Weighted Research Articles

ВИКОРИСТАННЯ АЛГОРИТМУ ДЕЙКСТРИ ПРИ КОМП'ЮТЕРНОМУ ПОШУКУ ОПТИМАЛЬНОГО ШЛЯХУ НЕОРІЄНТОВАНОГО ГРАФА З УРАХУВАННЯМ ВПЛИВУ РАДІАЛЬНОГО ОХОПЛЕННЯ НА ВАГОВІ ФУНКЦІЇ РЕБР

Taking into account the influence of radial coverage, the weight functions of the edges of an undirected graph during the computer search for the optimal path are determined. Algorithms and computer programs were used to find the optimal path of the graph using the Dijkstra algorithm, which made it possible to determine the tension and changes in the relative tension in the filling zones of knitted and textile machines, taking into account the specifics of the design of the thread feeding system. This leads to a decrease in thread breakage. The development of mathematical models for determining the reduced coefficient of friction during the interaction of the thread with the ring and tubular thread guides of knitting machines allows the use of algorithms and computer programs to find the optimal path of the graph, using Dijkstra's algorithm, in which the tension of the thread at the exit point will be minimal. This makes it possible to determine the tension and change of relative tension in the filling zones of knitted and textile machines, taking into account the specifics of the design of the thread feeding system, taking into account the effect of radial coverage. Searching for the optimal path of the graph allows you to reduce thread breakage and optimize thread tension in the working area of ​​the initial product formation. Determining the weight functions of edges, taking into account the influence of radial coverage, unoriented graph during the computer search for the optimal path is an important component of the optimization of thread tension in the working zone of the formation of the output product. Tension optimization is carried out on the basis of its minimization, which allows to reduce the probability of a break in the working area. Optimization of the geometric parameters of the thread feeding system on the technological equipment, namely the construction of such a broken form of the thread, in which the total angle of coverage of the constructive structural elements of the technological equipment in the form of guides of a cylindrical shape and in the form of a torus, elements of tensioning devices, devices for monitoring breakage will have a minimum value. This will reduce the amount of friction force between the thread and the guide surfaces and obtain minimum tension in the working area. Taking into account the large number of structural elements of the thread feeding system on technological machines, their location in the plane and space, there is a need to use modern information technologies.

Preliminary analysis of global column-averaged CO2 concentration data from the spaceborne aerosol and carbon dioxide detection lidar onboard AEMS

In contrast to the passive remote sensing of global CO2 column concentrations (XCO2), active remote sensing with a lidar enables continuous XCO2 measurements throughout the entire atmosphere in daytime and nighttime. The lidar could penetrate most cirrus and is almost unaffected by aerosols. Atmospheric environment monitoring satellite (AEMS, also named DQ-1) aerosol and carbon dioxide detection Lidar (ACDL) is a novel spaceborne lidar that implements a 1572 nm integrated path differential absorption (IPDA) method to measure the global XCO2 for the first time. In this study, special methods have been developed for ACDL data processing and XCO2 retrieval. The CO2 measurement data products of ACDL, including the differential absorption optical depth between the online and offline wavelengths, the integral weighting function, and XCO2, are presented. The results of XCO2 measurements over the period from 1st June 2022 to 30th June 2022 (first month data of ACDL) are analyzed to demonstrate the measurement capabilities of the spaceborne ACDL system.

Effect of Ethanol Leaf Extract of Lantana camara on Fasting Blood Glucose, Body Weight and Kidney Function Indices of Alloxan-Induced Diabetic Albino Wistar Rats

The study was aimed at investigating the effect of ethanol leaf extract of Lantana camara on the fasting blood glucose, body weight and kidney function indices of alloxan-induced diabetic albino Wistar rats. Thirty male albino Wistar rats of weight 100-181 g were randomly assigned six groups of five rats each. Group 1 served as normal control. Group 2-6 animals were induced with 150 mg/kg body weight (B.W) of alloxan monohydrate intraperitoneally. Fasting blood glucose was checked 72hrs after induction and animals with blood glucose 200mg/dl and above were considered diabetic. Group 3 was treated with 50 mg/kg B.W of glibenclamide. Group 4,5 and 6 were orally treated with 600, 800 and 1000 mg/kg B.W of Lantana camara extract respectively for 21days. Blood sample was obtained by tail puncture to check glucose levels weekly with the use of glucometer. Animals treated with 600, 800 and 1000 mg/kg B.W of the extract showed significant decrease (P<0.05) in blood glucose, creatinine, urea and uric acid compared to untreated diabetic animals. Body weight of treated groups increased significantly (P<0.05) compared to the untreated group. The results obtained were synonymous to the glibenclamide treated group. This suggests that the extract possess antidiabetic potential and could be used in the management of diabetes.

