One of the efficient data mining tools is density-based clustering, including the density grid-based clustering. However, a common drawback always existing in clusters made by the density grid-based method is the existence of weakly connected grids deriving mainly from noise. Appearing such an unwanted connection with a high frequency reduces the accuracy of the obtained cluster data space (CDS) and its application efficiency. Here, we present an essential improvement to overcome this problem. First, we describe a concept of the weak-connected grid cell (WCG) and present a fuzzy-type approximation to depict the density-based distribution of data points at grid nodes. Then, we propose a strategy of searching WCG for density grid-based clustering (SWCG-DGB) to set up a CDS, filter noise, and tune the created CDS. A buffer is deployed during this phase to collect border points and filter noise, which improves the computational time significantly, especially for noisy datasets. Results from numerical surveys reflected the compared efficiency of this method in clustering validity, including the accuracy of the number of clusters.

Using density functional theory (DFT), the density of states of NH4V3O8 (NVO) was analyzed pre and post-oxygen defects (Od) formation. The findings revealed a reduced bandgap in NVO after Od introduction, emphasizing the role of Od in enhancing conductivity of the material, thus improving its electrochemical attributes. Through the water bath method, both NVO and its oxygen-deficient counterpart, (NH4)2V10O25⸱8H2O (NVOd), were synthesized as potential cathode materials for aqueous zinc-ion batteries (AZIBs). Experimental outcomes resonated with DFT predictions, highlighting the beneficial role of oxygen defects in boosting electrical conductivity. Notably, the refined material displayed a remarkable capacity of 479.3 mAh g-1 at 0.1 A g-1, underscoring its promise for advanced energy storage solutions.

A detection system, modeled in a graph, uses "detectors" on a subset of vertices to uniquely identify an "intruder" at any vertex. We consider two types of detection systems: open-locating-dominating (OLD) sets and identifying codes (ICs). An OLD set gives each vertex a unique, non-empty open neighborhood of detectors, while an IC provides a unique, non-empty closed neighborhood of detectors. We explore their fault-tolerant variants: redundant OLD (RED:OLD) sets and redundant ICs (RED:ICs), which ensure that removing/disabling at most one detector guarantees the properties of OLD sets and ICs, respectively. This paper focuses on constructing optimal RED:OLD sets and RED:ICs on the infinite king's grid, and presents the proof for the bounds on their minimum densities; [3/10, 1/3] for RED:OLD sets and [3/11, 1/3] for RED:ICs.

The 6TiSCH protocol (IEEE 802.15.4e) is crucial for the Industrial Internet of Things (IIoT), utilizing a time-slotted channel hopping (TSCH) mode based on node distribution. In our experiment, we explored node position clustering and adjusted the capacity of existing cells in congested areas to understand traffic patterns and optimize cell selection for TSCH resource allocation, particularly in slot frames. Efficient cell allocation prevents packet loss, manages congestion, and enhances data transmission reliability. Node clustering increases cell usage efficiency and reduces communication latency between nodes, with each cell allocation tailored to its traffic needs through the sink node from the clustering result. We evaluated the clustering method using the K-means algorithm through experiments using the 6TiSCH simulator. Additionally, we considered using the routing protocol for low power and lossy networks (RPL) as a comparison, such as OF0 and MRHOF, as the objective function to assess clustering results and their impact on throughput and packet delivery. Our method significantly improved average performance metrics: under the OF0 routing protocol, we achieved a 30.01% latency reduction, 15.95% faster joining time, 8% higher packet delivery ratio, and 13.82% throughput increase. Similarly, with the MRHOF routing protocol, we observed a 12.34% improvement in packet delivery ratio, 21.06% latency reduction, 12.68% faster joining time, and 25.97% higher throughput speed.

The aerospace industry develops prognosis and health management algorithms to ensure better safety on board. Particularly for in-flight controls where jamming is dreaded. For that, vibration signals are monitored to predict future defect occurrences. However, time series are not labeled according to severity level, and the user can only assess the system health from the data mining procedure. To that extent, we developed a clustering algorithm using a deep neural network core. We encoded the time series into pictures to be feed into an artificially trained neural network: U-NET. From the segmented output, one-dimensional information on cluster frontiers is extracted and filtered without any parameter selection. Then, a kernel density estimation finally transforms the signal into an empirical density. Ultimately, a Gaussian mixture model extracts the latter independent components. The method empowered us to reveal different degrees of severity faults in the studied data, with their respective likelihood without prior knowledge. We compared it to state-of-the-art machine learning algorithms. However, internal clustering results evaluation for time series is an open question. As state-of-the-art indexes were not producing relevant results, we built a new indicator to fulfill this task. We applied the whole method to an actuator consisting of an induction machine linked to a ball screw. This study lays the groundwork for future training of diagnosis and prognosis structures in the health management framework.

Pavement friction plays a crucial role in ensuring the safety of road networks. Accurately assessing friction levels is vital for effective pavement maintenance and management strategies employed by state highway agencies. Traditionally, friction evaluations have been conducted on a case-by-case basis, focusing on specific road sections. However, this approach fails to provide a comprehensive assessment of friction conditions across the entire road network. This paper introduces a hybrid clustering algorithm, namely the combination of density-based spatial clustering of applications with noise (DBSCAN) and Gaussian mixture model (GMM), to perform pavement friction performance rating across a statewide road network. A large, safety-oriented dataset is first generated by integrating network friction and vehicle crash data based on the attributes contributing possibly to friction related crashes. One-, two-, and multi-dimensional clustering analyses, respectively, are then performed to rate pavement friction. The Chi-square test is further employed to validate and identify the practical ratings. It is shown that by effectively capturing the hidden, intricate patterns within the integrated, complex dataset and prioritizing friction-related safety attributes, the hybrid clustering algorithm can produce pavement friction ratings that align effectively with the current practices of the Indiana Department of Transportation (INDOT) in friction management.

Monitoring crown closure evolution using multi-temporal Light Detection and Ranging (LiDAR) surveys is a method that we expect to be increasingly adopted given the availability of LiDAR sensors and the accumulating survey archives. However, little attention was devoted to comparing crown closure estimates from independent surveys. Although survey parameters cannot be modified after the data collection, we speculate that the error associated to crown closure estimates comparison can be reduced by selecting optimal post-survey parameters. In this study, we compared crown closure estimates of three airborne LiDAR surveys from 2018 (40 pt/m²) used as a reference, and two lower-density surveys from 2016 (4.5 pt/m²) and 2018 (2 pt/m²). We studied the effect of the height threshold used to separate canopy points and the grid resolution, using skewness and variance of lagged difference of crown closure. Crown closure estimates using low height thresholds were more different across surveys, resulting in higher root mean squared error (RMSE), bias and more different variograms. Results show that optimal height threshold was 3 m and grid resolution was 25 m, although there was room for decision (RMSE of 7% and 5%, and bias of 4% and 0% for 2016 and 2018 low-density surveys).

Natural polluted insulator surfaces are always coated with various kinds of soluble constituents, and those constituents affect flashover performance differentially. Currently this fact is not considered either in laboratory experiments or field pollution degree measurements, causing the existing insulation selection method to be deficient. In this paper a systematical research on insulator flashover voltage gradient correction involving types of soluble pollution constituents was presented. Taking typical type glass insulator as the sample, its flashover tests polluted by typical soluble chemicals NaCl, NaNO₃, KNO₃, NH₄NO₃, MgSO₄, Ca(NO₃)₂ and CaSO₄ were carried out. Then the flashover gradient correction was made combining the flashover performance of each soluble constituent, the ESDD contribution of the seven constituents, as well as the saturation performance of CaSO₄. The correction was well verified with the flashover test results of insulator polluted by three types of soluble mixture. Research results indicate that the flashover gradient correction method proposed by this paper performs well in reducing the calculating error. It is recommended to carry out component measurements and flashover gradient correction to better select outdoor insulation configuration.

To generate a probability density function (PDF) for fitting probability distributions of real data, this study proposes a deep learning method which consists of two stages: (1) a training stage for estimating the cumulative distribution function (CDF) and (2) a performing stage for predicting the corresponding PDF. The CDFs of common probability distributions can be adopted as activation functions in the hidden layers of the proposed deep learning model for learning actual cumulative probabilities, and the differential equation of trained deep learning model can be used to estimate the PDF. To evaluate the proposed method, numerical experiments with single and mixed distributions are performed. The experimental results show that the values of both CDF and PDF can be precisely estimated by the proposed method.

Martensitic steels are used at a wide range of strength levels in environments which expose them to hydrogen or water vapor over a large range of partial pressures and temperatures. Hydrogen can cause catastrophic failures under many seemingly benign conditions. The effect of hydrogen on the dimension stability of high strength martensitic steels under such conditions has been poorly understood, and existing models do not seem to adequately account for it. Experiments were conducted to measure the variation in volume due to the uptake of hydrogen of such steels under near-ambient conditions, and the results were compared to theoretical estimates derived from the density of defects acting as hydrogen traps. Based on these results a new model for hydrogen embrittlement was developed. The hydrogen lattice dilation (HLD) model isolates volume expansion as a primary driver of hydrogen embrittlement. It provides and distinguishes two modes of failure acceleration: the fast, brittle, stress-intensity independent cracking under higher static crack loading, and a slower, highly stress-intensity dependent tearing mode at lower stress intensity. The relationship between the two is explained, as is how hydrogen absorption by defects accounts for the crack threshold and crack velocity of each.

When describing the tribological behaviour of technical surfaces, the need for full length scale microtopographic characterization often arises. The self-affine of surfaces and the characterization of self-affine by a fractal dimension and its implantation into tribological models are commonly used. The goal of our present work was to determine the frequency range of fractal behaviour of surfaces by analysing the microtopographic measurements of a brake plunger. We also wanted to know if the bifractal and multifractal behaviour can be detected in real machine parts. As a result, we developed a new methodology for determining the fractal range boundaries to separate the nano- and micro-roughness. In order to reach our goals, we used atomic force microscope (AFM) and stylus instrument to provide measurements in wide frequency range (19 nm - 3 mm). As a result of the power spectral density (PSD) based fractal evaluation, it was found that the examined surface could not be characterized by a single fractal dimension and that we developed a methodology for stopping the margin of validity of each fractal dimension, and we also developed a methodology for determining the limits of validity of certain fractal dimensions.

Multi-board electronic cases with high density and high power modules are widely used in industrial power supply management. With the improvement of case performance and miniaturization requirements, heat dissipation becomes one of the important factors to be considered in the design process. First,The existing small electronic thermal design methods focus on heat dissipation structure or heat source layout optimization,and ignores on-load test for modeling analysis. Second,The selected power module has on-load power consumption, resulting in relatively low calorific value and the effectiveness of thermal design cannot be verified. Third, The thermal lacks Intelligent monitoring and feedback control mechanism. In order to solve these problems, this paper designs a kind of heat dissipation case with intelligent temperature control based on high-power and high-density power supply array. Based on the extremely miniaturization design principle, we adopt the composite heat dissipation mode based on conduction and supplemented by forced air cooling . The case is made of magnesium and aluminum alloy with a perforated design. Finally, we compare and analyze with the existing cooling design. The results show that the case is smaller in volume, and the cooling performance parameters are slightly better than the existing case. Under the condition of high-density and high-power design, The output power of the whole system is not less than 10kw and the lowest packing-level density is not less than 47w/cm2 with high reliability, portability and practicability. It also provides technical support and prototype support for the standardized design of similar power arrays.

Deep eutectic solvents (DESs) are known as tunable solvents. It is possible to prepare ternary deep eutectic solvent (TDES) are used for desired purpose by selecting the suitable molar ratio and components of mixture. Therefore, four DESs and two TDESs were prepared in this work. DESs and TDESs were prepared with potassium carbonate (PC) as a hydrogen bond acceptor (HBA) and three hydrogen bond donors (HBDs) such as glycerol (GL), ethylene glycol (EG) and 2-amino-2methyl-1-3-propanediol (AMPD) known as a hindered amine (HA). Binary DESs were PC-GL with molar ratios 1:10 and 1:16 and PC-EG with the same molar ratios. TDES were prepared by adding AMPD in binary DESs such as PC-GL-AMPD 1:16:1 and PC-EG-AMPD 1:10:1. The experimental density and refractive index of all DESs and TDESs were measured at the temperature of 293.15 to 343.15 K with an interval of 5 K. The effect of temperature, molar ratio and alkyl chain length on the properties was investigated. The molar volumes and isobaric thermal expansion were calculated using experimental density data. The experimental refractive index data was used to derive the specific refraction, molar refraction, free molar volume, electronic polarization, polarizability constant and internal pressure at several temperatures.

