Sampling Points Research Articles

Neural Network-Based Modeling of Diffusion-Induced Stress in a Hollow Cylindrical Nano-Electrode of Lithium-Ion Battery

Abstract Understanding the interaction between mechanical deformation and mass transport, such as diffusion-induced stress, is crucial in the development of advanced battery materials and electrochemical devices. Mathematical modeling and solving the coupling problems have played important roles in advancing the understanding of the interaction between mechanical deformation and mass transport. As the complexity of mathematical modeling continues to increase, numerical methods used to solve the related coupling problems are likely to encounter significant challenges. This work explores the feasibility of designing a neural network specifically for solving diffusion-induced stress in the electrode of lithium-ion battery via deep learning techniques. A loss function is constructed from the spatiotemporal coordinates of sampling points within the solution domain, the overall structure of the system of partial differential equations, boundary conditions, and initial conditions. The distributions of stress and lithium concentration in a hollow-cylindrical nanoelectrode are obtained. The high degree of conformity between the numerical results and those from finite element method is demonstrated.

Optimal sand transport roadbed geometry structure of Taklamakan Desert highway

In order to obtain the optimal geometric structure for sand transport in desert roads, this study fully utilizes the natural sand transport capacity of the desert roads, aiming to reduce occurrences of road damage due to sand burial. The research integrates Computational Fluid Dynamics (CFD) with optimization analysis theory. Various typical geometric structures of desert highway roadbed were modeled using the Design Exploration module in CFD. Optimization analysis methods were employed to model and compute the sediment transport optimization design on both the roadbed and road surface. Then, the initial sample points are obtained by using the Design of Experiments (DOE), and the response surface is established by using the Kriging model to obtain the change trend of the input parameters and the objective function. Finally, the cross-section parameters of the sediment transport subgrade corresponding to different inflow conditions are obtained. The results show that the sediment transport performance of embankment, cutting and semi-filled uphill subgrade is negatively correlated with the height of subgrade. The relationship between slope gradient and sediment transport performance of subgrade depends on the height of subgrade and the type of subgrade section. For embankment and cutting, when the subgrade height is less than 0.5 m, the sediment transport performance of the subgrade is positively correlated with the subgrade slope; however, when the subgrade height exceeds 0.5 m, the sediment transport performance is negatively correlated with the subgrade slope. For the semi-filled uphill flow subgrade, the sediment transport performance of the subgrade is negatively correlated with the subgrade slope. Comprehensive analysis shows that semi-filled and excavated downhill subgrade has the best sand transport performance, embankment subgrade has the second highest sand transport capacity, then cutting subgrades, while semi-filled and excavated uphill subgrade has the worst sand transport performance. The research conclusions provide valuable scientific guidance for the design of sand control embankment structures tailored to local conditions for desert highways. This is of significant importance for enhancing the sediment transport capacity of desert highways and prolonging their service life.

PHREEQ C Modelling Tool Application to Determine the Effect of Anions on Speciation of Selected Metals in Water Systems within Kajiado North Constituency in Kenya

