We show the tensor properties of joint probabilities on a Riemannian parametric manifold. Initially we develop a binary data matrix for parameter measurements of a large number of particles confining in a closed system in order to retrieve the joint probability densities of related parameters. By introducing a new generalized inner product as a multilinear operation on dual basis of parametric space, we extract the set of joint probabilities and prove them to meet contravariant tensor properties in a general Riemannian parametric space. We show these contravariant tensors reduce to classical ordinary partial derivatives definition in ordinary Euclidean parametric space. Finally we prove by a theorem that symmetrized iterative contravariant derivative of cumulative probability function on Riemannian manifold gives the set of joint probabilities in those manifold. We bring some examples for compatibility with physical tensors.

A precise understanding of the genes and associated genomes of SARS-CoV2 is important for various reasons such as discovering origin of the virus and virulence and so on. A thorough descriptive understanding of the SARS-CoV2 genomes and other coronavirus of the beta-coronavirus genus is primarily important. In this article, a set of ten genomes of four CoVs and their associated genes are considered for this present study. A spatial representations of nucleotide bases including purine-pyrimidine representations of the different genes of the corresponding genomes are quantified using Hurst exponent, Shannon entropy and density estimation of different nucleotides including GC content, in order to draw a comparison and contrast among the ten genomes of different types of CoVs which include MERS, SARS-CoV, HKU1 (Human Coronavirus) and associated their genes.

The lightcone gauge is a set of what are called the observational coordinates adapted to our past lightcone. We develop this gauge by producing a perturbed spacetime metric that describes the geometry of our past lightcone where observations are usually obtained. We connect the produced observational metric to the perturbed Friedmann-Lema\^itre-Robertson-Walker metric in the standard general gauge or what is the so-called 1+3 gauge. We derive the relations between these perturbations of spacetime in the observational coordinates and those perturbations in the standard metric approach, as well as the dynamical equations for the perturbations in observational coordinates. We also calculate the observables in the lightcone gauge and re-derive them in terms of Bardeen potentials to first order. A verification is made of the observables in the perturbed lightcone gauge with those in the standard gauge. The advantage of the method developed is that the observable relations are simpler than in the standard formalism, and they are expressed in terms of the metric components which in principle are measurable. We use the perturbed lightcone gauge in galaxy surveys and the calculations of galaxy number density contrast. The significance of the new gauge is that by considering the null-like light propagations the calculations are much simpler due to the non-consideration of the angular deviations.

In this study, modified red mud after phosphorus adsorption was used as the adsorbent, and hydrochloric acid and deionized water were used as desorbents to desorb phosphorus. The components in the adsorbent were optimized based on density functional theory, and adsorbent and desorbent models were established. Molecular dynamics simulation was performed to determine the phosphorus concentration before and after desorption, interaction energies, radial distribution function(RDF), mean-square displacement(MSD), and diffusion coefficient. The Monte Carlo method was used to simulate the desorption isotherm, desorption site, heat of desorption, and desorption energy. Simulation results showed that deionized water could only desorb phosphorus on the adsorbent surface, and the stability of the system deteriorated upon adding hydrochloric acid. Hydrochloric acid destroyed the ionic and hydrogen bonding between the O atoms in H2PO4− and reactive metal and oxygen atoms in the activated red mud particles. Moreover, the van der Waals force decreased considerably. The ionic and hydrogen bonds between H2PO4− and the surface of activated red mud particles were broken by hydrochloric acid, which accelerated the desorption of phosphorus from the adsorbent surface. The interaction between hydrochloric acid and phosphorus accelerated the diffusion, which decreased the adsorption capacity. Moreover, the desorption capacity increased with increasing temperature.

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.