Fuzzy Rule Interpolation (FRI) offers an innovative methodology for inferring outcomes from data points that match no established rules in a sparse fuzzy rule base. Generally, a traditional fuzzy rule-based system suffers from the inability to perform inference while facing an unmatched observation, given a sparse fuzzy rule base that is derived from insufficient data or inadequate human experience and that fails to cover parts of a specific problem domain. Fortunately, starting with a sparse rule base, Fuzzy Rule Interpolation (FRI) can help to formulate interpolated rules specifically in instances where observations fail to activate any existing rule. An interpolated rule gives a result called consequent, which is related to the unmatched observation so that the inference system will not fail to generate an outcome corresponding to the observation as the output. Conventionally, these interpolated rules will be discarded after obtaining outcomes. However, valuable information may be potentially embedded within those discarded rules addressing the limitation regarding the coverage of the original sparse knowledge space. Moreover, without exploiting the potential value of the interpolated rules, the fuzzy inference system based on a sparse rule base will never improve its efficiency and robustness in the long run. Therefore, this underscores the necessity for Dynamic Fuzzy Rule Interpolation (D-FRI), which aims to collate interpolated rules that cover particular knowledge spaces absent in the sparse rule base. Intuitively, those frequently appeared interpolated rules are considered valuable because future observations are more likely to hit the respective problem areas. Promoting selected interpolated rules to the sparse rule base can enhance the overall coverage of the knowledge space and increase the inference efficiency over time. This paper introduces a framework for Dynamic Fuzzy Rule Interpolation that integrates the widely used Transformation-based Fuzzy Rule Interpolation (T-FRI) with an effective form of clustering of interpolated results. Experimental findings validate the effectiveness of this approach.

Low-dimensional carbon-based (LDC) materials have attracted extensive research attentions in electrocatalysis because of their unique advantages such as structural diversity, low cost, and chemical tolerance. They have been widely used in a broad range of electrochemical reactions to relief environmental pollution and energy crisis. Typical examples include hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), carbon dioxide reduction reaction (CO₂RR), and nitrogen reduction reaction (NRR). Traditional “trial and error” strategies seriously slowed down the rational design of electrocatalysts for these important applications. Recent studies show that the combination of density functional theory (DFT) calculations and experimental research is capable of accurately predicting the structures of electrocatalysts, thus could reveal the catalytic mechanisms. Herein, current well-recognized collaboration methods of theory and practice are reviewed. The history of modern DFT, commonly used calculation methods, and basic functionals are briefly summarized. Special attention is paid to descriptors that are widely accepted as a bridge links the structure and activity, and the breakthroughs for high-volume accurate prediction of electrocatalysts. Importantly, correlating multiple descriptors are used to systematically describe the complicated interfacial electrocatalytic processes of LDC catalysts. In addition, machine learning and high-throughput simulations are crucial in assisting the discovery of new multiple descriptors and reaction mechanisms. This review will guide the further development of LDC electrocatalysts for extended applications from the aspect of DFT computations.

The electrochemical CO2 reduction reaction can lead to high value-added molecules production while helping decrease anthropogenic CO2 emissions. Copper can reduce CO2 to more than thirty different hydrocarbons and oxygenates, but it lacks the required selectivity. We present a computational investigation of the role of nano-structuring and alloying in Cu-based catalysts on the activity and selectivity of CO2 reduction to one-carbon products: carbon monoxide, formic acid, formaldehyde, methanol, and methane. The adsorption, activation, and conversion of CO2 were computed on monometallic and bimetallic (decorated and core-shell) 55-atom Cu-based clusters. The dopant metals considered were Ag, Cd, Pd, Pt, and Zn, located at different coordination sites. The relative binding strength of the intermediates at different applied potentials were used to identify the optimal catalyst for the selective CO2 conversion to one carbon products. It was discovered that single atom doping with Cd and Zn is optimal for the CO2 to carbon monoxide conversion. The core-shell models with Ag, Pd, and Pt provided higher selectivity for formic acid and formaldehyde. The Cu-Pt and Cu-Pd showed lowest overpotential for methane formation.

Osteoporosis is a common problem in orthopedic medicine, and it has become an important medical issue in orthopedics as Taiwan is gradually becoming an aging society. In the diagnosis of osteoporosis, the bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the main criterion for orthopedic diagnosis of osteoporosis, but due to the high cost of this equipment and the lower penetration rate of the equipment compared to the X-ray images, the problem of osteoporosis has not been effectively solved for many people who suffer from osteoporosis, however, at present, in clinical diagnosis, doctors are not yet able to accurately interpret X-ray images for osteoporosis manually, and must rely on the data obtained from DXA. In recent years, with the continuous development of artificial intelligence, especially in machine learning and deep learning, significant progress has been made in image recognition. Therefore, it is worthwhile to revisit whether it is possible to use a convolutional neural network model to read a hip X-ray image and then predict the patient's BMD. In this study, we proposed a hip X-ray image segmentation model and a hip X-ray image recognition classification model. First, we used the U-Net model as a framework to segment the femoral neck, greater trochanter, wards triangle, and the total hip in the hip X-ray images. We then performed image matting and data augmentation. Finally, we constructed a predictive model for osteoporosis using deep learning algorithms. In the segmentation experiments, we used intersection over union (IoU) as the evaluation metric for image segmentation, and both the U-Net and U-Net++ models achieved segmentation results greater than or equal to 0.5. In the classification experiments, using the T-score as the classification basis, the total hip using the DenseNet121 model has the highest accuracy of 74%.

One ambitious objective of Integrated Computational Materials Engineering (ICME) is to shorten the materials development cycle by using computational materials simulation techniques at different length scales. In this regard, the most important aspects are the prediction of the microstructural evolution during material processing and the understanding of the contributions of microstructural features to the mechanical response of the materials. One possible solution to such a challenge is to apply the Phase Field (PF) method because it can predict the microstructural evolution under the influence of different internal or external stimuli, including deformation. To accomplish this, it is necessary to take into account plasticity or, specifically, non-homogeneous plastic deformation, which is particularly important for investigating the size effects in materials emerging at the micron length scale. In this work, we present quasi-2D simulations of plastic deformation in a face centred cubic system in a finite strain formulation. Our model consists of dislocation-based strain gradient crystal plasticity implemented into a PF code. We apply this model to study the influence of grain size on the mechanical behavior of polycrystals, which includes dislocation storage and annihilation. Furthermore, the initial state of the material before deformation is also considered. The results show that a dislocation-based strain gradient crystal plasticity model can capture the Hall-Petch effect in many aspects. The model reproduced the correct functional dependence of the flow stress of the polycrystal on grain size without assigning any special properties to the grain boundaries. However, the predicted Hall-Petch coefficients are significantly smaller than those found typically in experiments. In any case, we found a good qualitative agreement between our findings and experimental results.

Fracture density, a critical parameter of unconventional reservoirs, can be used to evaluate potential of unconventional reservoirs and location of production wells. Many technologies, such as amplitude variation with offset and azimuth (AVOA) technology, vertical seismic profiling (VSP) technology, and multicomponent seismic technology, are generally used to predict fracture of reservoirs. they can qualitatively predict fracture by analyzing seismic attributes, including seismic wave amplitudes, seismic wave velocities, which are sensitive to fracture. However, it is important to quantitatively describe fracture of reservoirs. In this study, based on a double-layer model, the relationships between fracture density and the double-layer model’s physical parameters, such as velocity of fast shear-wave, velocity of slow shear-wave, and density, were established, and then a powerful quantitative prediction method for fracture density was proposed dramatically. Afterwards, the Hudson model for crack was used to test the applicability of the method. The result shown that the quantitative prediction method for fracture density can be applied suitable to the Hudson model for crack. Finally, the result of validation models indicated that the method can predict fracture density effective, in which absolute relative deviation (ARD) were less than 5% and root-mean-square error (RMSE) was 4.88×10-3.

The energy efficiency of grinding depends on the appropriate selection of cutting conditions, grinding wheel and workpiece material. Additionally, the estimation of specific energy consumption is a good indicator to control the energy consumed during the grinding process. Consequently, this study develops a model of material removal rate to estimate the specific energy consumption based on the measurement of active power consumed in a plane surface grinding of C45K with different thermal treatments and AISI 304. This model identifies and evaluates the power dissipated by sliding, ploughing and chip formation in a industrial-scale grinding process. Furthermore, the instantaneous positions of the abrasive grains during cutting are described to study the material removal rate. The estimation of specific chip formation energy is similar to that described by other authors in laboratory scale, which allows to validate the model and experiments. Finally, the results show that the energy consumed by sliding is the main phenomenon of energy dissipation in industrial-scale grinding process, where it is denoted that sliding energy by volume unity decreases as the depth of cut and speed of workpiece increase.

Defining integrals over volume element in curved spacetime together with the mass and energy densities within that region of spacetime is apparently equivalent to the given energy and mass of that body or particle. With this in mind equations involving energies and masses can be rewritten in terms of their densities and the integral over the curved space-time volume element. The idea find its place in quantum mechanical frameworks systematically accounting for the effect of spacetime volume structures and gravity on dynamics of quantum systems. This article briefly explores these concepts and runs through various frameworks and equations relevant to this idea including the quantum stress energy tensor, and expressing Schrodinger’s equation in ways that are tied to general relativity it also discusses the cosmological constant and the cosmological constant problem.

This manuscript critically reviews the design and delivery of spray-dried particles for the achievement of high total lung doses (TLD) with a portable dry powder inhaler. We introduce a new metric termed the product density, which is simply the TLD of a drug divided by the volume of the receptacle it is contained within. The product density is given by the product of three terms: the packing density (the mass of powder divided by the volume of the receptacle), the drug loading (the mass of drug divided by the mass of powder), and the aerosol performance (the TLD divided by the mass of drug). This manuscript discusses strategies for maximizing each of these terms. Spray drying at low drying rates with small amounts of a shell-forming excipient (low Peclet Number) leads to formation of higher density particles with high packing densities. This enables ultrahigh TLD (>100 mg of drug) to be achieved from a single receptacle. Emptying of powder from capsules is directly proportional to the mass of powder in the receptacle, requiring an inhaled volume of about 1 L for fill masses between 40 and 50 mg and up to 3.2 L for a fill mass of 150 mg.

Description of redox reactions is critically important for understanding and rational design of materials for electrochemical technologies including metal-ion batteries, catalytic surfaces, or redox-flow cells. Most of these technologies utilize redox-active transition metal compounds due to their rich chemistry and their beneficial physical and chemical properties for these types of applications. A century since its introduction, the concept of formal oxidation states (FOS) is still widely used for rationalization of the mechanisms of redox reactions, but there exists a well-documented discrepancy between FOS and the electron density-derived charge states of transition metal ions in their bulk and molecular compounds. We summarize our findings and those of others which suggest that density-driven descriptors are in certain cases better suited to characterize the mechanism of redox reactions, especially when anion redox is involved, which is the blind spot of the FOS ansatz.

As the largest carbon pool on Earth, forest ecosystems are essential to maintaining carbon sink balance. However, accurately estimating the carbon sequestration and carbon storage of forest resources remains an urgent issue to address. Plot investigation, model estimation, and machine learning are examples of current approaches. Nevertheless, because of variables such as regional characteristics and plot size, large-scale and extensive region estimates are comparatively scarce. This study, which focuses on Tianzhu County, aims to comprehensively analyze and estimate the Net Primary Productivity (NPP), carbon storage, and carbon density of the forest ecosystem in this area by integrating data from forest resource inventory and the CASA model. The main conclusions are as follows: (1) The main vegetation types in Tianzhu County include coniferous forests, broad-leaved forests, mixed forests, and shrub forests; (2) Accordin g to the CASA model calculations, the annual cumulative NPP in Tianzhu County in 2020 ranges from a maximum of 249.63 gC/m² to a minimum of 3.40 gC/m², with the forest NPP amounting to 134,674.65 tons of carbon. Based on MODIS observation data, the forest’s NPP is 171,728.32 tons of carbon, with a maximum of 325.36 gC/m² and a minimum of 0.02 gC/m²; (3) At the pixel scale, the carbon storage of forests in Tianzhu County is 361,700 tons. Specifically, 46,500 tons of carbon are stored in coniferous forests, 1,100 tons in broad-leaved forests, 500 tons in mixed forests, and 313,600 tons in shrub forests.