Fish intake and mercury exposure in young children

Fish consumption is one of the main sources of mercury (Hg) exposure, but few studies have examined Hg exposure from fish consumption among children. This study aimed to assess the frequency of fish intake and associations with Hg and other element concentrations among 700 three-year-old children from the New Hampshire Birth Cohort Study. Usual fish intake was derived from a validated food frequency questionnaire (Block Questionnaire for ages 2–7) and toenail element concentrations were determined using ICP-MS. Multiple linear regression analysis was used to assess the association between fish intake and toenail element concentrations. A mixture analysis, using Weighted quantile sum (WQS) regression, was used to estimate the relative contribution of fish consumption to element exposures. Twenty-three percent of children were reported to consume at least one fish meal/week on average during the previous 6 months. In adjusted linear regression models, children with any type of fish consumption versus no consumption had 108% (95% confidence interval (CI: 68%, 153%)) higher toenail Hg concentrations. To a lesser extent, children consuming “other fish (not fried) including tuna” and “fried fish or fish sticks” had 120% (95% CI: 82%, 164%), and 23% (95% CI: 2%, 51%) higher toenail concentrations, respectively, than those consuming no fish. Using WQS regression, Hg was the element most strongly related to fish consumption. Fish intake among young children was related to Hg exposure even at low levels of consumption. Future studies will need to determine the health consequences of this exposure.

A Rapid Detection Method for Coal Ash Content in Tailings Suspension Based on Absorption Spectra and Deep Feature Extraction

Traditional visual detection methods that employ image data are often unstable due to environmental influences like lighting conditions. However, microfiber spectrometers are capable of capturing the specific wavelength characteristics of tail coal suspensions, effectively circumventing the instability caused by lighting variations. Utilizing spectral analysis techniques for detecting ash content in tail coal appears promising as a more stable method of indirect ash detection. In this context, this paper proposes a rapid detection method for the coal ash content in tailings suspensions based on absorption spectra and deep feature extraction. Initially, a preprocessing method, the inverse time weight function (ITWF), is presented, focusing on the intrinsic connection between the sedimentation phenomena of samples. This enables the model to learn and retain spectral time memory features, thereby enhancing its analytical capabilities. To better capture the spectral characteristics of tail coal suspensions, we designed the DSFN (DeepSpectraFusionNet) model. This model has an MSCR (multi-scale convolutional residual) module, addressing the conventional models’ oversight of the strong correlation between adjacent wavelengths in the spectrum. This facilitates the extraction of relative positional information. Additionally, to uncover potential temporal relationships in sedimentation, we propose a CLSM-CS (convolutional long-short memory with candidate states) module, designed to strengthen the capturing of local information and sequential memory. Ultimately, the method employs a fused convolutional deep classifier to integrate and reconstruct both temporal memory and positional features. This results in a model that effectively correlates the ash content of suspensions with their absorption spectral characteristics. Experimental results confirmed that the proposed model achieved an accuracy of 80.65%, an F1-score of 80.45%, a precision of 83.43%, and a recall of 80.65%. These results outperformed recent coal recognition models and classical temporal models, meeting the high standards required for industrial on-site ash detection tasks.

