, regression equations were analyzed. Reporting a decrease for N, Glu, Frut and Suc with the highest values at 60 days, and quadratic equations with R2 greater than 0.91 were adjusted. The regrowth age had a marked effect on the contents of primary metabolites (N, Glu, Frut and Suc), which explains the close relationship through the established regression equations. As well as it was evidenced that the validation of the models for the prediction of secondary metabolites in both periods of the year, can be applied due to the dependence of these compounds on their precursors (nitrogen and sugars).

Establishment of regression equation between the herbaceous cover and herbage carbon of different plant functional types in a dry tropical grassland of BHU, Varanasi

Grasslands are one of the largest carbon sinks and are crucial in the carbon cycle. However, modelling each species' carbon versus cover relationship is complex, and modelling ground flora covers of plant functional types simplify model development and provide a helpful link between physiologic strategies and ecosystem processes. The present experiment randomly selected 115 quadrats of 1×1 meters from the Banaras Hindu University campus. The cover of each herbaceous species was recorded by visual charting method and measured by gridding each 1×1 meter quadrat into 100 cells; each represented 1% cover. Species-wise, herbage carbon content was calculated. Species-wise, herbage carbon, and cover were further categorized into different functional types. Prostate, perennials, grasses, and native plants accumulate more carbon and could solve global warming problems. The established regression equation between plant cover and carbon content could be used at a worldwide scale for non-destructive estimation of carbon at functional group levels. Furthermore, non-destructive methods are superior to destructive methods in maintaining the diversity of tropical grassland because biomass harvesting can destroy the habitat spaces of rare and endangered species.

Characterizing of Sandy Loam Soil Electrical Conductivity and Cone Index Relationship at Varying Depths in Punjab Region

Soil constitutes a fundamental resource for the production of food and fiber, thereby meeting diverse human needs and sustaining global ecosystems. Soil compaction and electrical conductivity are key soil properties that can significantly impact soil health and contribute to environmental challenges. The findings of the study shed light on the severity of soil compaction, with the highest cone index 4495 kPa value recorded at a depth of 225 mm in sandy loam soil. This highlights the potential limitations on root growth and nutrient uptake, which can have implications for plant productivity and the overall ecosystem. Furthermore, the study examined the electrical conductivity of the soil, which serves as an indicator of soil salinity. Elevated electrical conductivity levels can lead to adverse effects such as reduced crop yields and environmental stress. Bulk density was increased (1.4 to 1.73 Mg/m3) as well as the moisture content of the soil was decreased (7.6 to 4.3 %). Understanding the range of electrical conductivity values observed in the study (11 to 29 mS/m) helps to assess the extent of salinity-related challenges in the studied region. By establishing regression equations between cone index and soil properties like bulk density and moisture content, the study provides valuable insights into the underlying relationships that contribute to soil compaction and its environmental implications. The coefficient of determination (R2) between the bulk density with moisture content and cone index was 0.99 and 0.95, respectively. These findings can assist in the development of strategies to mitigate soil degradation, promote sustainable land management practices, and address environmental concerns related to soil health.

The geographical pension gap: Understanding the causes of inequality in China's pension funds.

The sustainability of social pension insurance is of great significance in guaranteeing the essential life of the elderly and promoting social stability. Based on the provincial panel data from 2012 to 2020, this study uses non-spatial measurement methods, ArcGIS visualization research methods, and geographic detectors to study the regional differences in China's pension fund balances and the underlying influencing factors. Compared with the traditional way of establishing regression equations to explore the correlation of influencing factors, geographic detectors can quantify the strength of each influencing factor and detect the interaction of different influencing factors. This study found that: First, the growth rate of China's overall pension fund balances has been declining yearly, with the fastest decline in northeast China, the middle in the Western and Central regions of China, and the slowest decline in Eastern China. Second, the spatial distribution of pension fund balances shows agglomeration characteristics, with high-value areas mainly distributed in Eastern China and low-value regions distributed primarily in Western and Northeastern China. Third, the overall Theil index for pension fund balances is trending down, but the Theil index for the Eastern region is on the rise. Fourth, seven factors, including the working-age population, the population aged 65 and above, and regional GDP, are the main factors that lead to regional differences in the balance of urban and rural residential insurance funds. Finally, the superimposed effects of each element are reflected in double-factor enhancement or non-linear enhancement relation.

Study of petrophysical parameters of productive series by use of well data

The progress of existing geophysical techniques for the last years led to a wider scope of the problems resolved using this set of tools. The tools allow tackling pivotal tasks such as the study of lithology in a geological section, correlation, evaluation of saturation, porosity, permeability, and clay fraction, and outlining of oil-gas and water-saturated layers. Complications emerging while resolving these problems directly depend on the petrophysical parameters of reservoir layers. For instance, similar values of resistivity in oil and water layers result in high value of clay fraction and variation of porosity in a wide range and this complicates distinguishing the oil and water layers. On the other hand, it is known that an increase of cementing clay amount in reservoirs causes drop of porosity (Kpor.) and increase of residual water saturation.&#x0D; This paper is devoted to design of models defining correlation between petrophysical parameters of reservoir layers by use of integrated well data and establishing regression equations from these parameters’ distributions. Models of variation of porosity, permeability, clay fraction and oil and gas saturation through the sections of wells were also designed. They made it possible to evaluate filtration-capacity characteristics and establish correlation between petrophysical parameters of reservoir layers and gain information about this field.&#x0D; The bar graph was drawn for permeability coefficient variation through studied reservoirs in Qirmaky suite (QD-1, QD-2, QD-3, QD-4) by use of sections of wells conditionally marked as 1, 2, 3, and 4 in the Balakhany field.&#x0D; Analysis of the constructed histograms allows us to classify the studied collector layers according to their permeability. Of the 17 layers studied in section of well 1, only Layer 17 has very good permeability, the other 16 are of good permeability; all 17 layers of well 2 have good permeability characteristics; of the 17 layers of well 3, Layer 3 is of poor permeability, layers 6, 7, and 14 have average permeability, and the rest are of good permeability; all 12 layers of well 4 have good permeability.&#x0D; The study target is Qirmaky suite (QD-1, QD-2, QD-3, QD-4) of the Productive Series in Balakhany field.

A more accurate approach to estimate the C-factor of RUSLE by coupling stratified vegetation cover index in southern China

Timely and accurate monitoring and forecasting of the cover and management factor (C-factor) is critical for soil erosion assessment at the national or regional scale. The stratified vegetation cover index (Cs) considers both the horizontal and vertical structure of vegetation. It is an ideal indicator for estimating the C-factor, but its applicability is limited in southern China where evergreen species dominate. To address this issue, this study proposed to reconstruct the structured vegetation index (S-Cs) in Nanjing, China, and sift out the optimal vegetation index for assessing the C-factor by establishing regression equations between the measured C-factor and S-Cs, fractional vegetation cover (FVC), Cs, and green coverage (VG). The results indicated that S-Cs can fully reflect the soil and water conservation benefits of different vegetation types and structures in southern China. Also, mixed coniferous and broadleaf forests had stronger soil and water conservation benefits than monocultures, and shrub-grass mixtures reduced soil erosion more than tree-grass mixtures. Besides, S-Cs was proved to be the best index to estimate the C-factor compared with Cs, FVC, and VG. Additionally, the C-factor fitting equation based on S-Cs was established as C = 0.213exp(−5.995 × S-Cs), which had good performance (R2 = 0.743, NSE = 0.507). This study broadened the application area of structured vegetation index and provided a new perspective for national or regional soil erosion assessment by coupling the S-Cs and the C-factor.