Recently, federated learning (FL) has been receiving great attention as an effective machine learning method to avoid the security issue in raw data collection as well as to distribute the computing load to edge devices. However, even though wireless communications is a essential part for implementing FL in edge networks, there have been a few works that analyze the effect of wireless networks on FL. In this paper, we investigate FL in small-cell networks where multiple base stations (BSs) and users are located according to homogeneous Poisson point process (PPP) with different densities. We comprehensively analyze the effects of geographic node deployment on the model aggregation in FL on the basis of stochastic geometry-based analysis. We derive the closed-form expressions of coverage probability with tractable approximations and discuss the minimum required BS density for achieving a target model aggregation rate in small-cell networks. Our analysis and simulation results provide insightful information for understanding the behaviors of FL in small-cell networks, and it can be exploited as a guideline for designing the network facilitating the wireless FL.

Understanding the ionic channel network of proton exchange membranes, which dictate fuel cell performance, is crucial when developing proton exchange membrane fuel cells. However, itis difficult to characterize due to complicated nano structure and differing changes to their structure with different amounts of water uptake. Electrostatic force microscopy (EFM) can map surface charge distribution as nano special resolution by measuring the electrostatic force between a vibrating conductive tip and a charged surface under an applied voltage, . In this study, the ionic channel network of a proton exchange membrane is analyzed using EFM. A mathematical approximation model of the ionic channel network is first derived, to explain changes in force gradient on the surface using EFM. The phase lag of dry and wet Nafion under stepwise changes to bias voltage is then measured. Based on the model, variations in the ionic channel network of Nafion with different amounts of water uptake are analyzed numerically. The mean surface charge density of both membranes, which is connected with the ionic channel network, is calculated using the model. The results show that the difference between the mean surface charge of the dry and wet membranes is consistent with the variation in their proton conductivity.

Metal-supported fuel cells (MSCs) offer potential material cost and robustness advantage over anode supported cells (ASCs). Because of the very good thermal shock stability of such MSCs, these can be heated up very quickly. However the challenge co-firing of metal substrate and electrolyte stays still unsolved. The production of the core component, the tape casted metal substrate, with defined shrinkage resulting from modification of metal powders is presented in the paper. This approach leads to an adjustment of the shrinkage mismatch during sintering, between metal and ceramic components, and adjustment of target specifications like porosity, green density and layer thickness.

The endothelium plays a key role in blood vessel health. At the interface of the blood, it releases several mediators that regulate local processes and that protect against the development of cardiovascular disease. In this interplay, there is increasing evidence for a role of extracellular nucleotides and endothelial purinergic P2Y receptors (P2Y-R) in vascular protection. Recent advances have revealed that endothelial P2Y1-R and P2Y2-R mediate nitric oxide-dependent vasorelaxation as well as endothelial cell proliferation and migration, which are processes involved in the regeneration of damaged endothelium. However, endothelial P2Y2-R, and possibly P2Y1-R, have also been reported to promote vascular inflammation and atheroma development in mouse models, with endothelial P2Y2-R also being described as promoting vascular remodeling and neointimal hyperplasia. Interestingly, at the interface with lipid metabolism, P2Y12-R has been found to trigger HDL transcytosis through endothelial cells, a process known to be protective against lipid deposition in the vascular wall. Better characterization of the role of purinergic P2Y-R and downstream signaling pathways in determination of the endothelial cell phenotype in healthy and pathological environments has clinical potential for the prevention and treatment of cardiovascular diseases.

Traditional discrimination techniques for Euler deconvolution use only the color spectrums of structural indexes, without considering the spatial distribution characteristics and inherent relationships among the Euler solutions to separate adjacent causative sources. In the present study, a new approach was developed for discriminating uncorrelated Euler solutions from coherent solutions based on the focusing levels indicated by the probability density distributions generated using multivariate kernel density estimations (KDE). A novel multiple coverage technique was proposed by using a series of different sized moving windows over gridded gravity data, which formed tight clusters of Euler solutions for different sized causative sources. The results of the probability density distributions were obtained using a 3-D KDE method for the Euler solution subsets {x, y, z} of synthetical models, and real data from a survey conducted in British Columbia (Canada) which had successfully established more credible and meaningful geological models when compared with three other subsets.

We construct a novel family of summation-integral type hybrid operators in terms of shape parameter $\alpha\in \lbrack 0,1]$ in this paper. Basic estimates, rate of convergence, and order of approximation are also studied using the Korovkin theorem and the modulus of smoothness. We investigate the local approximation findings for these sequences of positive linear operators utilising Peetre's K-functional, Lipschitz class, and second-order modulus of smoothness.

KThe promising possibility of organic photodetector (OPD) is emerging in the field of sensing applications for its tunable absorption range, flexibility, and large-scale fabrication abilities. In this work, we fabricated bulk heterojunction OPD with a device structure of glass/ITO/PEDOT:PSS/ P3HT:PC61BM/Al by spin coating process and characterized the dark and photocurrent at different applied bias conditions for red, green, and blue incident LED light. OPD photocurrent density exhibited up to 2.5–3 orders higher magnitude compared to the dark current density at -1 V bias while it increased up to 3–4 orders at zero bias conditions for red, green, and blue lights showing an increasing trend higher voltage applied in the negative direction. Different OPD inner periphery shapes, OPD to LED distance, and OPD area were also considered to bring the variation in OPD dark and photocurrent, which can affect the on/off ratio of the OPD–LED hybrid system and is a critical phenomenon for any sensing application.

Seawater density is an important physical property in oceanography that affects the accuracy of calculations such as gravity fields and tidal potentials, and the calibration of acoustic and optical oceanographic sensors. In related studies, constant density values are frequently used, which can introduce significant errors. Therefore, this study employs a basic convolutional neural network model to construct a comprehensive model showing the seawater density distribution across the globe. The model takes into account depth, latitude, longitude, and month as inputs. Numerous real seawater datasets were used to train the model, and it has been shown that the model has an absolute mean error and root mean square error of less than 2 kg/m3 in 99% of the test set samples. The model effectively demonstrates the influence of input parameters on the distribution of seawater density. In this paper, we present a newly developed global model for distributing seawater density which is both comprehensive and accurate, surpassing previous models. The utilization of the model presented in this paper for estimating seawater density can minimize errors in theoretical ocean models and serve as a foundation for designing and analyzing ocean exploration systems.

This research investigates the effect of pre-soaking treatment on plant-based aggregate using a wet grout binder to formulate a high-strength lightweight concrete (HSLWC). The surface modification utilising a novel grout soaking technique with various water-to-cement (w/c) ratios indicated a new method of approach for the recent development of lightweight plant-based aggregate (LWPA). In this experiment, the fresh and hardened properties of modified LWPA lightweight concrete were assessed by verifying their workability, densities, compressive and split tensile strengths towards the modulus of elasticity. The results showed that pre-soaking plant-based lightweight aggregate (w/c: 0.6, 0.8, 1.0, and 1.2) slightly increased the density of the samples compared to untreated LWPA. The oven-dry density of treated and untreated LWPA is controlled in the range of HSLWC. The outcomes indicated that the workability of the surface- modified LWPA has significant improvement up to 40% in 6 min for (TDS)/0.6 sample compared to the original LWPA. The mechanical properties of the LWPA concrete with surface modification method exhibit substantial increment of compressive strength, split tensile strength, and modulus of elasticity were recorded at 22%, 26%, and 34%, respectively. Significantly, the findings from this scientific method revealed that the pre-soaking treatment method on LWPA has shown to be a highly recommended technique in improving interfacial bonding while performing as one of the most promising solutions to improve the properties of lightweight concrete.

In this paper a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered and the robustness is studied on the basis of a simulation study. Previously, the composite minimum density power divergence estimator is introduced and its asymptotic properties are studied.

Residual sugars (RS) in wine are the sugars that remain in a wine after fermentation is complete. In some wine styles, such as semi-dry wines, the accurate measurement of the RS concentration is critical for both qualitative and legislative reasons. Brix, measured by a simple refractometer, can give a good estimation of the RS concentration in the must, but during fermentation, the presence of alcohol leads to inaccurate sugar measurements. In order to measure the RS accurately, other more precise techniques are used, most of which are expensive or require professional skills. Therefore, novel approaches for rapid, easy, and practical measurements for estimating the sugar content were suggested over the years. However, most of these methods do not supply an actual measurement of RS but rather give brix values, and those that measure RS involve special equipment, which is less relevant for small wineries. This study suggests a novel model for predicting and controlling the wine's residual sugar. The data the model uses is the initial brix of the must before fermentation and its density during fermentation. The model was created by measuring actual residual sugars during the fermentation of natural and synthetic musts, with various degrees of initial brix levels, while simultaneously measuring their densities and correlating the two measurements. Linear regression between the residual sugar of the wine and its density was obtained for all treatments and repetitions (i.e., different values of must initial brix) with R² values above 0.97. Using the model, one can calculate (before commencing the fermentation) the density values at which the fermentation will reach a particular desired residual sugar value for a specific initial brix level; the model is applicable for the fermentation conditions used in this work, i.e., brix levels of 18-27˚Bx, Saccharomyces cerevisiae strains (fx-33 and fx-10) in common conditions of fermentation regarding temperature and aeration.

China's vast geographical and climatic diversity presents distinct challenges to its aviation industry, especially in understanding Density Altitude (DA). The study reveals a concentration of airports in the eastern and central regions due to socio-economic factors, while the west, shaped by the Tibetan Plateau, faces infrastructural constraints owing to geographical barriers and limited economic activity. Notable DA variations, particularly negative values in the northeast and discrepancies between DA and elevation in the south, underscore operational complexities. The prominent influence of humidity on DA, especially in the southern coast, prompts a reevaluation of conventional aviation practices. To address these challenges, there's a pressing need for specialized training, region-centric flight planning, comprehensive risk assessment, and increased awareness about humidity's impact on DA. As China's aviation sector expands, harnessing these insights is crucial for sustained operational excellence.

This letter attempts to clarify an issue regarding the proper definition of plastic dislocation density tensor. This study shows that the Ortiz’s and Berdichevsky’s plastic dislocation density tensor are equivalent with each other, but not with Kondo’s one. To fix the problem, we propose a modified version of Kondo’s plastic dislocation density tensor.

The main result of this work is the estimation of the entropy mode accompanying a wave disturbance, observed at the atmosphere heights range of 90-120km. The study is the direct continuation and development of recent results on diagnosis of the acoustic wave with the separation on direction of propagation. The estimation of the entropy mode contribution relies upon the measurements of the three dynamic variables (the temperature, density and vertical velocity perturbations) of the neutral atmosphere measured by the method of the resonant scattering of radio waves on the artificial periodic irregularities of the ionospheric plasma. The measurement of the atmosphere dynamic parameters has been carried out on the SURA heating facility. The mathematical foundation of the mode separation algorithm is based on the dynamic projecting operator technique. The operators are constructed via the eigenvectors of the coordinate evolution operator of the transformed system of balance equations of the hydro-thermodynamics.

In 1969, Jean-Marie Souriau introduced a “Lie Groups Thermodynamics” in Statistical Mechanics in the framework of Geometric Mechanics. This Souriau’s model considers the statistical mechanics of dynamic systems in their "space of evolution" associated to a homogeneous symplectic manifold by a Lagrange 2-form, and defines in case of non null cohomology (non equivariance of the coadjoint action on the moment map with appearance of an additional cocyle) a Gibbs density (of maximum entropy) that is covariant under the action of dynamic groups of physics (eg, Galileo's group in classical physics). Souriau Lie Group Thermodynamics was also addressed 30 years after Souriau by R. F. Streater in the framework of Quantum Physics by Information Geometry for some Lie algebras, but only in the case of null cohomology. Souriau method could then be applied on Lie Groups to define a covariant maximum entropy density by Kirillov representation theory. We will illustrate this method for homogeneous Siegel domains and more especially for Poincaré unit disk by considering SU(1,1) group coadjoint orbit and by using its Souriau’s moment map. For this case, the coadjoint action on moment map is equivariant. For non-null cohomology, we give the case of Lie group SE(2). Finally, we will propose a new geometric definition of Entropy that could be built as a generalized Casimir invariant function in coadjoint representation, and Massieu characteristic function, dual of Entropy by Legendre transform, as a generalized Casimir invariant function in adjoint representation, where Souriau cocycle is a measure of the lack of equivariance of the moment mapping.

