LD Model Research Articles

Detection of Construction and Demolition Illegal Waste Using Photointerpretation of DEM Models of LiDAR Data

Illegal waste is a global problem with negative impacts on human health and the environment. This article focuses on detection using remote sensing of sites of demolition and construction waste. We hypothesise that construction and demolition waste represent a human modification of terrain and, as a result, will be sensible to detection using visualisation models of terrain, specifically DEM (digital elevation model). To this effect, we start with a DEM of 0.25 m per pixel developed using data from the second iteration of the PNOA LiDAR project by the Spanish National Geographic Institute (IGN). We evaluate seven modelling tools of the Relief Visualisation Toolbox (RVT) for the visual detection of waste. The study area includes the city of Mérida (Extremadura, Spain). Our fieldwork identified 494 points of illegal waste in this area. These points were classified according to five categories in relation to land use, and we established a total of 14 areas with a surface area of 450 m by 450 m. Our results suggest that three of the seven models employed allow us to differentiate with clarity what is anthropic from the natural terrain and, in some scenarios, the location of construction and demolition waste. The LD model was the one with the best results, allowing an increase in the number of locations of illegal dumping of CDW in the study area.

An analytical model for solute transport in a large-strain aquitard affected by delayed drainage

This paper proposed a model for solute transport in a large-strain aquitard coupling effects of diffusion, adsorption, and consolidation processes. The analytical solutions describing the drawdown and solute transport in the aquitard were derived under the condition of variable drawdowns in adjacent confined aquifer. The breakthrough time (BTs) of solute transport in the large-strain aquitard (LD model) was analyzed, and compared with that of the rigid porous medium (ND model) before consolidation, and the equivalent rigid porous medium (NDf model) at end of the consolidation, respectively. Results reveal that greater Darcy flow velocity, stronger solute diffusivity, and weaker adsorption of soil particles result in shorter BTs of solute transport in the large-strain aquitard, and the impacts of specific storage and void ratio on the BTs are influenced by the adsorption of soil particles. Compared with the ND model, the delayed drainage accelerates solute transport with weak adsorption, while it has the opposite effect with strong adsorption. BTs predicted by the LD model is always smaller than that of the NDf model. It is also found that the larger leakage coefficient of the aquitard significantly enlarges the difference of BTs between the NDf and LD models (Δt), and the consolidation factor of the aquitard is positively correlated with the Δt. The ratio of Δt over the BTs of the LD model has a linear positive relationship with the average cumulative water release of the per unit volume aquitard under the fixed drawdown in the adjacent confined aquifer.

Çelik Levha Arıza Tespiti için Makine Öğrenimi Algoritmalarının Karşılaştırmalı Analizi

Metals are one of the most important building materials of modern times. Especially the production and metalworking process of flat metal sheets is very sensitive. Control of the manufacturing process affects not only the intermediate products but also the quality of final products. Early detection of defects on steel plate surfaces is an important task in industrial production. Process control and mistake detection have traditionally been done manually by experts. However, this method is not proper in terms of both time and cost. With the industrial revolution IR 4.0, machine learning (ML) techniques have been developed to solve fault detection problems in products. This study focuses on developing basic machine learning methods for the detection of six different error classes that may occur during production on steel surfaces. Five standard ML models: LD, KNN, DT, SVM, RF, and deep learning (DNN) model: one-dimensional DNN was developed for the classification problem. The UCI steel plate deformation data set was used as the experimental data set. Five performance criteria: Accuracy, Sensitivity, Specificity, Precision, and F1 value were used to determine the success of the methods. The success rates of LD, KNN, DT, SVM, RF and DNN classification methods were 90.136%, 91.7880%, 93.013%, 93.287%, 95.479%, 96.986%, respectively. The results show the significant impact of the machine learning approach on the steel plate fault diagnosis problem.