PDHL-MARCOS method based on cumulative prospect theory for MAGDM and its application in network security evaluation

The increasingly large and complex network brings convenience to our life and production, but it also brings potential dangers. Any minor vulnerability may lead to failure of application software configuration, software maintenance, user management and system management. Eventually, our network is interrupted, and even life and production data are leaked. Therefore, establishing a scientific and effective network security evaluation model is an effective way to supervise, manage and improve network security; It is also an effective measure to reduce the loss of life and production. Therefore, we first selected six factors closely related to network security to form a complete network security evaluation index system. Then, the utility function in the traditional measurement of alternatives and ranking according to compromise solution (MARCOS) method is improved by using the value function in cumulative prospect theory (CPT), and a PDHL-MARCOS evaluation model that can reflect the decision-makers’ (DMs’) attitudes towards gains and losses is obtained in the probabilistic double hierarchy linguistic term set (PDHLTS). In addition, the relative entropy (RE) method is also used to obtain expert weights. The combination weights of attributes are obtained using the correlation coefficient and the standard deviation (CCSD) method and the weight function in CPT.

On Orlicz classes defined in terms of associated weight functions

N-functions and their growth and regularity properties are crucial in order to introduce and study Orlicz classes and Orlicz spaces. We consider N-functions which are given in terms of so-called associated weight functions. These functions are frequently appearing in the theory of ultradifferentiable function classes and in this setting additional information is available since associated weight functions are defined in terms of a given weight sequence. We express and characterize several known properties for N-functions purely in terms of weight sequences which allows to construct (counter-) examples. Moreover, we study how for abstractly given N-functions this framework becomes meaningful and finally we establish a connection between the complementary N-function and the recently introduced notion of the so-called dual sequence.

Detecting diabetic retinopathy using a hybrid ensemble XL machine model with dual weighted-Kernel ELM and improved mayfly optimization

The uncontrolled increase of blood glucose level affects the retina and cause Diabetic Retinopathy (DR), which can permanently damage blood vessels if left untreated for a long time. Early detection helps the patient’s to minimize the severity level. However, the existing Synergic Deep Learning (SDL) model for detecting severity levels of fundus DR images lacks proper filtering methods, suffers from low image quality, and improperly tuned hyperparameters. To address these issues, a hybrid ensemble Extreme Learning (XL) machine model is proposed in detection and classification of DR. The proposed model includes preprocessing steps, such as image filtering, conversion, segmentation, and morphological operations, to improve image quality. Also the parameters are tuned effectively and the weight functions are analyzed based on the extracted features that lower the blurriness of the images. A Dual Weighted-Kernel Extreme Learning Machine (DW-KELM) is developed to classify DR images with improved accuracy, and an Improved Mayfly Optimization (IMO) algorithm is applied to optimize the DW-KELM model’s parameters. Implementing the Weighted Average Ensemble (WAE) technique enhances the model’s performance by allocating different weights. Two datasets, namely the SUSTech-SYSU, APTOS-2019 and IDRID datasets, are used for experimentation, and the results revealed that DW-KELM achieved 99% accuracy, with an overall sensitivity, specificity, precision, and F1-score of 98.52%, 96.32%, 98.10%, and 98.52% respectively. The proposed model achieved better performance in classifying 5 DR classes, including moderate DR, Proliferative DR, no DR, severe DR, and mild DR, with good image quality.

Analyticity theorems for parameter-dependent plurisubharmonic functions

In this paper, we first show that a union of upper-level sets associated to fibrewise Lelong numbers of plurisubharmonic functions is in general a pluripolar subset. Then we obtain analyticity theorems for a union of sub-level sets associated to fibrewise complex singularity exponents of some special (quasi-)plurisubharmonic functions. As a corollary, we confirm that, under certain conditions, the logarithmic poles of relative Bergman kernels form an analytic subset when the (quasi-)plurisubharmonic weight function has analytic singularities. In the end, we give counterexamples to show that the aforementioned sets are in general non-analytic even if the plurisubharmonic function is supposed to be continuous.

Evaluating alternative fuels for a bus fleet: An Italian case

A current topic that has surfaced among Public Transport Companies (PTCs) is the selection of alternative fuels for their bus fleets. Both European and Italian regulations are pushing toward abandoning diesel fuel and the consolidation of alternative traction power sources, such as battery-electric vehicles, fuel-cell electric vehicles, and hydrogen-electric vehicles. The literature has provided some approaches toward assessing this selection such as multicriteria-decision-methods in some countries in the world. However, not enough specific attention has been paid to cost criteria, experts involved, and the type of service required. This paper intends to address these gaps by applying an integrated method, which includes: (i) the Analytical Hierarchy Process (AHP) to define the weights of criteria; (ii) the ELimination Et Choix Traduisant la REalitè I (ELECTRE I) to find a good compromise solution among the fuel alternatives and (iii) a simple Weighted Sum Model (WSM) to refine ranking. This integrated method was applied in Italy involving a panel of experts from whom the data was collected. Different fuel alternatives for both urban and interurban services and with and without funding are discussed. The results provide a useful tool supporting PTC policies, which aims to rationalise and prioritise bus fuel alternatives when deciding on fleet renewal.