Quantum nonlocality represents correlation properties between subsystems of a composite quantum system, usually including the four types: Bell nonlocality, steerability, entanglement, and quantum correlation (quantum discord). Given a basis $e_{AB}=\{|e_{ij}\>\}_{i\in[d_A],j\in[d_B]}$ for the Hilbert space $\H_A\otimes \H_B$ of a bipartite system $AB$, a density operator $\rho^{AB}$ (quantum state) of $AB$ can be represented as a $d_Ad_B\times d_Ad_B$ matrix $\hat{\rho}_{e_{AB}}=[\]$, called the density matrix of a density operator $\rho^{AB}$. A natural question is what is the relationship between the quantum nonlocality of a density operator $\rho^{AB}$ and its corresponding density matrix $\hat{\rho}_{e_{AB}}$? In this work, we discuss the relationships between quantum locality and basis, and prove that one type of quantum locality of density operators and that of their density matrices under a basis are the same if and only if the chosen basis is the tensor product of the bases of subsystems. Consequently, different bases define different quantum nonlocality density operators.

Obesity and overweight are associated with many metabolic diseases, such as hypertension, diabetes, and dyslipidemia, which are closely related to a sedentary lifestyle and lack of exercise. Aerobic exercise effectively increases the high-density lipoproteins-cholesterol (HDL-C) levels and decreases the triglyceride (TG) levels. The consumption of Cuban policosanol (Raydel®) is also effective in enhancing the HDL-C quantity and HDL functionality to treat dyslipidemia and hypertension. On the other hand, no study has examined the effects of a combination of high-intensity exercise and policosanol consumption in obese subjects to improve metabolic disorders. In the current study, 17 obese subjects (average BMI 30.0±1.1 kg/m2, eight male and nine female) were recruited to participate in a program combining exercise and policosanol (20 mg) consumption for 12 weeks. After completion, their BMI, waist circumference, total fat mass, systolic blood pressure (SBP), and diastolic blood pressure (DBP) decreased by approximately 15% (p=0.022), 12.7% (p=0.008), 33% (p=0.006), 11% (p<0.046), and 13% (p=0.007), respectively. In the serum lipid profile, at week 12, they showed a remarkable decrease in the total cholesterol (TC) and triglyceride (TG) levels, up to 17% (p<0.019) and 54% (p<0.002) from the baseline, respectively. Although the serum HDL-C was increased by approximately +12% from the baseline, the percentage of HDL-C in TC, HDL-C/TC (%), was increased by up to +32% (p=0.007) at week 12. The serum coenzyme Q10 (CoQ10) level was increased 1.2-fold in all participants at week 12 from the baseline. In particular, the male participants showed a 1.4-fold increase (p=0.027) from the baseline. The larger increase in serum CoQ10 was correlated with the larger increase in the serum HDL-C during 12 weeks. The hepatic function parameters were improved; the serum -glutamyl transferase decreased at week 12 by up to 55% (p<0.007), while the aspartate aminotransferase and alanine transaminase levels decreased within the normal range. In the lipoprotein level, the extent of oxidation and glycation were reduced significantly in VLDL and LDL, with a remarkable decrease in the TG content in particles. The antioxidant abilities of HDL2 and HDL3, such as paraoxonase (PON) and ferric ion reduction ability (FRA), were enhanced significantly by up to 1.8-fold (p<0.001) and 1.6-fold (p<0.001) at week 12. The particle size and number of HDL2 were increased up to +10% during the 12 weeks with a remarkable decrease in the TG content, glycation extent, oxidation up to 32% (p=0.032), 18% (p=0.043), and 11% (p=0.023), respectively. The particle number and diameter of HDL3 were increased by up to +9% with a remarkable increase in the PON activity, FRA activity, and TC content of +82% (p<0.001), +56% (p<0.001), and +32% (p=0.009), respectively. Expression of apolipoproteinA-I in HDL2 and HDL3 were significantly elevated more in both gender around 30~48% with more distinct band intensity and less glycation at week 12. These improvements in HDL quality and functionality were linked to the higher survivability of adult zebrafish and their embryos. Under the co-presence of carboxymethyllysine (CML), a microinjection of HDL2 to zebrafish embryo from week 0 resulted in approximately 47% survivability with developmental defects and attenuated speed. On the other hand, the HDL2 microinjection from week 12 resulted in remarkably higher survivability (~ 70%). In conclusion, 12 weeks of Cuban policosanol (Raydel®, 20 mg) consumption with high-intensity exercise showed significant improvement in blood pressure, body fat mass, blood lipid profile without liver damage, CoQ10 metabolism, and renal impairment. At week 12, all participants showed a remarkable decrease in oxidation and glycation extent in the VLDL and LDL with a decrease in the TC and TG content. Significant enhancement of the qualities and functionalities in HDL2 and HDL3 by the policosanol consumption were also detected: increase in apoA-I content, TC content, particle size, and particle numbers along with antioxidant abilities, such as PON and FRA.

For a dynamical system, it is known that the existence of a Lyapunov density implies almost global stability of an equilibrium. It is then natural to ask whether the existence of a common Lyapunov density for a nonlinear switched system implies almost global stability, in the same way as a common Lyapunov function implies global stability for nonlinear switched systems. In this work, the answer to this question is shown to be affirmative as long as switchings satisfy a dwell-time constraint with an arbitrarily small dwell time. As a straightforward extension of this result, we employ multiple Lyapunov densities in analogy with the role of multiple Lyapunov functions for the global stability of switched systems. This gives rise to a minimum dwell time estimate to ensure almost global stability of nonlinear switched systems, when a common Lyapunov density does not exist. The results obtained for continuous-time switched systems are based on some sufficient conditions for the almost global stability of discrete-time non-autonomous systems. These conditions are obtained using the duality between Frobenius-Perron operator and Koopman operator.

Iterative Stochastic decoding is an alternative to standard fixed-point decoding of Low-density parity check codes (LDPC) to reduce inter-node routing. In this paper, we propose a Flexible Field-Programmable Gate Array (FPGA)-Based Stochastic decoding (SD) hardware architecture for LDPC codes in the Fifth-Generation (5G) New Radio (NR) Standard that supports decoding of set of various code rates. This decoder’s runtime flexibility is desirable to switch a better performing code rate automatically based on the channel conditions without the extra time needed for reprogramming of FPGA. An offline design method is implemented to generate the hardware description language (HDL) code description of the decoder for the required code-rate set, which is further synthesized and integrated into the Xilinx Kintex-7 series FPGA board to determine the hardware resource utilisation and processing throughput. The Synopsys design tools were employed during both the simulation and synthesis stages, in combination with TSMC 65-nm CMOS standard cell technology, to facilitate comparative analysis. Compared with state-of-the-art designs, the proposed architecture reduces hardware utilization by up to 26% and achieved energy efficiency by 52%.

The present paper contains data on the density (ρ), sound velocity (u), specific heat capacity (c_p ) of the mixture of N,N-dimethylformamide + 1-butanol (DMF + BuOH) determined in the entire concentration range of solution and in the temperature range: (293.15–318.15) K. The analysis of thermodynamic functions such as isobaric molar expansion, isentropic and isothermal molar compression, isobaric and isochoric molar heat capacity, as well as their excess functions (〖 E〗_(p,m)^E,〖 K〗_(S,m)^E,〖 K〗_(T,m)^E,〖 C〗_"p,m" ^E,〖 C〗_"V,m" ^E) and also V_m^E was undertaken. The analysis of changes in the physicochemical quantities was based on consideration of the system in an aspect of intermolecular interactions with resulting changes in the mixture structure. The results available in the literature are confusing during the analysis and became the reason for our decision to thoroughly examine the system. What is more, for a system whose components are widely used, there is no information in the literature regarding the heat capacity of the tested mixture, which was also achieved and presented in this publication. The conclusions drawn from so many data allow us to approximate and understand the changes that occur in the structure of the system due to repeatability and consistency of the obtained results

In the present work, we report on a 3D MOF of {[Pb5(3-OH)(3-NO3)3(6-pmdc)3·H2O}n formula (pmdc = pyrimidine-4,6-dicarboxylate) synthesized by an oven-heated solvent-free procedure. The large connectivity afforded by the three ligands in their coordination to lead(II) ions grows cubic building units characterized by a central Pb atom with an unusual coordination index of 12 and six pmdc ligands occupying the faces. These cubic units are linked one another giving rise to a quite condensed structure that represents an unprecedented topology showing the (4.62)6(43)2(45.610)3(45.68.82)6(46.69)6(612.83) point symbol. The crystalline material has been characterized by routine physico-chemical techniques to confirm its purity and its thermal behaviour has been also studied by thermogravimetric and thermodiffractometric analyses. The solid presents greenish blue photoluminescent emission based on pmdc ligands, as revealed time-dependent density-functional theory (TD-DFT) calculations, by that is substantially more intense than in free H2pmdc ligand according to its improved quantum yield. The emissive capacity of the material is further analysed according to decreasing temperature of the polycrystalline sample, finding that sizeable long-lasting phosphorescence is present.

In the Formula Student Racing Car, the anti-deformation ability of the frame will affect the four-wheel positioning parameters of the racing car, and then affect the handling and stability performance of the racing car. The quality of the frame directly determines the power and economy of the racing car, so the performance of the frame is very important to the performance of the race. In order to improve the performance of the frame and reduce the total weight of the frame, the research on the lightweight design of the frame is particularly important. In this paper, based on the variable density method, the global topology optimization of the frame is carried out to obtain the distribution of the frame material, realize the efficient use of the material, and improve the torsional stiffness of the frame. Based on the adjoint variable method, the sensitivity analysis of the frame is carried out. According to the sensitivity analysis results, the size of the frame is optimized. The total mass of the frame is reduced by 12.8 %, and the performance of the maximum displacement and maximum stress is improved. The lightweight design of the frame is realized as a whole.

The petroleum industry produces thousands of barrels of oilfield waters from the initial stage driven by primary production mechanisms to the tertiary stage. These produced waters contain measurable amounts of oil in water emulsions, the exact amounts being determined by the chemistry of the crude oil. To meet strict environmental regulations governing the disposal of such produced waters, demulsification to regulatory permissible levels is required. Within the electric double layer theory, coupled with the analytical solutions to the Poisson Boltzmann Equation, continuum electrostatics approaches can be used to describe the static and electrokinetic properties of such emulsion systems. Therefore, theoretical understanding of the stability of oil in water emulsions within such fundamental concepts provides reliable approaches to demulsification. In this paper, we have used theoretical approaches, based on zeta potential and surface charge density models to determine the stability of oil in water emulsions for different crude oil samples. Accordingly, we have used literature based data on the chemistry of the crude oils, and have ranked the order of emulsion stability based on criterial established by zeta potential plots for the oil. Our theoretical calculations show that where the isoelectric points of crude oil samples are closer to each other, the degree of ionization plots versus pH indicate close tends for salinities at varying pH of oilfield waters. Based on the chemistry of crude oil samples, the most efficient and cost-effective means of demulsification is by reducing produced water pH to values closer to the average point of zero charge pH values

Within the context of sustainable material development for the construction sector, this study explores the viability of panels composed of recycled newspaper-derived cellulose (9%), rice husk (14%), borax (15%), and polyvinyl acetate-based glue (62%). The methods employed involve water absorption and density tests, following ASTM C-1763 and C-303 standards. The fire resistance test conforming to the European standard UNE 23-725-90, and a mold growth test using AOAC 2002.11. The composite is prone to absorbing a significant amount of water when exposed to humid conditions. However, the incorporation of rice husk and borax can provide benefits such as improved moisture resistance compared to other cellulitic insulators, which may be advantageous in specific climates. Also, the developed composite has an intermediate density compared to other polymeric materials. This characteristic presents advantages in applications that demand a balance between strength and lightness. During the fire resistance tests, the samples with borax presented less fire propagation, and superficial damage compared with the specimens without borax. This is important, considering the fireproofing property, required in building materials. The presence of borax in the composite has an inhibitory effect on the growth of fungi and yeasts. These findings are consistent with previous research. Nevertheless, further research and testing are imperative to assess its viability and performance for commercial applications.

For traffic management under sudden disaster in high-density areas, the first and foremost step is to prevent traffic congestion in the disaster-affected area by traffic flow control, as to provide enough and flexible traffic capacity for emergency evacuation and emergency rescue. Catastrophe border identification is the foundation and the key to traffic congestion prediction under sudden disaster. This paper uses a mathematical model to study the regional traffic flow in the high-density area under sudden fire disaster based on the Cusp Catastrophe Theory (CCT). The catastrophe border is identified by fitting the CCT-based regional traffic flow model to explore the stable traffic flow changing to the instable state, as to provide a theoretical basis for traffic flow manage and control in disaster-affected areas, and to prevent the traffic flow being caught into disorder and congestion. Based on VISSIM simulator data by building simulation scenarios with and without sudden fire disaster in a Sudoku traffic network, the catastrophe border is identified as 439pcu/lane/h, 529pcu/lane/h, 377pcu/lane/h at 5s, 10s, 15s data collection interval respectively. The corresponding relative precision, which compares to the method of Capacity Assessment Approach (CAA), is 89.1%, 92.7% and 76.5% respectively. It means that 10s data collection interval would be the suitable data collection interval in catastrophe border identification and regional traffic flow control in high-density area under sudden fire disaster.