Heavy metals and anions in water pose a significant risk to living organisms, including humans, and must therefore be carefully monitored. There are numerous approaches and methods of analysis to choose from. Using the PHREEQ C chemical modeling technique, this study looked at the effect of certain anions on the speciation of selected metals in the water environment of Kajiado North. Twenty-five sampling points were used in the study, which covered five Kajiado North election wards. Samples were taken twice during the dry and rainy seasons, in November 2019 and March 2020. Using standard methods, physicochemical characteristics were analyzed, concentrations of selected heavy metals using the (ICP- OES) 7000 series, and selected anions using a multi parameter photometer, their concentration values compared to the specified maximum contaminant level and speciation analysis done using the Computer-based technique PHREEQ C. The range observed for pH, temperature, electrical conductivity, sulphate, chloride, fluoride, nitrate and carbonates was 7.43- 9.30, 23.0 -28.0oC, 335-1265μS/cm, 4.54-361.41mgL-1, 5.19-184.6 mgL-1, 0.01-2.90 mgL-1, 0.1-8.6 mgL-1, and 3.18-55.19 mgL-1 respectively. The range observed for heavy metals was 0.06-1.08 mgL-1 , 0.00 -0.05082 mgL-1, 0.01-0.02597 mgL-1, 0.01-0.01610 mgL-1, 0.00 -0.0327 mgL-1, 0.00-42.7842 mgL-1, and below detection limit, for Fe, Mn, Cu, Zn, Pb, Mg, and Cd respectively. The findings revealed that Cd, Zn, Cu, Cl-, NO2-, and eElectrical cconductivity concentrations were below the WHO levels. At certain sampling points, however, SO42-, F-, Pb, Fe, and Mn were above WHO limits. In some water systems, traces of SO42-, F-, Cu, Fe, Cd, and Mn were found to pose significant health risks, according to PHREEQ C speciation analysis. Anion concentrations, pH, temperature, and metal concentrations are all important variables in modeling. Metals formed anion complexes and the total abundance of metal species was classified at the highest levels as Fe(OH)3, PbCO3, Zn(CO3)2, Cu(CO3)2, Mn+2, MgF-, and Mg+2. At a water system temperature of 25oC without anions, it was found to have the highest chemical species. CuCO3, CuNO3, and CuOH+ complexes are also formed at low pH. Based on the data for different metal species at different pH values, the bioavailability of metal species definitely depends on pH.

Application of Sampling Methods for Constrained Space in Hull Form Optimization

Use of approximation models instead of direct application of CFD tools plays a crucial role in hull form optimization to enhance efficiency. The selection of sample points directly impacts the accuracy and cost of approximation models, and the effectiveness of hull form optimization. This paper presents a sampling method based on constrained space. The distribution pattern of the constrained space is initially analyzed, and its boundary is subsequently extracted by the Support Vector Machine (SVM), providing guidance for the subsequent sample selection. To ensure effective sampling within the constrained space, the maximum minimum distance criterion is employed. The proposed methodology is validated via a case study involving a 13,000DWT inland twin-screw bulk carrier. The Kriging approximation model is constructed to optimize the hull form while adhering to specific constraint conditions, thereby demonstrating the feasibility and efficacy of the proposed approach.

Novel study on active reliable PID controller design based on probability density evolution method and interval-oriented sequential optimization strategy

Vibration active control is a significant problem in practical engineering, but the influence of hybrid uncertainties in practical engineering cannot be ignored. For the uncertainties with adequate data, probability theory can be used while for the uncertainties with insufficient data, probability theory is limited and interval quantification can be used. Taking the widely used proportional-integral-differential (PID) control as an example, a novel study on controller design based on probability density evolution method and interval-oriented sequential optimization strategy considering interval and random uncertainties is proposed. Firstly, under a certain sample point of interval uncertainties, probability density evolution equation is utilized to calculate the probability density function of uncertain response considering only random uncertainties. In this way the probabilistic reliability corresponding to the sample point can be obtained. Then the hybrid reliability is defined as the average probability within the interval uncertainty and the adaptive dichotomy method is utilized to choose proper sample points of interval uncertainties, in which the reliability curve and the interval uncertainty axis is regarded as the judgement of convergence. Next the hybrid reliability is introduced to the optimization as a constraint and the PID gains reliable design optimization is established to balance the energy-consuming and safety. Finally, the sequential optimization strategy is adopted to improve the efficiency of optimization. In every iteration step of the optimization, the constraint of deterministic optimal design is adjusted according to the static reliability at the moment before the passage or reaching the maximum value. Three numerical examples are presented to demonstrate the accuracy and practicability of the proposed framework.