Subdivision Schemes Based on Weighted Local Polynomial Regression: A New Technique for the Convergence Analysis

The generation of curves and surfaces from given data is a well-known problem in Computer-Aided Design that can be approached using subdivision schemes. They are powerful tools that allow obtaining new data from the initial one by means of simple calculations. However, in some applications, the collected data are given with noise and most of schemes are not adequate to process them. In this paper, we present new families of binary univariate linear subdivision schemes using weighted local polynomial regression which are suitable for noisy data. We study their properties, such as convergence, monotonicity, polynomial reproduction and approximation and denoising capabilities. We establish conditions that connect the weight function with two essential properties: noise elimination and approximation capability. We propose a multi-objective optimization problem for improving these two capabilities and conclude that only some weight functions are Pareto optimal. For the convergence study, we develop some new theoretical results. Finally, some examples are presented to confirm the proven properties.

An improved stochastic car-following model considering the complete state information of multiple preceding vehicles under connected vehicles environment

Studying the car-following model contributes to improving vehicle driving efficiency and traffic flow stability within the context of connected automated vehicles (CAVs). Therefore, an improved stochastic car-following model (SMLVM) is proposed in this paper, building upon the traditional FVD model and BLVD model. This new model comprehensively considers four deterministic factors: acceleration, velocity, headway, and optimal speed memory of multiple preceding vehicles, as well as the comprehensive influence of stochastic factors on car-following behavior during the traveling process. Meanwhile, weight functions are utilized to represent the varying strengths of influence from vehicles ahead with different positions and speeds on the following vehicle. The SMLVM model is categorized and discussed based on practical application scenarios in this paper. When the focus is primarily on fundamental traffic flow behavior, relative motion between vehicles, and other basic principles, the SMLVM model degenerates into the MLVM model. Through stability analysis and simulation experiments on MLVM model, critical stability conditions are derived. Comparisons with other classical models demonstrate that the MLVM model exhibits stronger stability and resistance to disturbances. When the focus is primarily on various realistic driving scenarios, through simulation experiments on SMLVM models in different scenarios, it is found that the influence of stochastic factors on SMLVM models mainly depends on the magnitude of the intensity of stochastic fluctuations, which is rarely affected by the specific functional expressions of the stochastic terms. Finally, empirical analysis is conducted by selecting five sets of processed data from the next-generation simulation (NGSIM) dataset. Based on parameter estimation using the SMLVM model, and a comparison is made with the FVD model and BLVD model. The results confirm that the model proposed in this paper fits vehicle speeds better and absorbs disturbances more effectively, and exhibiting greater stability in traffic flow.

Nonexistence results for a time-fractional biharmonic diffusion equation

We consider weak solutions of the nonlinear time-fractional biharmonic diffusion equation ∂tαu+∂tβu+uxxxx=h(t,x)|u|p\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\partial _{t}^{\\alpha }u+\\partial _{t}^{\\beta }u+u_{xxxx}=h(t,x)|u|^{p}$\\end{document} in (0,∞)×(0,1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$(0,\\infty )\ imes (0,1)$\\end{document} subject to the initial conditions u(0,x)=u0(x)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$u(0,x)=u_{0}(x)$\\end{document}, ut(0,x)=u1(x)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$u_{t}(0,x)=u_{1}(x)$\\end{document} and the Navier boundary conditions u(t,1)=uxx(t,1)=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$u(t,1)=u_{xx}(t,1)=0$\\end{document}, where α∈(0,1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\alpha \\in (0,1)$\\end{document}, β∈(1,2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\beta \\in (1,2)$\\end{document}, ∂tα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\partial _{t}^{\\alpha}$\\end{document} (resp. ∂tβ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\partial _{t}^{\\beta}$\\end{document}) is the fractional derivative of order α (resp. β) with respect to the time-variable in the Caputo sense, p>1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$p>1$\\end{document} and h is a measurable positive weight function. Using nonlinear capacity estimates specifically adapted to the fourth-order differential operator ∂4∂x4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\frac{\\partial ^{4}}{\\partial x^{4}}$\\end{document}, the domain, the initial conditions and the boundary condition, a general nonexistence result is established. Next, some special cases of weight functions h are discussed.