This paper considers a nonlinear model for population dynamics with age structure. The fertility rate with respect to age is non constant and has the form proposed by . Moreover, its multiplicative structure and the multiplicative structure of mortality makes the model separable. In this setting it is shown that the number of births in unit time is given by a system of nonlinear ordinary differential equations. The steady state solution together with the equilibrium solution is found explicitly.

Normally, the Nernst voltage calculated from the concentration of the reaction gas in the flow channel is considered to be the ideal voltage (reversible voltage) of the oxyhydrogen fuel cell, but actually it will cause a concentration gradient when the reaction gas flows from the flow channel through the gas diffusion layer to the catalyst layer. The Nernst voltage loss in fuel cells in most of the current literature is thought to be due to the difference in concentration of reaction gas in the flow channel and concentration of reaction gas on the catalyst layer at the time when the high net current density is generated. Based on the Butler-Volmer equation in oxyhydrogen fuel cell, this paper demonstrates that the Nernst voltage loss is caused by the concentration difference of reaction gas in flow channel and on the catalytic layer at the time when equilibrium potential (Galvanic potential) of each electrode is generated.

Background Although high-density lipoprotein has cardioprotective effects, the association between serum high-density lipoprotein cholesterol (HDL-C) and hypertension is poorly understood. Objective We investigated whether low and high concentrations of HDL-C are associated with hypertension using a large healthcare dataset. Methods In a community-based cross-sectional study of 1,493,152 Japanese people aged 40–74 years who underwent a health checkup, blood pressures and clinical parameters, including nine HDL-C concentrations (20–110 mg/dL or over) were investigated. Results A crude U-shaped relationship was observed between the nine HDL-C concentrations and blood pressure in males (n = 830,669), while a left-to-right inverted J-shaped relationship was observed in females(n = 662,483). An age-adjusted logistic regression analysis showed J-shaped relationships (left-to-right inversion in females) between HDL-C and odds ratios for hypertension (≥140/90 mmHg), with lower limits of 60–79 mg/dL in males and 90–99 mg/dL in females, which were unchanged after adjusting for smoking, habitual exercise, alcohol consumption, and pharmacotherapy for hypertension, dyslipidemia, and diabetes. However, further adjustment for body mass index and serum triglyceride concentration revealed latent positive linear associations between HDL-C and hypertension, although the association between extremely high HDL-C (≥100 mg/dL) and hypertension was attenuated in non-alcohol drinkers. Conclusion Both low and extremely high HDL-C concentrations are associated with hypertension. The former association may be dependent on excess fat mass, which is often concomitant with low HDL-C, whereas the latter association may be dependent on frequent alcohol consumption.

Nowadays, bioeconomy and nanotechnology trends push food packaging sector in the re-placement of food additives by biobased antioxidant/antibacterial compounds and their inclusion in nanocarriers to control their release. Herein by following this trend, a rich in thymol-(TO) activated carbon (AC) nanostructure (TO@AC) was prepared and physiochemically characterized with various technics. This TO@AC nanostructure as well as pure AC were extruded with low density polyethylene (LDPE) to develop novel active packaging LDPE/TO@AC and LDPE/AC films. X-ray diffractometry, Fourier Transform Infrared Spectroscopy and Scanning Electron Microscopy measuraments shown high dispersity and capability of both AC and TO@AC in LDPE matrix which was resulted in enhanced tensile and water/oxygen barrier properties of obtained LDPE/AC and LDPE/TO@AC films. LDPE/TO@AC films shown higher elongation at break values and water/oxygen barrier than LDPE/AC films and significant antioxidant activity. TO release kinetics studies shown that by increasing TO@AC content the total TO amount released increased and the constant release rate decreased. Pork fillets wrapped with the optimum active film containing 15 wt.% TO@AC and succeed to prevent lipid oxidation and heme iron loss during storage. Estimation of microbial population of pork fillets shown that this active film could ex-tend the microbiological shelf-life of pork fillets by 2 days

Carbon supported nanoparticles of monometallic Ni catalyst and binary Ni-Transition Metal (Ni-TM/C) electrocatalytic composites were synthesized via chemical reduction method, where TM stands for the doping elements Fe, Co, and Cu. The chemical composition, structure and morphology of the Ni-TM/C materials were characterized by X-ray photoelectron spectroscopy (XPS), X-ray diffractometry (XRD), transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM) and energy-dispersive X-ray spectroscopy (EDS). The electrochemical properties towards hydrogen oxidation reaction in alkaline medium were studied using the rotating disc electrode and cycling voltammetry methods. A significant role of the TM dopant in the promotion of the hydrogen electrooxidation kinetics of the binary Ni-TM/C materials were revealed. A record-high in exchange current density value of 0.060 mA cm²_Ni was measured for Ni₃Fe₁/C, whereas the monometallic Ni/C counterpart has only shown 0.039 mA cm²_Ni. In order to predict the feasibility of the electrocatalysts for hydrogen chemisorption, density functional theory was applied to calculate the hydrogen binding energy and hydroxide binding energy values for bare Ni and Ni₃TM₁.

In veterinary medicine, the significance of High-Density Lipoprotein (HDL) measurements is not well-documented than it is in humans. The HDL level can be measured in dogs, and through referring to the normal range, it is possible to find out what this means for various endocrine diseases and hyperlipidemia diseases. Aim of this study is to measure the HDL levels in dogs with various conditions and to evaluate whether the Total Cholesterol (TC), HDL ratio is effective as a prognostic indicator in various hyperlipidemia and endocrine diseases. Through prospective clinical trial, sixteen client-owned dogs and cats visiting a local private practice were divided into three groups; five dogs without hyperlipidemia or metabolic disease (Group 1); eight animals with Cushing's, hypothyroidism, and gallbladder sludge (Group 2) and three diabetics, urinary disorders, and healthy cats (Group 3). In two dogs, the TC/HDL values were between 2 and 3; in two dogs, the values were between 3 and 4; in two dogs, the values were between 4 and 5. In three dogs, the TC/HDL values were between 5 and 6 and in three dogs, the ratio values were between 6 and 7. The other value was higher than 8. Except two dogs which showed lower value than 3, all dogs had concurrent endocrine disease including Cushing’s disease, hypothyroidism, gall bladder mucocele, hyperlipidemia. There was a difference in each group in terms of the TC/HDL value compared to the group with underlying disease. This means that TC/HDL values can be an excellent indicator of endocrine disease in dogs as well. In cats, although this is a very small sample, a high TC/HDL value of 9 points are shown in the cat which had diabetes mellitus. However, for more statistically significant results, a larger sample group for further investigation is needed.

We will demonstrate that the photon energy density parameter Ωγ of the universe can be derived exactly in Rh = ct cosmology. We find that it must be Ωγ = 1/5760π ≈ 5.52621330180192× 10^(−5). This indicates that there is no uncertainty in the radiation density within at least somesub-classes of Rh = ct cosmology.

Oxidative stress is one of the primary instigators of the onset of various human ailments, including cancers, cardiovascular diseases, and dementia. Particularly, oxidative stress has a severe effect on low-density lipoprotein (LDL) oxidation, leading to several detrimental health effects. Thereof, in this study, the effect of beeswax alcohol (BWA) was evaluated to prevent LDL oxidation, enhancement of paraoxonase 1 (PON-1) activity of high-density lipoprotein (HDL), and zebrafish embryo survivability. Furthermore, the implication of BWA consumption on the oxidative plasma variables was assessed by a preliminary clinical study on middle and older human subjects (n=50). Results support BWA augmentation of PON-1 activity in a dose-dependent manner (10-30 μM), which was significantly better them the effect exerted by coenzyme Q10 (CoQ10). Moreover, BWA significantly curtails CuSO4 (final 0.5 μM) evoked LDL/apo-B oxidation and a marked reduction of lipid peroxidation in LDL. The transmission electron microscopy (TEM) analysis revealed a healing effect of BWA towards the restoration of LDL morphology and size impaired by the exposure of Cu2+ ions (final 0.5 μM). Additionally, BWA counter carboxymethyllysine (CML, 500 ng) induced toxicity and rescued zebrafish embryos from development deformities and apoptotic cell death. A completely randomized, double-blind, placebo-controlled preliminary clinical study on middle and older-aged human subjects (n=50) exhibited that 12 weeks of BWA (100 mg/day) supplementation efficiently diminished serum malondialdehyde (MDA), total hydroperoxides, and enhanced total antioxidant status by 25%, 27%, and 22%, respectively, compared to the placebo control and baseline values. Furthermore, the consumption of BWA did not exhibit any noteworthy changes in anthropometric profile, lipid profile, glucose levels, and biomarkers pertinent to kidney and liver function, thus confirming the safety of BWA for consumption. Conclusively, BWA prevents LDL oxidation, enhances PON-1 activity in HDL, and has a positive impact on the oxidative variables of human subjects.

This paper presents a comprehensive evaluation of metal foam employment within polymer electrolyte fuel cells (PEFCs) and compares it with conventional serpentine channels from both experiment viewpoints and computational fluid dynamics simulation. The experiments are designed to study the effects of material, area density, compression ratio, and final thickness of metal foam. Additionally, the influence of housing plate material and relative humidity (RH) is also tested for the first time. The results reveal that at RH=75-100%, the best distributor design is nickel foam with a compression ratio of 70%, a final thickness of 0.5mm, and SS-304 housing plate, which delivers 3110 mA cm^-2 as limiting current density that is scarce in the literature. The PEFC with this foam distributor shows a 10% improvement in maximum power density and 45% in limiting current density compared to the serpentine channel case. While at RH=30%, the same foam flow field with a final thickness of 1mm is a superior option. The experiments also indicate that maximum power density increases by 23% as the compression ratio rises from 0 to 70%, while reducing final thickness from 1 to 0.5 mm causes a 19% enhancement in cell performance. Simulation results reveal that metal foam is more successful in evenly reactant distribution so that the average oxygen mass fraction at the cathode catalyst layer is increased by 38% in the metal foam case compared to the serpentine channel.

The intramolecular ionic Diel-Alder (IIDA) reactions of two dieniminiums have been studied within the Molecular Electron Density Theory (MEDT) at the B97XD/6-311G(d,p) computational level. ELF topological analysis of dieniminiums shows that its electronic structure can been seen as the sum of those of butadiene and ethaniminium. The superelectrophilic character of dieniminiums accounts for the high intramolecular global electron density transfer taking place between the diene and iminium frameworks at the transition state structures (TSs) of these IIDA reactions. The activation enthalpy associated to the IIDA reaction of the experimental dieniminium, 8.7 kcal·mol-1, is closer to that of the ionic Diels-Alder (I-DA) reaction between butadiene and ethaniminium, 9.3 kcal·mol-1. However, the activation Gibbs free energy of the IIDA reaction is 12.7 kcal·mol-1 lower than that of the intermolecular I-DA reaction. The strong exergonic character of the IIDA reaction, higher than 17 kcal·mol-1, makes the reaction irreversible. These IIDA reactions present a total re/exo and si/endo diastereoselectivity, which is controlled by the most favourable chair conformation of the tetramethylene chain. Electron localization function (ELF) topological analysis of the single bond formation indicates that these IIDA reactions take place through a non-concerted two-stage one-step mechanism. Finally, ELF and atoms-in-molecules (AIM) topological analyses of the TS associated to inter and intramolecular processes show the great similitude among them.

Materials design for processing and application requires fundamental understanding of their properties based interatomic interaction. The use of the novel concept of total bond order density (TBOD) as a single quantum mechanical metric to characterize the internal cohesion of a crystal and correlate with the calculated physical properties is particularly appealing. This requires detailed first-principles calculation of the electronic structure, interatomic bonding and related properties. In this article, we use this new concept and apply it to chalcogenide crystals based on data obtained from 25 crystals: Ag₂S, Ag₂Se, Ag₂Te, As₂S₃, As₂Se₃, As₂Te₃, As₄Se₄, Cu₂S, Cu₂Se, Cu₂Te, Cu₄GeS₄, Cu₂SnS₃, Cu₂SnSe₃, GeS₂, GeSe₂, Ge₄Se₉, Sb₂S₃, Sb₂Se₃, Sb₂Te₃, SnS, SnSe, CdSe, CdTe, ZnSe, and ZnTe. Together with the calculated optical and mechanical properties, we demonstrate the efficacy of using this novel approach for materials design that could facilitate the exploration and development of new chalcogenide crystals and glasses. Moreover, the TBOD and its partial components (PBOD) could be the key descriptors in machine learning protocol for broader scale design when a large database is available.