Estimating soil water retention curves from soil thermal conductivity measurements

The soil water retention curve represents the relationship between soil water content (θ) and matric potential (ψ). The van Genuchten (vG) model is commonly used to characterize the shape of a θ(ψ) curve. Based on the similarities between θ(ψ) curves and soil thermal conductivity (λ) versus θ curves, Lu and Dong proposed a unified conceptual λ(θ) model (LD model) for estimating λ(θ) curves from θ(ψ) curves. Their work makes it possible to relate the shapes of λ(θ) curves to θ(ψ) curves. In this study, we present an empirical approach to estimate the vG model parameter m from the LD model shape parameter p based on a model calibration with θ(ψ) and λ(θ) datasets obtained from 10 soils. The saturated water content θs and the vG model parameter α are estimated from selected soil properties (i.e., bulk density, particle density, particle size distribution and organic carbon content), and the residual water content θr is estimated from the LD model parameter θf. For model evaluation, the θ(ψ) curves of six soils were estimated from measured λ(θ) values and selected soil properties, and were compared to direct θ(ψ) measurements. The proposed method performed well with root mean square errors of estimated θ values ranging from 0.015 to 0.052 cm3 cm−3 and bias ranging from −0.009 to 0.040 cm3 cm−3. We conclude that the proposed method accurately estimates θ(ψ) curves from λ(θ) curves and selected soil properties.

Applicability of the low-dissipation model: Carnot-like heat engines under Newton's law of cooling.

We investigate the validity of using the low-dissipation model (LD model) to describe the maximum power regime of the endoreversible model under Newton's law of cooling. We find it valid only when the temperature difference of heat reservoirs (T_{h}-T_{c},T_{h}>T_{c}) is small. Thus the efficiency at maximum power derived from the LD model is valid to the first order of Carnot efficiency when describing endoreversible heat engines. We conclude that the LD model produces the Curzon-Ahlborn efficiency (η_{CA}=1-sqrt[T_{h}/T_{c}]) in the maximum power regime with no dependence on dissipation ratios.

Evaluating and improving heritability models using summary statistics.

There is currently much debate regarding the best model for how heritability varies across the genome. The authors of GCTA recommend the GCTA-LDMS-I model, the authors of LD Score Regression recommend the Baseline LD model, and we have recommended the LDAK model. Here we provide a statistical framework for assessing heritability models using summary statistics from genome-wide association studies. Based on 31 studies of complex human traits (average sample size 136,000), we show that the Baseline LD model is more realistic than other existing heritability models, but that it can be improved by incorporating features from the LDAK model. Our framework also provides a method for estimating the selection-related parameter α from summary statistics. We find strong evidence (P < 1 × 10-6) of negative genome-wide selection for traits, including height, systolic blood pressure and college education, and that the impact of selection is stronger inside functional categories, such as coding SNPs and promoter regions.

Comparative analysis of pork tenderness prediction using different optical scattering parameters

This study aimed at the assessment of pork tenderness using hyperspectral backscattering imaging technique. Backscattering images for 54 pork samples in the spectral range of 480–900 nm were characterized by 3-parameter Lorentzian distribution function (LD) and diffusion equation (DE), which represent a statistical model and a theoretical model respectively. Characteristic parameters spectra were obtained and employed to establish partial least squares regression (PLSR) models for the Warner-Bratzler Shear Force (WBSF) values of pork samples. By contrast, the results showed that LD function interpreted pork scattering profiles more accurately than DE model between 480 and 600 nm. The PLSR model based on two-LD parameter combinations (the asymptotic value a and the peak value b of the backscattering profile) gained the best prediction results, with correlation coefficient in the prediction set (Rp) of 0.902, root mean square error of prediction (RMSEP) of 5.218 N, indicating that hyperspectral backscattering imaging technique coupled with LD model is preferable for rapid and nondestructive evaluation of pork tenderness.