Carleman estimate and applications for a heat equation with multiple singularities

The goal of this article is the analyses of inverse source problem and null controllability for a heat equation with multipolar inverse-square potentials: ∑ j = 1 m μ j | x − x j | 2 , where x 1 , x 2 , … , x m are different points, defined in a bounded C 2 domain Ω ⊂ R n , and μ 1 , … , μ m are real constants. More precisely, we show that for any μ j ≤ ( n − 2 ) 2 4 , j = 1 , … , m , we can obtain a Lipschitz stability result in inverse source problems and we will show that the system is null controllable. Our proofs are mainly based on Carleman estimates, and due to multiple singularities, we give a new Carleman estimate by choosing an appropriate weight function.

Monascus red pigments alleviate high-fat and high-sugar diet-induced NAFLD in mice by modulating the gut microbiota and metabolites.

Monascus red pigments (MRP) may have benefits against NAFLD with an unclear mechanism. This study aimed to explore the protective effect of MRP supplementation against NAFLD through regulation of gut microbiota and metabolites. The C57BL/6 mice animals were randomly allocated into the normal diet (NC), HFHS diet-induced NAFLD model, and MRP intervention group fed with HFHS diet. Serum lipid profiles and liver function parameters were measured. Liver and colon histopathology analysis was conducted to determine the injury in the liver and colon. 16S rRNA gene sequencing was employed to analyze gut microbial composition from fecal samples. Untargeted metabonomics was performed to analyze changes in metabolites in serum and fecal samples. MRP supplementation significantly improved the HFHS-induced alterations in body weight, lipid profiles, and liver function (p < .01). MRP supplementation decreased the abundance of Akkermansia, Candidatus saccharimonas, Dubosiella, and Oscillibacter, while increasing Lactobacillus, Lachnospiraceae NK4A136 group, and Rikenella in mice fed the HFHS diet. Furthermore, MRP supplementation improved the serum and fecal metabolic profiles induced by the HFHS diet, primarily involving the arachidonic acid metabolism, unsaturated fatty acid biosynthesis, and adipocyte lipolysis pathways. Liver function and lipid profiles were closely associated with the abundance of Lactobacillus, Streptococcus, Oscillibacter, Akkemansia, and Desulfovibrio (p < .01). These findings revealed that MRP supplementation may help restore gut microbiota composition and balance its metabolites, thereby improving NAFLD. This study presents a novel outlook on the potential benefits of MRP supplementation in ameliorating NAFLD and supports the application of MRP as a new functional food.

Analysis of functionally graded piezoelectric structures by Hermite interpolation element-free Galerkin method

Functionally graded piezoelectric structures (FGPSs) have excellent electromechanical properties and are promising for engineering applications. However, the inhomogeneous material properties and piezoelectric effects create great difficulties in the mechanical analysis of the FGPSs. In this paper, a Hermite interpolation element-free Galerkin method (HIEFGM) is proposed for the numerical analysis of the FGPSs. The HIEFGM utilizes a set of nodes to represent the problem domain, which can ideally reflect the inhomogeneous material properties of the FGPSs. Firstly, the governing equations of the FGPSs are derived through the constitutive equation, equilibrium equation, and boundary conditions. Secondly, the approximating function of the field quantities is obtained by the improved moving least-square method and Hermite interpolation. The HIEFGM formulation of the FGPSs is obtained using the variational principle. Furtherly, the influence of weight function, scaling parameter, and node densities on the HIEFGM of the FGPSs is discussed in detail through a parameter study. Finally, the availability of present method is estimated by several examples with different configurations and boundary conditions. The influence of gradation exponent on the electromechanical responses of the FGPSs is analyzed. The results show that the present method has excellent accuracy and stability in analyzing the FGPSs. As the gradation exponent increases, the distribution of the field quantities of the FGPSs exhibits nonlinear characteristics. This work may provide an effective methodology for the analysis of the FGPSs, and contribute to the theoretical research and engineering application of the FGPSs.