Background: Several preventive strategies to reduce dyslipidaemia, have been suggested of which dietary modification features as an important one. Addition of almonds in our daily diets has been proposed to beneficially impact the lipid profile. This review critically examines the available evidence assessing the effect of almonds on dyslipidaemia in the South Asian (particularly Indian) context. Methods: An extensive review comprising of epidemiological studies, clinical trials, meta-analyses and systematic reviews was conducted from published literature from across the world. Studies examining the effect of almonds on different aspects of dyslipidaemia viz. high LDL-C, low HDL-C, triglyceridaemia, high total cholesterol levels have been included. Results: Dyslipidaemia is a major risk factor for coronary heart disease and strategies to manage dyslipidaemia have been shown to reduce the incidence of CVD. Although there are proven pharmacological therapies to help manage this condition, there are not many nutritional interventions which can impact dyslipidaemia. Almonds have been shown to reduce LDL-C which is a known risk factor for CHD, in several studies and the effect of almonds has been well documented in systematic reviews and meta-analysis of clinical trials. Conclusions: Addition of almonds in the diet has been shown to not only to reduce LDL-C levels, but also to maintain HDL-C levels. This review informs about the use of this simple nutritional strategy which may help manage known major risk factors for heart disease such as high LDL-C and low HDL-C levels especially in the context of South Asians.

Brushless Direct Current Motors are significantly improved for using many electrical applications. The design investigation is increased year by year and most of the motor design researchers find out the superior efficiency of the BLDC motor. The traditional motor consumed more electrical power than BLDC motor. The design of BLDC motors that are compact, small, easy to control, save energy and light weight. Due to this fact, the design of BLDC motor should be analyzed to improve the motor characteristics performance. The research focuses on the design of BLDC motor performance using Taguchi Method and Response Surface Methodology (RSM) for Finite Element Method (FEM). Firstly, the Taguchi Method is applied to identify the optimization point of design parameters and consider using the reference model of actual BLDC electric fan motor with a rated power of 26Watts design. Based on the Taguchi Method to create the RSM is used to two-step optimization design performance using in FEM analysis. The performances of motor design proposed approach to provide the effeteness for motor design investigator. In this investigation aims the better structural performances in output power, torque, efficiency and torque ripple. The final design of proposed model achieved an energy efficiency is 10% higher than the reference design of prototype modes, the output power result is 10W higher this reference design. We can reduce the loss of the proposed motor design. Furthermore, the maximum torque can also increase the 0.032Nm of that design. The design simulation results were produced and studied by the FEM analysis of JMAG software. From the evaluation results, the configurations of reference model design are compared with the proposed design by using the three methods of motor design optimization showed the best characteristics for performance of motor investigation design.

Gaussian mixture models (GMMs) are powerful tools specifically suited for problems where data distributions are multi-modal. Inspired by Fourier expansion, we propose a concept called GMM expansion to approximate arbitrary densities. A simple learning method is introduced under this framework. Theoretical and numerical analyses are provided to show that densities under GMM expansion are able to approximate arbitrary densities with certain accuracy. The proposed learning algorithm demonstrates better accuracy and time efficiency compared to classic density approximation methods such as the Expectation Maximization (EM) algorithm and Bayesian variational inference (BVI) for Gaussian mixture models. The proposed framework also shows better accommodation of neural networks. Three neural network applications are built to demonstrate its usability. The accuracy of density estimation in neural networks is reported to be significantly improved in one of the applications. Another application shows that latent variables can be easily turned into random variables. This user-friendly method opens up more possibilities in terms of latent manipulation, embedding techniques, and many other potential uses.

Molecular transport and quantum tunneling of H2 and H2O molecules through nanoporous gra-phene is studied using computational modeling and first principles density functional theory. It is demonstrated that molecules with sufficiently high kinetic energies can tunnel through the na-nopores. It is also demonstrated that molecules can be trapped in front of the nanopore or behind it. These investigations help us learn the behavior of molecules in and around nanopores of gra-phene. They also help us learn fundamentals of molecular tunneling. We believe, nanoporous gra-phene can play important roles for gas separation and nanofiltration.

In this study we have investigated the effect of the addition of Nb2O5 (up to 5 mol%) on the structure and luminescent properties of ZnO-B2O3 glass doped with 0.5 mol % Eu2O3 by using of infrared (IR), Raman and photoluminescence (PL) spectroscopy. Physical properties as molar volume, oxygen packing density and glass transition temperature were determined using the results of differential thermal analyisis (DTA) and Archimedes principle for density. IR and Raman spectra revealed that niobium ions incorporate into the base zinc borate glass as NbO4 trtraherda and NbO6 octahedra. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (392 nm) excitation using the sharp 7F0 - 5L6 transition of Eu3+. The integrated fluorescence intensity ratio R (5D0 → 7F2/5D0 → 7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites. The higher Еu3+ luminescence emission observed in zinc borate glasses containing 1÷5 mol% Nb2O5 compared to the Nb2O5-free zinc borate glass evidences that Nb2O5 is suitable component for modification of host glass structure and improving the emission intensity.

This study examines the projected impact of climate change on the Density Altitude (DA) at Chinese airports during the summer by the end of the 21st century. Findings indicate that climate change is expected to significantly increase the DA at all Chinese airports, with an estimated rise between 300 and 800 feet. The analysis suggests temperature increases will universally contribute to a rise in DA. Pressure changes, however, are more variable. Most airports are predicted to see an increase in pressure, which could offset some temperature effects on the DA. Airports in eastern China are expected to see a decrease in pressure, amplifying the effects on DA and creating operational challenges.

In this study, we discuss the thermospheric density response to the solar activity and QBO. By using the wavelet power spectrum method, the thermospheric density from 1967 to 2013 shows ~11-year period, semiannual and annual variations, while the seasonal variation is usually more significant under high solar activity conditions. Importantly, we investigate the possible link between the density and the QBO, with the aid of GAMDM model and different density residual method. As a result, the difference between the measured density and empirical model seemingly has QBO signal, but the ratio of them revels that the QBO signal does not exist in the thermospheric density. Comprehensively, we thought the stratospheric QBO cannot impact on the thermosphere, and more data and numerical modeling are needed for further validation.

A potential association between hematopoietic stem cell status in the bone marrow and the surrounding bone tissue has been hypothesized, and some studies have investigated the link between blood count and bone mineral density (BMD), although their exact relationship remains controversial. Moreover, biological factors linking the two are largely unknown. In our present study, we found no clear association between platelet count and BMD in the female group, with aging having a very strong effect on BMD. On the other hand, a significant negative correlation was found between platelet count and BMD in the male group. As a potential mechanism, we examined whether megakaryocytes, the source of platelet production, secrete cytokines that regulate BMD, namely OPG, M-CSF, and RANKL. We detected the production of these cytokines by megakaryocytes deriving from bone marrow mononuclear cells and found that RANKL was negatively correlated with BMD. This finding suggests that RANKL production by megakaryocytes may mediate the negative correlation between platelet count and BMD. To our knowledge, this is the first report to analyze bone marrow cells as a mechanism for the association between blood count and BMD. Our study may provide new insights into the development and potential treatment of osteoporosis.

The production and secretion of very-low density lipoproteins (VLDL) by hepatocytes has a direct impact on liver fat content as well as the concentration of cholesterol and triglycerides in the circulation and thus affects liver and cardiovascular health, respectively. Importantly, excess caloric intake and lack of physical activity are associated with overproduction of VLDL, hepatic steatosis, and increased levels of atherogenic lipoproteins. Cholesterol as well as triglycerides in remnant particles after VLDL lipolysis are risk factors for atherosclerotic cardiovascular disease (ASCVD) and have garnered increasing attention over the last few decades. To date, however, increased risk of ASCVD is not the only concern when considering today’s cardiometabolic patients, as they often also suffer from hepatic steatosis. This notion highlights the importance of understanding the molecular regulation of VLDL biogenesis. Fortunately, there has been a resurgence of interest in the intracellular assembly, trafficking, degradation, and secretion of VLDL by hepatocytes, that has led to many exciting new molecular insights, the topic of this review. We think that increasing our understanding of the biology of this pathway will help improve the health of the cardiometabolic patient in the long term.

The elegance of mathematical models in quantum mechanics has often been seen with awe, and especially frustration. Nonetheless, the mathematical physics of quantum mechanics is fascinating beyond measure. And fortunately, there are quite baffling things about quantum mechanics that showed us what we never thought could be seen, making it simpler to figure out the behavior of physical systems without having to delve into the subtleties of the subject. In this paper, we present a review on the density of quantum states in an intuitive fashion that is easily comprehensible to undergraduate students with an elementary background in physics.

In this paper, we propose a quantitative definition of emergence from the density matrix framework as a state of knowledge of the system and its generalized probability formulation, in order to detect emergent properties. We propose the use of a descriptor based on the difference of von Neumann entropy, to calculate if subsystems of systems have inner correlations by defining emergent systems in terms of emergent information.

Development and engineering of protein crystals regarding mechanical stability and crystallizability occurs on a small scale. Later in the process chain of industrial production however, filtration properties are important to separate the crystals from mother liquor. Many protein crystals are sensitive to mechanical stress which is why it is important to know the filtration behavior early on. In this study we analyze settling and filtration behavior of isometric, rod-like and needle shaped lysozyme and rod-like alcohol dehydrogenase (ADH) crystals on a small scale using an optical analytical centrifuge. Needle shaped lysozyme and rod-like ADH crystals show compressible material behavior. With the results from settling and filtration experiments the flux density function is calculated and modeled which can be used to describe the whole settling and permeation process in dependency of the solids volume fraction. This is also an issue for simulations of industrial processes.

One of the notable temporal properties of dynamical systems is that a set of initial states leads the solutions to reach desired states avoiding a predetermined unsafe set.This property, that we call safe reachability has been studied in literature for autonomous systems using Barrier functionand Barrier densities [1]. In this paper, we generalize a sufficient condition for safe reachability of autonomous systemto switched systems under arbitrary switching signals. The condition relies upon the existence of a common Barrier density function for each subsystem. We apply the condition using the sum of squares method together with Putinar Positivstellensatz.

This study investigated the evolution of density, gas permeability and thermal conductivity of sugar maple wood during the thermo-hygro-mechanical densification process. The results suggested that the oven-dry average density of densified samples was significantly higher than that of the control samples. However, the oven-dry density did not show a linear increase with the decrease of wood samples thickness. The radial intrinsic gas permeability of the control samples was 5 to 40 times higher than that of densified samples, which indicated that the void volume of wood was reduced notably after the densification process. The thermal conductivity increased by 0.5 - 1.5% per percent increase of moisture content for densified samples. The thermal conductivity of densified wood was lower than that of the control samples. The densification time had significant effects on the oven-dry density and gas permeability. Both the densification time and the moisture content had significant effects on thermal conductivity, but their interaction effect was not significant.

This study investigated the physical and combustion properties of briquettes produced from agricultural wastes (groundnut shells and corn cobs), wood residues (Anogeissus leiocarpus) and admixtures of the particles at 15%, 20% and 25% starch levels (binder). A 6 x 3 factorial experiments in a Completely Randomized Design (CRD) was adopted for the study. The briquettes produced were analyzed for density, volatile matter, ash content, fixed carbon and specific heat of combustion. The result revealed that the density ranged from 0.44g/cm³ to 0.53g/cm³, while briquettes produced from groundnut shells had the highest (0.53g/cm³) significant mean density. Mean volatile matter and ash content of the briquettes ranged from 24.35% to 34.95% and 3.37% to 4.91%. A. leiocarpus and corn cobs particles had the lowest and highest ash content respectively. The briquette fixed carbon and specific heat of combustion ranged from 61.68% to 68.97% and 7362kca/kg to 8222kca/kg respectively. Briquette produced from A. leiocarpus particles had the highest specific heat of combustion. In general, briquettes produced from A. leiocarpus particles and admixture of groundnut shell and A. leiocarpus particles at 25% starch level had better quality in terms of density and combustion properties and thus suitable as environmentally friendly alternative energy source.