Source identification of polycyclic aromatic hydrocarbons (PAHs) in soils around crude oil contaminated area in Ohaji/Egbema, Imo State

ABSTRACT This study aims to determine the source of polycyclic aromatic hydrocarbons (PAHs) in the soils surrounding an area in Ohaji/Egbema, Imo State, that has been contaminated by crude oil. Soil samples were collected in the study area using a soil auger at a depth of 0–20 cm at three sampling locations (sample A, sample B, and sample C) in the Mmahu community in Ohaji/Egbema. In each of the sampling locations, twenty sub-samples were collected from twenty sampling points and pooled together to form representative samples for each of the sampling locations. Prior to GC-MS analysis, the composite samples were air-dried, sieved through a 2-mm mesh, and then kept in pet bottles that had been previously cleaned. The GC-MS investigations were carried out using a Shimadzu Model 2010 GC-MS (Shimadzu, Japan) fitted with an HP-5 MS fused silica column. This was used to quantify the 16 USEPA priority PAHs in the studied soils. The sum of the 16 USEPA priority PAHs in the sample locations ranged from 0.0192 mg/kg in the control sample to 10.73 mg/kg in sample A. Compared to high molecular weight PAHs (4–6 rings), the total concentration of low molecular weight PAHs (2–3 rings) was found to be substantially greater. According to the PAH molecular diagnostic ratio, all sampling points had low to high molecular mass ratios >1, which suggests that the origin of the PAH contamination was petrogenic. The petrogenic source of contamination was attributed to oil spillage around the study area. The knowledge of source identification of PAHs in soils helps in the determination of the most appropriate remediation strategy in order to prevent further contamination and minimise the risks to human health and the environment.

Path planning for robotic fish based on improved RRT* algorithm and dynamic window approach

Purpose The purpose of this paper is to address two major challenges faced by robotic fish when operating in underwater environments: insufficient path planning capabilities and difficulties in avoiding dynamic obstacles. To achieve this, a method is proposed that combines the Improved Rapid Randomized Tree Star (IRRT*) with the dynamic window approach (DWA). Design/methodology/approach The RRT-connect algorithm is used to determine an initial feasible path quickly. The quality of sampling points is then improved by dividing the regions and selecting each region’s probability based on its fitness value. The fitness function and roulette wheel method are introduced for region selection. Subtarget points of the DWA algorithm are extracted from the IRRT* algorithm to achieve real-time dynamic path planning. Findings In various maps, the iteration count for the IRRT* algorithm decreased by 61%, 35% and 51% respectively, compared to the RRT* algorithm, whereas the iteration time was reduced by 75%, 34% and 57%, respectively. In addition, the IRRT*-DWA algorithm can successfully navigate through multiple dynamic obstacles, and the average time, path length, etc. do not change much when parameters change, and the stability is high. Originality/value A novel IRRT*-DWA algorithm is proposed, which, by refining the sampling strategy and updating sub-target points in real time, not only addresses the limitations of existing algorithms in terms of path planning efficiency in complex environments but also enhances their capability to avoid dynamic obstacles. Ultimately, experimental results indicate a high level of similarity between the actual and ideal paths.

Remote sensing inversion on heavy metal content in salinized soil of Yellow River Delta based on Random Forest Regression—a case study of Gudao Town

To explore the potential of using the mineral alteration information extracted by remote sensing technology to indirectly estimate the heavy metal content of salinized soil, 23 sampling points were uniformly set up in the town of Gudao in the Yellow River Delta as the research area in 2022. The concentrations of seven heavy metals, Cr, Cu, Pb, Zn, As, Mn and Ni, at the sampling points were determined in laboratory tests. Spectral derivative indices, topographic factors, and mineral alteration information (iron staining, hydroxyl, and carbonate ions) were extracted and screened as modeling factors using Sentinel 2 imagery. An inverse model of heavy metal content was constructed using the random forest algorithm, and the model accuracy was evaluated using the cross-validation method. The results of the study show that: (1) Hydroxyl and carbonate ion alteration can be effectively used for the inversion of soil As and Ni content in this study area. Iron-stained alteration can be used as a modeling factor in the inversion of Cr, Cu, Pb, Zn, and Mn concentrations. (2) The inclusion of alteration information improves the accuracy of heavy metal content inversion. The Cu concentration was verified to be the best predictor, with an RMSE of 3.309, MAPE of 11.072%, and R2 of 0.904, followed by As, Ni, and Zn; the predictive value of Mn, Cr and Pb was average. (3) Based on the results of concentration inversion, the high concentration areas of As, Ni, and Mn are primarily distributed on both sides of the river and around lakes and ponds. The high-concentration areas of Zn were mainly distributed in the farmland areas on both sides of the river. Areas with high concentrations of Cu were mainly distributed in the eastern oil extraction area, both sides of the rivers, and around lakes.