The effect of hydroxylated fatty acid-containing phospholipids in the remodeling of lipid membranes

The synthetic fatty acid 2-hydroxyoleic acid (2OHOA) is an antitumor drug that regulates membrane lipid composition and structure. An important effect of this drug is the restoration of sphingomyelin (SM) levels in cancer cell membranes, where the SM concentration is lower than in non-tumor cells. It is well known that free fatty acid concentration in cell membranes is lower than 5%, and that fatty acid excess is rapidly incorporated into phospholipids. In a recent work, we have considered the effect of free 2OHOA in model membranes in liquid ordered (Lo) and liquid disordered (Ld) phases, by using all-atom molecular dynamics. This study concerns membranes that are modified upon incorporation of 2OHOA into different phospholipids. 2OHOA-containing phospholipids have a permanent effect on lipid membranes, making a Ld membrane surface more compact and less hydrated, whereas the opposite effect is observed in Lo domains. Moreover, the hydroxyl group of fatty acid chains increases the propensity of Ld model membranes to form hexagonal or other non-lamellar structures. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.

Effect of Amphipathic HIV Fusion Inhibitor Peptides on POPC and POPC/Cholesterol Membrane Properties: A Molecular Simulation Study

T-20 and T-1249 fusion inhibitor peptides were shown to interact with 1-palmitoyl-2-oleyl-phosphatidylcholine (POPC) (liquid disordered, ld) and POPC/cholesterol (1:1) (POPC/Chol) (liquid ordered, lo) bilayers, and they do so to different extents. Although they both possess a tryptophan-rich domain (TRD), T-20 lacks a pocket binding domain (PBD), which is present in T-1249. It has been postulated that the PBD domain enhances FI interaction with HIV gp41 protein and with model membranes. Interaction of these fusion inhibitor peptides with both the cell membrane and the viral envelope membrane is important for function, i.e., inhibition of the fusion process. We address this problem with a molecular dynamics approach focusing on lipid properties, trying to ascertain the consequences and the differences in the interaction of T-20 and T-1249 with ld and lo model membranes. T-20 and T-1249 interactions with model membranes are shown to have measurable and different effects on bilayer structural and dynamical parameters. T-1249’s adsorption to the membrane surface has generally a stronger influence in the measured parameters. The presence of both binding domains in T-1249 appears to be paramount to its stronger interaction, and is shown to have a definite importance in membrane properties upon peptide adsorption.

Mitochondrial Colocalization with Ca2+ Release Sites is Crucial to Cardiac Metabolism

In cardiomyocyte subcellular structures, colocalization of mitochondria with Ca2+ release sites is implicated in regulation of cardiac energetics by facilitating Ca2+ influx into mitochondria to modulate the tricarboxylic acid (TCA) cycle. However, current experimental techniques limit detailed examination of this regulatory mechanism. Earlier, we developed a three-dimensional (3D) finite-element cardiomyocyte model featuring a subcellular structure that integrates excitation-contraction coupling and energy metabolism. Here, using this model, we examined the influence of distance between mitochondria and Ca2+ release sites by comparing a normal (50-nm) distance model and a large (200-nm) distance model (LD). The influence of distance was minimal under a low pacing rate (0.25 Hz), but under a higher pacing rate (2 Hz), lower levels of mitochondrial Ca2+ and NADH, elevated phosphate, and suppressed force generation became apparent in the LD model. Such differences became greater when functional impairments (reduced TCA cycle activity, uncoupling effect, and failing excitation-contraction coupling) were additionally imposed. We concluded that juxtaposition of the mitochondria and the Ca2+ release sites is crucial for rapid signal transmission to maintain cardiac-energy balance. The idealized 3D model of cardiac excitation-contraction and metabolism is a powerful tool to study cardiac energetics.