Rising organic charge in northern freshwaters is attributed to increasing levels of Dissolved Natural Organic Matter (DNOM) and shifts in water chemistry. Organic charge concentration may be determined by charge balance calculations (Org.-) or modelled (OAN-) using the conceptual Oliver and Hruška models based on the density of weak acid functional sites (SD) present in DNOM. The charge density (CD) is governed by the SD and protonation and complexation reactions on the functional groups. The models use this SD as a key parameter in empirically fitting the model to Org.-. Utilizing extensive datasets of water chemistry, this study shows that spatial and temporal differences in SD and CD are influenced by variations in the humic-to-fulvic ratio of DNOM and the organic aluminum (Al) complexation, as well as the mole fraction of CD to SD governed by the acidity. Site median SD obtained for 44 long-term monitored acid-sensitive lakes was 11.1 and 13.9 µEq/mg C for the Oliver and the Hruška model, respectively. During the 34 years of monitoring the CD increased by 70%, likely due to rising pH and declining Al complexation with DNOM. Present-day median SD values for the Oliver and Hruška models in 16 low-order streams are 13.8 and 15.8 µEq/mg C, respectively, and 10.8 and 12.5 µEq/mg C, respectively, in 10 high order rivers.

The critical role of global electron density transfer (GEDT) in increasing the reaction rate of polar organic reactions has been studied within the framework of Molecular Electron Density Theory (MEDT). To this end, the series of the polar Diels-Alder (P-DA) reactions of cyclopentadiene with cyanoethylene derivatives, for which experimental kinetic data are available, have been chosen. A complete linear correlation between the computed activation Gibbs free energies and the GEDT taking place at the polar transition state structures (TSs) is found; the higher the GEDT at the TS, the lower the activation Gibbs free energy. An interacting quantum atoms (IQA) energy partitioning analysis allows establishing a complete linear correlation between the electronic stabilization of the electrophilic ethylene frameworks and the GEDT taking place at the polar TSs. This finding supports Parr’s proposal for the definition of the electrophilicity  index (J. Am. Chem. Soc., 1999, 121, 1922). The present MEDT study allows establishing the critical role of the GEDT in the acceleration of polar reactions, since the electronic stabilization of the electrophilic framework with the electron density gain is greater than the destabilization of the nucleophilic one, making a net favorable electronic contribution to the decrease of the activation energy.

Abstract Cholesterol has ruled the history of atherosclerotic cardiovascular diseases (CVD) for decades, and the transport of cholesterol by lipoproteins has become a cornerstone of our view of etiology of the disease. Discovery of the lipoprotein-specific transport of lipid oxidation products (LOP) has opened a new and exciting area in research of CVD by revealing strong connections between atherogenic LOP, lipoprotein transport functions and CVD. This review goes through the evidence in support of the lipoprotein-specific LOP transport and speculates of possible consequences of the proposed role of lipoprotein LOP transport as a risk factor. Association of lipoprotein LOP with known risk factors of CVD are largely parallel with those of cholesterol, and due to the common transport and cellular intake mechanisms the elucidation of independent effects of either cholesterol or LOP is difficult. Yet, unlike cholesterol, LOP can directly initiate and boost atherogenic processes. It therefore appears inevitable that increasing knowledge of the lipoprotein-specific LOP transport will affect the present view of the role of cholesterol in aetiology and as a risk factor of CVD.

The ionic Diels-Alder (I-DA) reactions of a series of six iminium cations with cyclopentadiene have been studied within the Molecular Electron Density Theory (MEDT). The superelectrophilic character of iminium cations,  > 8.20 eV, accounts for the high reactivity of these species participating in I-DA reactions. The activation energies are found between 13 and 20 kcal·mol-1 lower in energy than those associated to the corresponding Diels-Alder (DA) reactions of neutral imines. These reactions are low endo selective as a consequence of the cationic character of the TSs, but highly regioselective. Solvents have poor effects on the relative energies, and an unappreciable effect in the geometries. In dichloromethane the activation energies increase slightly as a consequence of the better solvation of the iminium cations than the cationic TSs. ELF topological analysis of the bonding changes along the I-DA reactions shows that they are very similar to those in polar DA reactions. The present MEDT study makes it possible establishing that the global electron density transfer (GEDT) taking place at the TSs of I-DA reactions, and not steric (Pauli) repulsions such as have been recently proposed, are responsible for the features of these type of DA reactions.

The electronic structure and the participation of the simplest azomethine imine (AI) in [3+2] cycloaddition (32CA) reactions have been analysed within the Molecular Electron Density Theory (MEDT) using DFT calculations at the MPWB1K/6-311G(d) level. Electron localisation function (ELF) topological analysis reveals that AI has a pseudoradical structure, while the conceptual DFT reactivity indices characterise this TAC as a moderate electrophile and a good nucleophile. The non-polar 32CA reaction of AI with ethylene takes place through a one-step mechanism with low activation energy, 5.3 kcal/mol-1. A bonding evolution theory (BET) study indicates that this reaction takes place through a non-concerted [2n+2τ] mechanism in which the C–C bond formation is clearly anticipated prior to the C–N one. On the other hand, the polar 32CA reaction of AI with dicyanoethylene takes place through a two-stage one-step mechanism. Now, the more favourable regioisomeric transition state structure (TS) is located 8.5 kcal•mol⁻¹ below the reagents, in complete agreement with the high polar character of the TS. The current MEDT study makes it possible to extend Domingo’s classification of 32CA reactions to a new pra-type of reactivity.

The extended finite element method (XFEM) is now widely used in crack simulations and the direction of propagation of the XFEM crack in SS-304 has been quite interesting. This paper discusses the direction,θ(+ve in anti-clockwise direction), of the XFEM crack (under mode-I) propagation based on the von Mises stress-field around the crack-tip for static loading under the light water reactors (LWRs) conditions. The Mises core region from the crack-tip is chosen for β=〖90〗^o, the angle between the load and the initial crack. Experimental data for LWRs’environment is obtained and the simulations have been carried out applying three different static loads and results for the direction of the crack are calculated by measuring the stress-field around the crack-tip. It has been found that the direction of the XFEM varies inversely as the stress-field around the crack tip is increased. The computational results have been compared with the numerical results based on the minimum strain energy density criterion[S-criterion].

When extract building from high resolution remote sensing image with meter/sub-meter accuracy, the shade of trees and interference of roads are the main factors of reducing the extraction accuracy. Proposed a Bayesian Convolutional Neural Networks(BCNET) model base on standard fully convolutional networks(FCN) to solve these problems. First take building with no shade or artificial removal of shade as Sample-A, woodland as Sample-B, road as Sample-C. Set up 3 sample libraries. Learn these sample libraries respectively, get their own set of feature vector; Mixture Gauss model these feature vector set, evaluate the conditional probability density function of mixture of noise object and roofs; Improve the standard FCN from the 2 aspect:(1) Introduce atrous convolution. (2) Take conditional probability density function as the activation function of the last convolution. Carry out experiment using unmanned aerial vehicle(UVA) image, the results show that BCNET model can effectively eliminate the influence of trees and roads, the building extraction accuracy can reach 97%.

Soybean are vulnerable to drought and temperature increases potentially induced by climate change. The purpose of this study was to determine if the use of cover crops (CC) can influence the gas exchange potential of glyphosate tolerant soybean when the vapor pressure deficit (Vpd) increases. This two years study was conducted in an open experimental field comprising Direct Seeding plots without CC (DS) or with CC (DSCC). Stomatal conductance (Gs) was measured five times on the same identified leaves following GBH application. These leaves were then collected in order to observe the stomata (size, density and stomatal index) with a scanning electron microscope and to perform measurements on foliar traits (venation density, width of midrib). The Vpd was calculated concomitantly to Gs measurements at the leaf surface. The results suggest that the use of CC promotes phenotypic change in soybean leaves (more elaborate venation and a higher stomatal density), which in turn may enhance their tolerance to drier conditions. In 2019, Gs could be up to 29% higher in DSCC plots compared to DS ones along with similar Vpd values. This study shows that the benefits of using CC can be observed through the morphological development strategies of the crop plants and their higher tolerance to drought.

Recently, the composite materials consisting of ionic liquids (ILs) and metal-organic frameworks (MOFs) have attracted a great of attention due to their fantastic properties. Many theoretical studies have been performed towards its special structures and applications. Yet, the mechanism for the diffusion of ILs inside MOFs channels still remain unclear. Here, the DFT calculations together with frontier orbital analysis, natural charge analysis, and energy decomposition analysis were performed to investigate the diffusion behavior of a typical IL, [C4mim][PF6], into the ZIF-8 SOD cage. The potential energy surface (PES) profiles indicate that it is quite difficult for the cation [C4min]+ to diffuse into the cage of ZIF-8 through the pristine pores because of its large imidazole steric hindrance. Moreover, the PES reveals that a success diffusion could be obtained by the thermal contributions, by which the pore size is enlarged through the swing effects at a higher temperature. Subsequently, electronic structure analyses reveal that the main interactions between [PF6]-or [C4mim]+ and ZIF-8 is the steric repulsion interactions. Finally, the effects of amounts of [C4mim][PF6]on the ZIF-8 were investigated, and the results show that two pairs of [C4mim][PF6] per SOD cage is more reasonable in terms of interaction energies and structural changes.

There is a continuous interest in cannabinoids like Δ9-tetrahydro cannabinol (Δ9-THC) and cannabidiol (CBD). A patent of Webster et al., described the conversion of CBD to either D8-THC or D9-THC, depending on the acid catalyst applied. The use of para-toluene sulfonic acid (pTSA) led to the formation of D8-THC, while boron trifluoride etherate (BF3·Et2O) yielded mainly D9-THC. The enormous difference in product selectivity between these two catalysts was investigated with Molecular Modeling. It was found that pTSA leads to fast isomerization of Δ9-CBD to Δ8-CBD and subsequent ring closure to Δ8-THC. BF3·Et2O catalysis leads to the formation of tertiary carbenium ions in the Transition States which yield D9-THC and some iso D8-THC. Under dry conditions in refluxing toluene, it was found that pTSA is predominantly present as a dimer, and only a small fraction is available as monomeric catalyst. Applying the computationally derived activation barriers in Transition State theory yielded reaction rates predicting amounts of cannabinoids that are in close agreement with the experimental findings.

The phytonutraceutical Ormona® is a product composed of: purified oil of Bixa orellana Linné; dry extract of Myrciaria dubia McVaugh; dry extract of Trifolium pratense L. and dry extract of Euterpe oleracea Mart. obtained using Evolve® technology. This study evaluated the effects of Ormona® on Wistar rats affected by ovariectomy-induced osteoporosis. Pre-treatment was conducted for 15 days before surgery and continued for a further 45 days after the surgical procedure. The experimental design consisted of 5 groups (n=5): OVW: treated with distilled water (1 mL/ kg, p.o); ADS: alendronate sodium (4 mg/ kg p.o); EST: conjugated estrogen (2 ug/ kg, p.o); ORM: Ormona® (20 mg/kg, p.o); ORM + EST: Ormona® (20 mg/kg + conjugated estrogen 2 ug/ kg, p.o. Biochemical and hormonal parameters, along with bone histopathology and trabecular and femoral diaphysis size, were evaluated through Scanning Electron Microscopy (SEM) and bone calcium quantification by atomic absorption spectrophotometry. The results show that ovariectomy caused bone alterations such as loss of femoral microarchitecture, decreased bone homeostasis parameters, and changes in the lipid profile. Estrogen supplementation reduced parameters such as cholesterol, LDL, and Ca2+ concentration. However, Ormona® showed higher serum estradiol levels (p&lt; 0.01), effects on the lipid profile, including parameters that estrogen replacement and alendronate sodium did not affect, with an increase in HDL, and positive modulation of bone metabolism, increasing osteocytes and the presence of osteoblasts. Ormona®, therefore, produced better results than the groups treated with estrogen and alendronate sodium.

The well-known equations for the process of powder compaction (PCP) in a rigid die published over the period from the beginning of the last century to the present are considered. Most of the considered equations are converted into the dependence of the densification pressure on the relative density. The equations were analyzed and their ability to describe PCP was assessed by determining the coefficient of determination when approximating experimental data on the compaction of various powders. It is shown that most of the equations contain two constants, the values of which are determined by fitting the mathematical dependence to the experimental curve. Such equations are able to describe PCP with high accuracy in the case of compaction of powders up to a relative density of 0.9-0.95. It is also shown that different equations can describe PCP in the range of density change from the initial to 0.9 with the same and sufficiently high accuracy, but when the process of compaction is extrapolated to higher values of density, the curves diverge. This indicates the importance of equations that can unambiguously describe PCP to a relative density equal to or close to 1.0. For an adequate description of PCP to a relative density greater than 0.95, equations containing three or four constants have proven themselves well.