Water quality assessment of Bheemasandra Lake, South India: A blend of water quality indices, multivariate data mining techniques, and GIS.

An integrated approach combining water quality indices (WQIs), multivariate data mining, and geographic information system (GIS) was employed to examine the water quality of Bheemasandra Lake, located adjacent to a sewage treatment plant (STP) in Tumakuru city, India. The analysis of 22 lake water samples, examined before and after the monsoons, revealed that the physicochemical parameters namely - electrical conductivity, biochemical oxygen demand, turbidity, total dissolved solids, ammoniacal nitrogen, nitrates, phosphates, magnesium, total hardness, total alkalinity, and calcium - exceeded the acceptable limits stipulated by national and international standards. The Canadian Council of Ministers of the Environment WQI (pre-monsoon: 25.3; post-monsoon: 33.9) and weighted arithmetic WQI (pre-monsoon: 3398; post-monsoon: 2093) designated the water as unsafe for drinking. Irrigation WQIs (sodium adsorption ratio, sodium percentage, residual sodium carbonate, magnesium hazard, permeability index, and potential salinity) implied water's suitability for irrigation. However, electrical conductivity indicated otherwise. Industrial WQIs (Larson-Skold Index, Langelier Index, Aggressive Index, and Puckorius Scaling Index) illustrated scaling propensity and the chloride sulfate mass ratio alluded galvanic corrosion potential. Hierarchical cluster analysis gathered 22 sampling points into two clusters (cluster 1: relatively lower polluted regions; cluster 2: highly polluted regions) for each season based on similarities in water features. Principal component analysis extracted four (79.07% cumulative variance) and six (87.14% cumulative variance) principal components before and after the monsoons, respectively. These components identified the primary pollution sources as urban sewage and natural lithological processes. WQI maps, created using the inverse distance weighted interpolation technique, enhanced the visualization of spatial-temporal variations. This study highlights the dire consequences of urbanization, STP pollution, and sewage management failures, necessitating that concerned authorities should implement policies and measures to curb the negative impacts on the environment and public health.

Validation of a bupropion, dextromethorphan, and omeprazole cocktail for simultaneous phenotyping of cytochrome P450 2B11, 2D15, and 3A12 activities in dogs.

Develop a cytochrome P450 (CYP) phenotyping cocktail for dogs using specific substrates for hepatic P450 enzymes CYP2B11, CYP2D15, and CYP3A12 and determine whether alternative sampling methods (saliva and urine) or single time point samples could be used instead of multiple blood sampling. 12 healthy client-owned dogs (8 females and 4 males) from February 2019 to May 2019. In a randomized crossover study, dogs received oral administration of the probe drug bupropion (75 mg), dextromethorphan (30 mg), or omeprazole (40 mg) alone or as a 3-drug combination (Program in Individualized Medicine [PrIMe] cocktail) to evaluate simultaneous phenotyping of CYP2B11, CYP2D15, and CYP3A12. Pharmacokinetic profiles for the probe drugs and metabolites were determined using plasma, saliva, and urine. Dogs received probe drugs alone or combined. Pharmacokinetic profiles up to 6 hours postdose for the probe drugs and metabolites were determined using plasma, saliva, and urine. The PrIMe cocktail was well tolerated. There was no statistically significant interaction between the probe drugs when administered together. Single time point plasma metabolic ratios at 4 hours postdose for all probe drugs strongly correlated with the corresponding area under the plasma concentration-versus-time curve (AUC) ratios. Saliva AUC metabolic ratios for CYP3A12 and CYP2D15 and 6-hour urine for CYP2B11 and CYP2D15 were correlated with plasma AUC ratios. The PrIMe cocktail can be used for simultaneous CYP phenotyping using plasma 4-hour single time point sample metabolic ratios. Saliva and urine sampling are suitable for specific CYPs. The PrIMe cocktail has potential as a useful tool in dogs to detect clinically important CYP-mediated drug-drug interactions, identify novel pharmacogenes, determine the drug-metabolizing phenotype of individual dogs, aid in individualized dose selection, and evaluate the effects of various physiological states on drug metabolism.