Superconducting fluctuation and infrared absorption of Cd-substituted Tl0.9Bi0.1Sr1.8Yb0.2Ca1−xCdxCu1.99Fe0.01O7−δ ceramics

Tl0.9Bi0.1Sr1.8Yb0.2Ca1−xCdxCu1.99Fe0.01O7−δ (x=0–0.4) ceramics were prepared using the conventional solid-state synthesis method to investigate the effects of Cd2+ substitutions on superconducting fluctuation behavior, SFB and structural properties of the Tl1212 derivatives. Electrical resistivity measurements showed all the samples exhibit metallic normal-state behavior with zero resistivity critical temperature, Tc zero increasing from 40.0K (x=0) to 76.4K (x=0.3) before decreasing to 74.8K (x=0.4) with increasing Cd2+. FTIR analysis in conjunction with XRD results indicates improved inter-plane coupling that is evidenced in the form of decreased c-axis length and softening of the apical oxygen mode when Cd concentration was increased. In order to study the effect of Cd substitutions on SFB, excess conductivity analysis above Tc was performed using the Aslamazov–Larkin, AL model in conjunction with the Lawrence–Doniach, LD model. The results showed cross-over between two-dimensional, 2D to three-dimensional, 3D SFB transition for all the samples (x=0.1–0.4) with decreasing temperature. The highest transition temperature, T2D–3D was observed at x=0.3 which showed both the longest coherence length, ξc(0) and the highest inter-plane coupling constant, J within the series. Our results suggest that the increase in J and lowering of anisotropy, γ resulted in enhancement of superconductivity in the compound.

Influence of Ce Substitution at Sr-Site on Superconducting Fluctuation Behavior and Infrared Absorption of Tl0.9Bi0.1Sr2−x Ce x Ca0.9Y0.1Cu1.99Fe0.01O7−δ (x=0–0.20) Ceramics

Ce substituted Tl0.9Bi0.1Sr2−xCexCa0.9Y0.1Cu1.99Fe0.01O7−δ (x=0–0.20) samples were synthesized to determine the effects of the higher valence ion substitution on superconductivity and structure of the Fe-doped Tl1212 derivatives. The normal state behavior for x=0 showed semiconductor-like behavior which gradually turned to metallic behavior with increasing Ce at x=0.05–0.15. However, further substitution of Ce for x>0.15 turned the normal state to insulating behavior. The zero critical temperature, Tc zero increased from 65.4 K (x=0.05) to 71.0 K (x=0.10), but slightly decreased for x>0.10 indicating the optimum value of average copper valence was achieved at x=0.10. Excess conductivity analysis using the Aslamazov Larkin, AL and Lawrence–Doniach, LD models revealed two-dimensional, 2D to three-dimensional, 3D transition of superconducting fluctuation behavior, SFB with the highest transition temperature, \(T_{\mathrm{2D}\mbox{-}\mathrm{3D}}\) at x=0.10. FTIR analysis in conjunction with XRD results showed softening of FeO2/CuO2 planar oxygen mode from 610.5 cm−1(x=0) to 605 cm−1(x=0.20) which is suggested to be related to possible increase of inter plane coupling, J and this is supported by computed results based on the LD model. The enhanced J increases superconducting coherence length along c-axis, ξc(0), and hence lowers anisotropy, γ resulting in enhanced superconducting properties.

The photophysics of a Rhodamine head labeled phospholipid in the identification and characterization of membrane lipid phases

The organization of lipids and proteins into domains in cell membranes is currently an established subject within biomembrane research. Fluorescent probes have been used to detect and characterize these membrane lateral heterogeneities. However, a comprehensive understanding of the link between the probes’ fluorescence features and membrane lateral organization can only be achieved if their photophysical properties are thoroughly defined. In this work, a systematic characterization of N-(lyssamine Rhodamine B sulfonyl)-1,2-dioleoyl-sn-3-phosphatidylehanolamine (Rhod-DOPE) absorption and fluorescence behavior in gel, liquid-ordered (lo) and liquid-disordered (ld) model membranes was performed. In agreement with a previous study, it was found that Rhod-DOPE fluorescence lifetimes present a strong sensitivity to lipid phases, becoming significantly shorter in lo membranes as the probe membrane concentration increases. The sensitivity of Rhod-DOPE absorption and fluorescence properties to the membrane phase was further explored. In particular, the fluorescence lifetime sensitivity was shown to be a consequence of the enhanced Rhod-DOPE fluorescence dynamic self-quenching, due to the formation of probe-rich membrane domains in these condensed phases that cannot be considered as typical probe aggregates, as excitonic interaction is not observed. The highly efficient dynamic self-quenching was shown to be specific to lo phases, pointing to an important effect of membrane dipole potential in this process. Altogether, this work establishes how to use Rhod-DOPE fluorescence properties in the study of membrane lipid lateral heterogeneities, in particular cholesterol-enriched lipid rafts.