An improved GNSS ambiguity best integer equivariant estimation method with Laplacian distribution for urban low-cost RTK positioning

The integer least squares (ILS) estimation is commonly used for carrier phase ambiguity resolution (AR). More recently, the best integer equivariant (BIE) estimation has also attracted an attention for complex application scenarios, which exhibits higher reliability by a weighted fusion of integer candidates. However, traditional BIE estimation with Gaussian distribution (GBIE) faces challenges in fully utilizing the advantages of BIE for urban low-cost positioning, mainly due to the presence of outliers and unmodeled errors. To this end, an improved BIE estimation method with Laplacian distribution (LBIE) is proposed, and several key issues are discussed, including the weight function of LBIE, determination of the candidates included based on the OIA test, and derivation of the variance of LBIE solutions for reliability evaluation. The results show that the proposed LBIE method has the positioning accuracy similar to the BIE using multivariate t-distribution (TBIE), and significantly outperforms the ILS-PAR and GBIE methods. In an urban expressway test with a Huawei Mate40 smartphone, the LBIE method has positioning errors of less than 0.5 m in three directions and obtains over 50% improvements compared to the ILS-PAR and GBIE methods. In an urban canyon test with a low-cost receiver STA8100 produced by STMicroelectronics, the positioning accuracy of LBIE in three directions is 0.112 m, 0.107 m, and 0.252 m, respectively, with improvements of 17.6%, 27.2%, and 26.1% compared to GBIE, and 23.3%, 28.2%, and 30.6% compared to ILS-PAR. Moreover, its computational time increases by 30–40% compared to ILS-PAR and is approximately half of that using TBIE.

An exploratory study on the ability of manganese to supplement rotenone neurotoxicity in rats

Parkinson’s disease (PD) is a complex disorder, primarily of idiopathic origin, with environmental stressors like rotenone and manganese linked to its development. This study explores their potential interaction and resulting neurotoxicity, aiming to understand how environmental factors contribute to PD. In an eight-day experiment, male Wistar rats weighing 280–300 g were subjected to rotenone, manganese, or a combination of both. Various parameters were assessed, including body weight, behavior, serum markers, tissue damage, protein levels (tyrosine hydroxylase, Dopamine- and cAMP-regulated neuronal phosphoprotein –DARPP-32-, and α-synuclein), and mitochondrial function. Manganese heightened rotenone’s impact on reducing food intake without causing kidney or liver dysfunction. However, the combined exposure intensified neurotoxicity, which was evident in augmented broken nuclei and decreased tyrosine hydroxylase and DARPP-32 levels in the striatum. While overall mitochondrial function was preserved, co-administration reduced complex IV activity in the midbrain and liver. In conclusion, our findings revealed a parallel toxic effect induced by rotenone and manganese. Notably, while these substances do not target the same dopaminergic regions, a notable escalation in toxicity is evident in the striatum, the brain region where their toxic effects converge. This study highlights the need for further exploration regarding the interaction of environmental factors and their possible impact on the etiology of PD.

An adaptive iterative reweighted filtering methodology for urban MLS dataset

ABSTRACT This study presents a novel filtering methodology for Mobile Laser Scanning (MLS) data using robust iterative reweighting. Initially, 3D point clouds are projected onto a 2D grid to create surfaces from the lowest points. Weights are assigned based on the Height Above Ground (HAG) of these points. Ground points are distinguished by applying a surface function to the dataset via iterative reweighting. Among the tested four robust weight functions, the Denmark and Beaton-Tukey functions outperformed others, achieving total error values of 2.30 and 2.32 across three test areas, respectively. This method efficiently filters MLS data, irrespective of ground point proportions.

Existence of positive weak solutions for stationary fractional Laplacian problem by using sub-super solutions

Abstract In this work, we establish a theorem concerning the extension of positive weak solutions for a stationary fractional Laplacian problem featuring weight functions that change sign. Additionally, we introduce novel conditions to ensure the existence of a positive solution for the given problem. These conditions are derived utilizing the approach of sub-super solutions, thereby extending and complementing existing results in the literature.