Land Subsidence Susceptibility Mapping in Ca Mau Province, Vietnam, Using Boosting Models

The Ca Mau Peninsula, situated in the Mekong Delta of Vietnam, features low-lying terrain. In addition to the challenges posed by climate change, land subsidence in the area is exacerbated by the overexploitation of groundwater and intensive agricultural practices. In this study, we assessed the land subsidence susceptibility in the Ca Mau Peninsula utilizing three boosting machine learning models: AdaBoost, Gradient Boosting, and Extreme Gradient Boosting (XGB). Eight key factors were identified as the most influential in land subsidence within Ca Mau: land cover (LULC), groundwater depth, digital terrain model (DTM), normalized vegetation index (NDVI), geology, soil composition, distance to roads, and distance to rivers and streams. The dataset includes 2011 points referenced from the Persistent Scattering SAR Interferometry (PSI) method, of which 1011 points are subsidence points and the remaining are non-subsidence points. The sample points were split, with 70% allocated to the training set and 30% to the testing set. Following computation and execution, the three models underwent evaluation for accuracy using statistical metrics such as the receiver operating characteristic (ROC) curve, area under the curve (AUC), specificity, sensitivity, and overall accuracy (ACC). The research findings revealed that the XGB model exhibited the highest accuracy, achieving an AUC and ACC above 0.88 for both the training and test sets. Consequently, XGB was chosen to construct a land subsidence susceptibility map for the Ca Mau Peninsula. In addition, 31 subsidence points measured by leveling surveys between 2005 and 2020, provided by the Department of Survey, Mapping and Geographic Information Vietnam, were used for validating the land subsidence susceptibility from the XGB method. The findings indicate a 70.9% accuracy rate in predicting subsidence susceptibility compared to the leveling measurement points.

Assessment of Microplastic Pollution in River Ecosystems: Effect of Land Use and Biotic Indices

The proximity of freshwater ecosystems to anthropogenic activities makes them one of the most threatened environments by plastic pollution in the form of microplastics (MPs). Therefore, it is crucial to identify the primary drivers of MP dynamics in rivers to enhance their management. This work analyzed the concentration of MPs in water and sediments and evaluated the influence of land use and its relationship with the main biotic indices employed to assess the water quality of rivers. This research was carried out in four different catchments, with three sampling points established in each river basin. The results revealed that MPs were ubiquitous across all locations, with concentrations ranging from 0.10 to 35.22 items m−3 in waters and from 26 to 643 items Kg−1 in sediments. The highest concentration of MPs both in water and sediments were found in the Lagares River (35.22 items m−3 and 643 items Kg−1), while the lowest concentrations were found in the Miñor River for water (0.10 items m−3) and Tea River for sediments (138 items Kg−1). Urbanization degree was identified as the primary driver of MP pollution in water, whereas population density correlated with sediment pollution levels. These findings explain the elevated MPs abundance in the more urbanized and populated Gafos and Lagares rivers compared to the relatively pristine Miñor and Tea rivers. Furthermore, the presence of MPs in sediments was found to negatively impact the most sensitive benthic macroinvertebrate taxa, as evidenced by lower values of the IASPT and EPT indices at sampling points with higher sediment MPs concentrations (Gafos and Lagares).