Effects of stretching processing parameters on the mean elongation ratio and maximum spread ratio of heavy forgings

Heavy forgings are the essential parts of some nuclear, electrical power generation, rolling mill equipments. The rigid-viscoplastic finite element models (FEM) were established to study the effects of processing parameters (deformation degree, tool width ratio, blank width ratio, strain rate, friction, and forming temperature) on the mean elongation ratio and maximum spread ratio of heavy forgings during stretching process. A new formula (LD model) is proposed to predict the mean elongation ratio for stretched heavy forgings. The predicting capabilities of LD model were verified by experiments. Results show that: (1) The mean elongation ratio and maximum spread ratio increase with the increase of deformation degree; (2) When the tool width ratio is decreased, the mean elongation ratio increases and the maximum spread ratio decreases; (3) When the blank width ratio is increased, the mean elongation ratio increase and the maximum spread ratio decrease; (4) The mean elongation ratio is not affected by strain rate, friction, and forming temperature. However, the effects of these three process parameters on the maximum spread ratio of deformed block are significant; (5) There is a good agreement between the experimental results and predictions by LD model, which confirms that the proposed LD model is valid for the practical industrial productions.

Salmonella SPI-1-mediated neutrophil recruitment during enteric colitis is associated with reduction and alteration in intestinal microbiota

Gastrointestinal infections involve an interactive tripartite relationship between the invading pathogen, the host, and the host's resident intestinal microbiota. To characterize the host inflammatory response and microbiota alterations during enteric salmonellosis, C57BL/6 mice were pre-treated with a low dose of streptomycin (LD model) and then infected with S. Typhimurium strains, including mutants in the two Type III secretion systems, SPI-1 and SPI-2 (invAmut and ssaRmut, respectively). Cecal colonization and inflammation in the LD model were evaluated to assess infection success and progression, and compared to the traditional high dose (HD) model. Perturbations to the microbial community in the LD model were assessed via evaluation of total microbial numbers, the proportion of intestinal γ-Proteobacteria and tRFLP analysis. In the LD model, consistently high colonization by the parental strain (WT) and invAmut S. Typhimurium was associated with significant intestinal pathology. However, microbial community profiles were more similar both in numbers and composition between mice infected with the mutant strains, than with the WT strain. Consequently, significant infection-induced inflammation did not always produce similar microbiota perturbations. Large numbers of luminal neutrophils were observed in the ceca of WT-infected, but not in invAmut or ssaRmut infected mice. Neutrophils were thus implicated as a potential mediator of microbiota perturbations during WT enteric salmonellosis. These studies offer a new model of S. Typhimurium-induced intestinal disease that retains the three participants of the disease process and further defines the role of virulence factors, the host microbiota, and inflammation in S. Typhimurium-induced intestinal disease.

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Solvation effect on conformations of 1,2:dimethoxyethane: charge-dependent nonlinear response in implicit solvent models.

The physical content of and, in particular, the nonlinear contributions from the Langevin-Debye model are illustrated using two applications. First, we provide an improvement in the Langevin-Debye model currently used in some implicit solvent models for computer simulations of solvation free energies of small organic molecules, as well as of biomolecular folding and binding. The analysis is based on the implementation of a charge-dependent Langevin-Debye (qLD) model that is modified by subsequent corrections due to Onsager and Kirkwood. Second, the physical content of the model is elucidated by discussing the general treatment within the LD model of the self-energy of a charge submerged in a dielectric medium for three different limiting conditions and by considering the nonlinear response of the medium. The modified qLD model is used to refine an implicit solvent model (previously applied to protein dynamics). The predictions of the modified implicit solvent model are compared with those from explicit solvent molecular dynamics simulations for the equilibrium conformational populations of 1,2-dimethoxyethane (DME), which is the shortest ether molecule to reproduce the local conformational properties of polyethylene oxide, a polymer with tremendous technological importance and a wide variety of applications. Because the conformational population preferences of DME change dramatically upon solvation, DME is a good test case to validate our modified qLD model. The present analysis of the modified qLD model provides the motivation and tools for studying a wide variety of other interesting systems with heterogeneous dielectric properties and spatial anisotropy.