As the global community shifts away from fossil fuels towards more environmentally friendly energy alternatives, there is an escalating demand for sophisticated energy storage solutions. Solid-State Batteries (SSBs) have emerged as a promising advancement, presenting a superior substitute to conventional lithium-ion batteries. This review provides an in-depth examination of SSBs, emphasizing their enhanced energy density, safety, and longevity. We evaluate conventional cathode materials, including lithium cobalt oxide (LiCoO2), lithium manganese oxide (LiMn2O4), and lithium iron phosphate (LiFePO4). Additionally, we introduce emerging materials such as sulfides, oxides, and air-based cathodes, discussing their benefits, limitations, and their congruence with solid electrolytes. Special attention is devoted to the structural fine-tuning of cathode ma-terials, investigating approaches like nanostructuring, surface coatings, and composite strategies to counteract issues such as restricted conductivity and structural volatility. The review critically analyzes the electrical and thermal properties of these materials, which are essential for battery safety and efficacy. Moreover, we present a comparative assessment of cathode materials based on performance indicators and identify prevailing research voids and hurdles in the commerciali-zation of SSB cathodes. Concluding, we suggest prospective research directions and innovations, underscoring the revolutionary potential of SSB technologies in paving the way for a sustainable energy horizon.

Cadmium, an environmental toxin, is associated with a range of adverse health effects due to increased Reactive Oxygen Species production, including decreased bone mineral density and osteoporosis. Notably, cadmium is found at concentrations 4-5x higher in the blood of smokers versus non-smokers. Experiments performed in human cancer cells indicate that melatonin may directly protect against cadmium-induced tissue damage via regulation of mitochondrial activity. Further, recent evidence has demonstrated that melatonin can improve bone health for individuals with osteoporosis and partially protect against cadmium-associated inhibition of bone repair. Here we review this data and propose supplementation with melatonin as a strategy to protect against the negative impacts of cadmium exposure on bone mineral density within individuals regularly exposed to cadmium via cigarette smoking.

Consumption of prunes has been shown to slow bone loss after menopause in American women but there is no data on its effects in Asian women. 135 postmenopausal Korean women with osteopenia were randomized to 100g/day of prunes or no prunes with 600U vitamin D and 800mg of calcium for 12 months. Bone density was measured at baseline and 12 months in the lumbar spine, both hips and the L forearm. Serum levels of CTX and P1NP and vitamin D calcium and phosphate were measured at baseline, 6 and 12 months. PTH was measured at baseline if vitamin D was low Four women dropped out of each group over the 12 months. There was no difference between groups in blood measures or bone density in any region over the 12 month trial., In conclusion 100g/day of prunes has no effect in Korean woman on bone density or bone markers.

The outbreak of the COVID-19 pandemic has raised concerns about potential environmental factors that could influence the spread and severity of the SARS-CoV-2 virus. Atmospheric pollution, particularly particulate matter (PM), has been suggested as a contributing factor to viral infections and respiratory complications. This two-year observational study aimed to investigate the relation between air pollution and the spread of COVID-19, focusing on PM2.5. Unlike previous studies limited to specific cities or countries, inevitable to use temporal data. Our research analyzed data from various states across the United States, considering both spatial and temporal correlation. The analysis considered the number and geographic distribution of COVID-19 cases along with daily PM2.5 exposure levels, accounting for monthly average PM2.5 exposure, from March 2020 to December 2021. The observed conflicting results of the temporal and spatial correlation present challenges for researchers in understanding the true nature of the relationship between PM2.5 air pollution and COVID-19 cases. The correlation between various factors, such as population density, PM2.5, temperature, and wind speed, and COVID-19 refers to an association or statistical relationship, not causation. Moreover, the intricate interplay of these variables makes it difficult to establish a clear cause-and-effect relationship.

Although impending urbanization is a well-acknowledged problem, there is a rising concern about how the urban forms will change and what can be the impacts on the global energy demand. As hubs of economic, social and cultural activities, cities are major energy consumers and GHG emissions. Energy consumption is a technical or a spatial problem? From Newman and Kenworthy to today, several studies have tried to shed light on this nexus. In this work, the controversial paradigm of urban density is discussed as a key component of the fight against climate change impacts. Concerning energy consumption, an in-depth bibliometric analysis is developed to identify the interdependencies of the terms. As a key ‘promise’ of an efficient urban configuration, density has been the core of diverse studies but with still under exploration arguments. This work provides a way forward for planners seeking to design strategies related to dense urban tissues exploring controversial paradigms as a key solution for energy-efficient problems.

Nickel-base superalloys like VDM 780 may possess a high content of Cr and Co. This influences solution energies of phase-forming elements like Al and Ta (γ′-phase), Nb (γ′′- and δ-phase), and Ti (η-phase). We perform density functional theory studies of a nickel matrix at 0 K with high concentrations of either Co and Cr and calculate the influence of these elements on solution energies. In the case of Co, the solution energy can be predicted well by the nearest-neighbor interaction in the Co-rich matrix. For Cr, the effect is more complicated because Cr has a larger ionic radius and changes the magnetic state of the material. The effect of a Cr-rich matrix on the energy of Co is dominated by magnetic effects, interactions with the other elements by elastic deformation of the lattice.

The X-ray emission from a supernova remnant (SNR) is a powerful diagnostic of the state of the shocked plasma, and, given a model, can be used to determine the energy of the explosion, the age of the SNR and the density of the surrounding medium. Observed properties are shock radius, electron temperature (kTe) and emission measure (EM) of the shocked-gas. The standard and XSPEC definitions have an important difference. The XSPEC definition is superior for SNRs, which have components with low hydrogen abundance. SNR model calculations are based on hydrodynamic solutions for fluid variables of density, pressure and velocity. The relations between fluid variables and kTe or EM depend on composition, ionization state and electron-ion temperature ratio (Te/TI). Here the effects of composition, ionization and Te/TI on standard and on XSPEC versions of kTe and EM are investigated.

Our study assessed the impact of using ovitraps with pyriproxyfen on mosquito populations and the feasibility of using human saliva samples to test for seroconversion to dengue virus (DENV). We used a quasi-experimental research design by forming the intervention (n=220) and the control (n=223) groups in neighboring Taguig City, Philippines, over four months. Socio-demographic data, entomological indices, and IgG antibodies against DENV were measured. Associations between the implementation of ovitraps dosed with pyriproxyfen and mosquito densities (percentage positive ovitraps and container indices) and DENV seroconversion were calculated post-intervention in Months 2, 3, and 4. Among participants recruited at baseline, 17 and 13 were seropositive for dengue (DENV) in the intervention and control groups, respectively. Both entomological indices were lower in the treated area than the control site at months two, three, and four post-interventions but not earlier. Dengue seroconversions rates did decrease in the treated population but not significantly so. In conclusion, the use of PPF-treated ovitraps impacted the mosquito population but not the seroconversion rates. Compliance to provide saliva samples and the ability to detect IgG antibodies within these samples were encouraging and suggested that further studies on a larger population and longer duration are warranted.

Astragalus bone is one of the most important fossil records as it can reconstruct the prehistoric life. Respectively, this study aims to model the body mass, habitat preference, and population density of prehistoric bovid Duboisia santeng (Dubois 1891) in eastern Java island in the early Pleistocene. The astragali from 9 specimens were used to estimate the body mass and population density. Likewise regression models are used to analyze the relationship between astragalus lateral length, width, and body mass compared to the astragalus of extant Bovid species. The result revealed the body mass average was 60.3 kg (95%CI: 58.9-61.7) and this indicates the D. santeng belongs to large herbivores. While the population density was estimated at about 5.39 individuals per km2 (95% CI: 3.18-7.6).

In this four-month-long study (from April 1, 2020 to August 1, 2020), we have collected, modeled, and analyzed COVID-19 data from the top five most infected counties per top six most infected states in the United States (30 counties total). More specifically, we collected data on each state’s total COVID-19 cases, deaths, tests conducted, and their counties’ population, density, percentage of seniors, number of hospitals, total COVID-19 cases, and total COVID-19 related deaths. In this study, we have models illustrating the growth of COVID-19 cases and deaths per county, growth of COVID-19 cases and deaths per state (which is really the sum of our chosen five counties), and growth of COVID-19 tests conducted per state. In addition, our study also contains models illustrating the statistics of several variables that might have affected a county’s COVID-19 data, which has been mentioned above: population, density, percentage of seniors, and number of hospitals. An interesting finding we have noticed upon modeling the 30 counties’ density and total COVID-19 cases as an xy scatter plot is that there is a considerably strong relationship between the two variables. Los Angeles County (which was an extreme outlier), in particular, supports the idea that a county’s most populous city can greatly affect its entire county’s COVID-19 cases; if the largest city is extremely dense, it appears that the entire county has a greater total COVID-19 case count.

The present investigation deals with the determination of the physio-chemical properties of two commercial grade samples of local gums (Gum Arabic and Natural Rubber Latex (NRL)). The results revealed that the gum samples have high melting point that indicate thermal stability at room and moderate temperatures. The gum samples have about 95 % carbohydrate content and a corresponding high internal energy and can serve as a source of energy. The rheology of the samples revealed shear-thickening characteristics with gum Arabic being thixotropic and pseudo-plastic in nature while NRL was observed to be anti-thixotropic and rheopectic. Further results from the moisture absorption, contact angle and Fourier Transform Infrared Radioscopy (FTIR) analyses gave better insight into their hydroscopic behaviors. Gum Arabic has excellent water absorption capacity with less wettability as it consists mainly of more water-soluble compounds in comparison to Natural Rubber Latex. These insights from the study will enhance wider application of the gums with increased value-addition to the gums and the communities where they (can) thrive.

Temperature influences the life of many organisms in various ways. A great number of them live under conditions, where their ability to adapt to changes in temperature can be vital and largely determine their fitness. Understanding the mechanisms and principles underlying this ability to adapt can be of great advantage, for example, to improve growth conditions for crops and increase their yield. In times of imminent, increasing climate change, this becomes even more important, in order to find strategies and help crops cope with these fundamental changes. There is intense research in the field of acclimation, that comprises fluctuations of various environmental conditions, but most acclimation research focuses on regulatory effects and the observation of gene expression changes within the examined organism. As thermodynamic effects are a direct consequence of temperature changes, these should necessarily be considered in this field of research, but are often neglected. Also, compensated effects might be missed, even though they are equally important for the organism, since they do not cause observable changes, but rather counteract them. In this work, using a systems biology approach, we demonstrate that even simple network motifs can exhibit temperature dependent functional features, resulting from the interplay of network structure and the distribution of activation energies over the involved reactions. The demonstrated functional features are (i) the reversal of fluxes within a linear pathway, (ii) a thermo-selective branched pathway with different flux modes and (iii) the increased flux towards carbohydrates in a minimal calvin cycle that was designed to demonstrate temperature compensation within reaction networks. By this, we expand the scope of thermodynamic modelling of biochemical processes by addressing further possibilities and effects, following established mathematical descriptions of biophysical properties.

Background We aimed to compare the retinal, optic disc vascular density (ODVD) values, and acircularity index (AI) of patients with idiopathic macular telangiectasia type 2 (IMT) and healthy individuals using the optical coherence tomography angiography(OCTA) device. Methods The study included 39 patients with IMT and 37 healthy controls. The OCTA findings of the patients and controls were examined. Results The total, parafoveal and perifoveal vascular density of the superficial capillary plexus, choriocapillaris blood flow, inside-disc ODVD, retinal nerve fiber layer (RNFL), and retinal thicknesses were found to be statistically significantly lower and the foveal avascular zone value was statistically significantly higher in the IMT group compared to the control group (p=0.001, p=0.01, p=0.02, p=0.01, p=0.009, p=0.002, p=0.02, respectively).There was a statistically significant negative correlation between best-corrected visual acuity (BCVA) and AI (p=0.02), a statistically significant positive correlation between peripapillary vascular density and BCVA(p=0.04). Conclusion We consider that the lower retinal, choriocapillaris, and ODVD values, retinal and RNFL thicknesses in the patients with IMT compared to the controls were due to vascular damage, remodeling, fibrosis, proliferation, and Müller cell damage. Ellipsoid zone defect, AI, and peripapillary vascular density are important indicators in the evaluation of visual acuity in these patients.