Trends in Water Quality in a Tropical Kenyan River-estuary System: Responses to Anthropogenic Activities

Aims: To determine the spatial variation in physico-chemical water quality attributes in estuarine ecosystems of South Coast Kenya to inform its management. Study Design: We employed diagnostic research design where such factors as anthropogenic activities, hydrology, and accessibility were considered in choosing 12 sampling stations. A mixed sampling design (probability and non-probability) was used to sample. Place and Duration of Study: Four discharging rivers into estuarine system with a reference point were identified. 12 sampling points were earmarked and sampled for 12 months. Methodology: Nine selected water quality parameters were collected in triplicates monthly for 12 months. Temperature, dissolved oxygen, pH, conductivity, salinity and TDS were collected in situ using YSI Multiparameter meter (Professional plus) while nutrients were analyzed in the laboratory calorimetrically. Data was tested for normality and homogeneity of variances using Levene's and Shapiro-Wilk tests. Two-way analysis of variance (ANOVA), and Principal Component Analysis (PCA) were done using the 64-bit R Software version 4.3.0 to test for significant differences and correlate the parameters among the sampling sites respectively. Observed differences were considered statistically significant at P < 0.05. Results: The measured environmental variables differed significantly among the sampling stations (P < 0.05). temperature and salinity exhibited moderate to strong effect on water quality, while pH and nutrients (phosphates, nitrates, and ammonia) exhibited mixed effects with both negative and positive loadings on the Principal Components. It is demonstrated that the south coast estuary, Kenya is affected by two gradients: mineralization from the sea and the organic matter gradient at the upstream stations dominated by the fluvial inflows from the respective rivers. Conclusion: The south coast of Kenya estuary is impacted by natural processes and anthropogenic activities. we recommend for continued regular water quality assessment and monitoring to acquire sufficient data to shape policy frameworks towards its sustainable management.

Dynamic characteristics and evolution laws of underground brine in Mahai salt lake of Qaidam Basin during mining process

In the late stage of underground brine mining in salt lakes, the method of injecting fresh water is often used to extract the salt from the brine storage medium. This method of freshwater displacement breaks the original water–rock equilibrium and changes the evolution process of the original underground brine. To explore the mechanism of salt release in saline water-bearing media under conditions of relatively fresh lake water dissolution, this paper analyzes the changes in the chemical parameters of brine from 168 sampling points in the Mahai salt lake in the Qaidam Basin at three stages (before exploitation, during exploitation, and late exploitation) by correlation analysis, ion ratio analysis, and other methods and investigate the variations in porosity and the evolution laws of brine. The results show that the changes in the main ion content and brine mineralization during the exploitation process are small. The changes in Ca2+ content are significant due to the low solubility of calcium minerals, the precipitation of gypsum during the mixing process, and the adsorption of cations by alternating with Ca2+. Primary intergranular pore skeletons are easily corroded to form secondary pores, which increase the geological porosity. Na+ and Cl- are the dominant ions in the brine in the study area, but the concentration of Ca2 + decreased significantly under the influence of mining, by 41.7% in the middle period and 24.5% in the late period. The correlation between Ca2+ and salinity changes significantly in different mining stages, and the reason for the decrease of Ca2+ may be due to the influence of mineral dissolution, mixing, and anion-cation exchange. The porosity of the layer in the study area showed the opposite trend of Ca2+, and the porosity increased first and then decreased. The innovation of this paper lies in analyzing the reasons and mechanisms of the disturbance of artificial dissolution mining on stratum structure by comparing the hydrochemical characteristics and porosity of underground brine storage media in three different mining stages. The research in this paper provides a theoretical basis for the calculation of brine resource reserves and the sustainable development of underground brine in salt lake areas.

From field soil sampling to watershed model: Upscaling by integrating information entropy and interpolation method

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.