APPROACHES IN WIND FIELD MODELING AND AIR QUALITY MONITORING SYSTEMS

There is an increasing interest in the research of methods for measuring, calculation, prediction and estimation of the level of pollutant in ambient air. Wind velocity is a major actor in atmospheric pollutant dispersion, so, together with experimental techniqu es, theoretical wind field models, combined with ad equate interpolation methods, provide important tools for pollution assessment and air quality prediction. Th is paper firstly discusses some basic concepts of the variat ional analysis formalism, as a classic framework fo r wind field models over complex terrains. The discrete version of the variational wind field model in Cartesian co ordinates can be used for interpolation of measured data and prediction of pollutant transport dynamics. The str ucture of an extended air quality monitoring system, integrat ing measurement stations, workstations and wind fie ld model- based software applications, dedicated to construct ion of atmospheric parameters maps, is finally prop osed. INTRODUCTION AND MOTIVATION

The harmful effect of exercise on reducing taurine concentration in the tissues of rats treated with CCl4 administration.

We have previously reported that oral taurine administration reduced the frequency of painful muscle cramps in patients with liver cirrhosis, and that skeletal muscle taurine concentration was significantly decreased after exercise. The aim of this study was to examine taurine concentration in various tissues of a liver damaged with fibrosis (LD) in a rat model before and after exercise. Rats were divided into normal (NML) and LD groups. The LD group received CCl(4) injection for 10 weeks. Thereafter, both groups were divided into control (NML/CTL, LD/CTL) and exercise (NML/EX, LD/EX) groups, respectively. The rats in the EX groups were subjected to treadmill running. Plasma, liver, brain, heart, and skeletal muscle taurine concentration, as well as plasma and liver lipid peroxidase (LPO) concentration, were measured. The liver, brain, and skeletal muscle taurine concentration in the LD groups was significantly decreased compared to that in the respective NML groups. Furthermore, the taurine concentration in the heart and skeletal muscles in the LD/CTL group was significantly decreased post exercise. The respective plasma and liver LPO concentration in the LD groups was significantly increased compared to that in the corresponding NML group. Moreover, plasma LPO concentration in the LD/EX group was significantly higher than in the LD/CTL group. Tissue taurine concentration, particularly in skeletal muscle, was significantly decreased in the LD model rats induced by CCl(4) administration, and furthermore, the significantly decreased concentration, except for liver, was aggravated by exercise, even though at lower intensity.

Impulse response of a linear diffusion analogy model as a flood frequency probability density function

The impulse response of a linear convective-diffusion analogy (LD) model used for flow routing in open channels is proposed as a probability distribution for flood frequency analysis. The flood frequency model has two parameters, which are derived using the methods of moments and maximum likelihood. Also derived are errors in quantiles for these parameter estimation methods. The distribution shows that the two methods are equivalent in terms of producing mean values—the important property in case of unknown true distribution function. The flood frequency model is tested using annual peak discharges for the gauging sections of 39 Polish rivers where the average value of the ratio of the coefficient of skewness to the coefficient of variation equals about 2.52, a value closer to the ratio of the LD model than to the gamma or the lognormal model. The likelihood ratio indicates the preference of the LD over the lognormal for 27 out of 39 cases. It is found that the proposed flood frequency model represents flood frequency characteristics well (measured by the moment ratio) when the LD flood routing model is likely to be the best of all linear flow routing models.