The urban environment induces stress on trees and the impact can be identified by observing the condition of the crown. The aim of this study is to correlate the variables crown density (Cdn), crown transparency (Ctr) and dieback (Cdie) with the following vegetation indices: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI2), blue normalized difference vegetation index (BNDVI), green normalized difference vegetation index (GNDVI), green-red vegetation Index (GRVI) and red-green-blue vegetation index (RGBVI) of the tree crown located in urban green areas, as well as chlorophyll fluorescence (Fv/Fm) as an indirect indicator of tree health condition. A total of 549 trees were evaluated, represented in 24 families, 36 genera and 53 species; the variables had average values of 67.96 % in Cdn, 35.19 % in Ctr and 1 % in Cdie. Correlations were found between Fv/Fm, NDVI and BNDVI. NDVI and BNDVI correlated with variables such as Cdn and Ctr, mainly in species such as Ligustrum lucidum, Jacaranda mimosifolia and Fraxinus uhdei. Therefore, it is possible to evaluate tree health condition of trees in urban green environments through the identification of unfavorable conditions at the crown level by using vegetation indices for some of the species studied.

This paper discusses about the quantum energy levels of muonic hydrogen considering only Coulomb interaction. The computational analysis in this paper will help the reader get a good understanding of how different a muonic hydrogen is from its electronic counterparts. Energy eigenvalues are calculated by numerical method and the probability density distribution of muon around the nucleus is plotted for different quantum states using special functions. The code is written in python. A comparative study of emission spectra between the muonic hydrogen and hydrogen has also been discussed.

This paper proposes an encryption scheme for high pixel density images. Based on the application of the quantum random walk algorithm, the Long short-term memory (LSTM) can effectively solve the problem of low efficiency of the quantum random walk algorithm in generating large-scale pseudorandom matrices, and further improve the statistical properties of the pseudorandom matrices required for encryption. The LSTM is then divided into columns and fed into the LSTM in order for training. Due to the randomness of the input matrix, the LSTM cannot be trained effectively, so the output matrix is predicted to be highly random. The LSTM prediction matrix of the same size as the key matrix is generated based on the pixel density of the image to be encrypted, which can effectively complete the encryption of the image. In the statistical performance test, the proposed encryption scheme achieves an average information entropy of 7.9992, an average number of pixels changed rate (NPCR) of 99.6231%, an average uniform average change intensity (UACI) of 33.6029% and an average correlation of 0.0032. Finally, various noise simulation tests are also conducted to verify its robustness in real-world applications where common noise and attack interference are encountered.

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.

We present large eddy simulations of a mid-latitude open ocean front using a modified state of the art computational fluid dynamics code. We investigate the energy and information fluxes at the submesoscale/small-scale range in the absence of any atmospheric forcing. We find submesoscale conditions (Ro∼1, Ri∼1) near surface, within baroclinic structures related with partially imbalanced frontogenetic activity. Near surface, the simulations show a significant scale coupling on scales larger than ∼103(m). This is manifested as a strong direct energy cascade and intense mutual communication between scales, where the latter was evaluated using an estimator based on Mutual Information Theory. At scales smaller than ∼103(m) the results show near-zero energy flux, however, at this scale range, the estimator of mutual communication still shows values corresponding with a significant level of communication between them. This fact motivates to investigate the nature of the self-organized turbulent motion at this scale range with weak energetic coupling but where communication between scales is still significant and to inquire into the existence of synchronization or functional relationships between scales with emphasis on eventual underlying non-local processes.

One-dimensional chain of core-shell pairs connected by ideal springs enables design of the metamaterial demonstrating the negative effective density and negative specific thermal capacity. We assume that the molar thermal capacity of the reported metamaterial is governed by the Dulong-Petit law in its high temperature limit. The specific thermal capacity depends of the density of the metamaterial; thus, it is expected to be negative, when the effective density of the chain is negative. The range of the frequencies enabling the effect of the negative thermal capacity is established. Dependence of the effective thermal capacity on the exciting frequency for various core/shell mass ratios is elucidated. The effective thermal capacity becomes negative in the vicinity of the local resonance frequency ω0 in the situation when the frequency ω approaches ω0 from above. The effect of the negative effective thermal capacity is expected in metals in the vicinity of the plasma frequency.