Magnetotelluric sampling theorem

We consider a general case of a magnetotelluric (MT) study to reveal three-dimensional (3D) distribution of the electrical conductivity within the Earth based on measurements of electromagnetic (EM) fields by a two-dimensional (2D) array. Such an MT array observation can be regarded as a spatially discrete sampling of the MT responses (impedances), and each observation site can be regarded as a sampling point. This means that MT array measurements must follow the Nyquist–Shannon sampling theorem. This paper discusses how the sampling theorem is applied to MT array studies and what kind of consideration is required in the application on the basis of synthetic model calculations, with special attention to spatial resolutions. With an aid of the EM scattering theory and the sampling theorem, we can show that an observation array resolves some features of the MT impedance but does not others. We call the resolvable and unresolvable features the MT signal and noise, respectively. This study introduces the spatial Fourier transform of array MT data (impedances) which helps us investigating sampling effects of lateral heterogeneity from a different angle (in the wavenumber domain). Shallow heterogeneities cause a sharp spatial change of impedance elements near structural boundaries. High wavenumber Fourier components are required to describe such a feature, which means the site spacing must be sufficiently short to be able to resolve such features. Otherwise, a set of array MT data will suffer from aliasing, which is one of the typical causes of MT distortion (MT geologic noise). Conversely, a signal due to a deep-seated conductivity anomaly will have more reduced amplitude at higher wavenumbers, which means focused imaging of such an anomaly is generally difficult. Finally, it is suggested to properly consider the sampling theorem in an observation array design, so as to have best performance in resolving MT signals.Graphical abstract

Adherence to sleep recommendations is associated with higher satisfaction with life among Norwegian adolescents

BackgroundSleep plays a crucial role in the health and well-being of adolescents; however, inadequate sleep is frequently reported in numerous countries. This current paper aimed to describe sleep duration, factors impacting sleep, consequences of insufficient sleep and satisfaction with life in Norwegian adolescents, stratified by sex and by adherence to the 8-hour sleep recommendation, and to examine potential associations between adherence to the 8-hours sleep recommendation and satisfaction with life.MethodsThis is a cross-sectional study using data from the Norwegian Ungdata Survey, collected in 2021. Adolescents from five Norwegian counties were included, comprising a total of 32,161 upper secondary school students. Study variables were collected through an electronic questionnaire administered during school hours and all data are anonymous. Descriptive data of sleep patterns are presented, and linear regressions were conducted adjusting for SES, perceived stress, physical activity level, over-the-counter analgesics use, grade level and screen time.Results73% of adolescents did not adhere to the 8-hours of sleep recommendation per night, with similar results for girls and boys. 64% reported tiredness at school (minimum 1–2 days weekly) and 62% reported that screen time negatively affected their ability to sleep. 23% reported that gaming affected their sleep, with a higher prevalence in boys than girls. Satisfaction with life score was 7.0 ± 1.9 points (out of 10) for the total sample, with higher scores for boys (7.3 ± 1.8 points) than girls (6.9 ± 1.9 points). Regressions revealed a positive association with satisfaction with life (B = 0.31, 95% [0.15 to 0.48]) in adolescents adhering to sleep recommendation of 8h compared to the ones not adhering to the sleep recommendation.ConclusionsMost Norwegian adolescents fail to adhere to the 8-hours of sleep recommendation and the majority feel tired at school or during activities. More than half of adolescents reported that screen time negatively affected their ability to sleep. Adhering to the sleep recommendation was associated with higher life satisfaction. Our findings highlight the importance of sufficient sleep in adolescents, while future research is needed to examine other sleep related measures on adolescents´ satisfaction with life.

Dynamics of dissolved inorganic carbon (DIC) and stable C isotope ratios (δ13CDIC) in a tropical watershed with diversified land use in São Paulo State, Brazil

The fluvial transport of dissolved inorganic carbon (DIC) is an important component of the global carbon cycle. Herein, we assessed the dynamics of DIC and the C stable isotopic composition (δ13CDIC) in a watershed with diversified land use in São Paulo State (Brazil), more specifically in the Sorocaba River basin (SRB) and considered the temporal and spatial scales. For this purpose, twelve fluvial samples at each sampling point (e.g., S1, S2, S3, S4 and S5) were collected in the SRB, from June 2009 to May 2010, which represented one complete hydrological cycle that included the extremes of the rainfall and discharge regimes. In addition, the δ13CDIC values were also characterized in the wet and dry season at all sampling points to verify their seasonal variability. The results reflected the seasonal variation in discharges, water temperatures, and electrical conductivities. Most of the DIC was transported in the wet season at all sampling points, where the less negative δ13CDIC values were characterized. The natural sources of DIC are associated with atmospheric/soil CO2 consumption. The anthropogenic impacts on both [DIC] and δ13CDIC are linked to untreated urban sewage that is discharged directly into the Sorocaba River, as well as to aquatic photosynthesis in the Itupararanga Reservoir. From 1970 to 2020, the modeling proposed in this study indicated that the annual flux of DIC (Friver) varied from 9.0 to 78.7 t km−2 a−1, confirming that the El Niño Southern Oscillation (ENSO) controlled Friver in the SRB, with higher and lower Friver values occurring during strong El Niño (EN) and La Niña (LN) years. The average Friver value was 20 t km−2 a−1, which is higher than those obtained in natural several temperate and tropical watersheds due to the influences of urban areas on [DIC] in the SRB.

Mapping the dynamics of intensive forage acreage during 2008–2022 in Google Earth Engine using time series Landsat images and a phenology-based algorithm

The increasing demand for livestock feed in China has led to a remarkable increase in forage acreage, particularly in forage fields under intensive agricultural management. However, there are no maps currently available to demonstrate and document the spatial and temporal patterns of the continuous expansion of intensive forage. Here we proposed a pixel- and phenology-based approach to map intensive forage by utilizing time series Landsat images and the Google Earth Engine platform. Given the challenge of accurately identifying intensive forage fields in diverse regions using fixed multi-temporal Landsat data, along with the distinct phenological characteristics of intensive forage fields that undergo multiple annual harvests, we proposed an innovative data mining approach based on dynamic monthly composite images (DMCI). This approach aims to enhance the algorithm’s efficiency and precision in identifying intensive forage. As a pilot study, we analyzed all available Landsat images (1732 scenes) from 2008 to 2022 in a county located in the farming-pastoral ecotone of northern China and tracked the historical dynamics of intensive forage expansion over five epochs at three-year intervals. The accuracy assessment of the intensive forage maps for the five epochs using validation sample points showed that the overall accuracy and Mathews correlation coefficient ranged from 97.1 % to 98.9 % and 0.93 to 0.98 respectively. The intensive forage acreage in the study area exhibited a dramatic expansion from 2008 to 2022, particularly after the 2012s. This study demonstrates the potential of our DMCI- and phenology-based algorithm and time series Landsat images for tracking the dynamics of intensive forage acreage at 30-m resolution in temperate single-cropping regions.

An Investigation into the Pole–Slot Ratio and Optimization of a Low-Speed and High-Torque Permanent Magnet Motor

At present, low-speed high-torque permanent magnet motors are widely used in the sampling industry, manufacturing industry and energy industry. However, the research on low-speed high-torque permanent magnet motors is far from enough. The primary difficulty in the initial design of low-speed high-torque permanent magnet motors is the selection of pole–slot ratio. The pole–slot ratio has a great influence on the electromagnetic performance such as torque ripple and the maximum output torque of low-speed motors. Choosing the appropriate pole–slot ratio scheme can make the design of a low-speed motor more efficient. In addition, the optimization design of the motor is also a necessary process. At present, there are many studies on optimization algorithms. However, the research on sample point sampling and surrogate model fitting is not enough. Choosing the appropriate sample point sampling method and surrogate model fitting method can help one obtain a more accurate surrogate model, which lays a foundation for the optimization of the motor. Based on the above analysis, this paper first selects four representative pole–slot ratio schemes for comprehensive comparison of their electromagnetic performances. Secondly, two sample point sampling methods and three surrogate model fitting methods are combined to obtain six surrogate models, and the accuracy of the six surrogate models is compared and analyzed. Finally, a 37kW,160rpm prototype is made, and the comparison of the surrogate model optimization prediction results, the finite element simulation calculation results and the measured results is carried out to further prove the accuracy of the selected surrogate model. The work performed in this paper provides a certain reference value for the initial design and optimization experiment design of low-speed high-torque permanent magnet motor.