To realize high response and selectivity gas sensor in detecting dissolved gases in transformer oil, in this study, the adsorption of four kinds of gases (H2, CO, C2H2 and CH4) on Pd-graphyne as well as the gas sensing properties evaluation were investigated. The energetically favorable structure of Pd doped γ-Graphyne was first studied, including the comparison of different adsorption sites and discussion of electronic properties. Then, the adsorption of these four molecules on Pd-graphyne was explored. The adsorption structure, adsorption energy, electron transfer and electron distribution, the band structure and density of states were calculated and analyzed. The results show that the Pd atom prefers to be adsorbed on the middle of three C≡C bonds and the band gap is smaller. The CO adsorption exhibits the largest adsorption energy and electron transfer and brings obvious change to the structure and electron properties to Pd-graphyne. Because of the conductance decrease after adsorption CO and acceptable recovery time at high temperature, the Pd-graphyne can be promising gas sensing materials to detect CO with high selectivity. This work offers theoretical support for the design of nanomaterials based gas sensor using novel structure for industrial application.

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.

Bianchi type III string cosmological models (massive and geometric) in presence of magnetic field with vacuum energy density following the techniques used by Letelier (1979) and Stachel (1980) are obtained. We find that the energy conditions (dominant as well as weak) given by Hawking and Ellis (1974) are satisfied for the models. Also the solutions obtained satisfy conservation equation for massive string with magnetic field and vacuum energy density. The models in general, represent anisotropic phase of space-time due to the presence of string. However, the models isotropize at late time and in special case. It has also been shown that the magnetic field is directly linked with the matter. For string dust model, the state finder parameters {r,s} are in excellent agreement with Planck results (Sahni et al. (2003)). The physical and geometrical aspects of the models with special cases are also discussed.

The structural, electronic and magnetochemical properties of the star-shaped polyoxopalladate [Pd₁₅O₁₀(SeO₃)₁₀]¹⁰⁻ (POPd) and its lanthanide functionalized derivatives have been investigated on the basis of density functional theory followed by a ligand field analysis using the Radial Effective Charge (REC) model. Our study predicts that heteroPOPd is a robust cryptand that enforces D_5h symmetry around the encapsulated Ln³⁺ centers. This rigid coordination environment favors interesting potential magnetic behavior in the Er and Ho derivatives, which may be of interest for molecular spintronics and quantum computing applications.

To map Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV 2) spreading and evaluate immune responses variations against this virus, it was essential to locally set up efficient serological tests. The SARS-CoV2 immunogenic proteins were very expensive and not affordable mainly for Low and Middle Income Countries (LMICs). For this purpose, the commonly used antigen, Re-ceptor-Binding Domain (RBD) of Spike S1 protein (S1RBD), was produced using the the Baculovirus Expression Vector System (BEVS) . During the current study, the expression of S1RBD was monitored using western blot under different culture conditions. Different parameters were studied: Multiplicity Of Infection (MOI), cell density at infection and harvest time. Hence, optimal conditions for efficient S1RBD production were identified: MOI 3; cell density at infection 2-3x 106 cells/mL and time post-infection (tpi or harvest time) of 72h and 72-96 h successively for expression in shake-flasks and 7L-bioreactor. A high production yield of S1RBD varying between 4mg and 70 mg per liter of crude cell culture supernatant was achieved, respectively, in shake-flasks and in 7L-bioreactor. Moreover, the produced S1RBD showed an excellent antigenicity potential against COVID-19 patient sera evaluated by western blot. Thus, additional serological assays, such as ELISA, were developed using the purified S1RDB (published by other research groups).

MXenes are two-dimensional nanomaterials isolated from MAX phases by the selective extraction of the A component —a p-block element. The MAX phase exfoliation energy, Eexf, is regarded as a chemical descriptor of the MXene synthesizability. Here we show, by density functional theory estimations of the Eexf values for 486 different MAX phases, that Eexf decreases i) when MAX is a nitride, ii) when going along a d series of the metal M component, iii) when going down a group of the p-block A element, as well as iv) when having thicker MXene phases. Furthermore, Eexf is found to bias, even to govern, the surface chemical activity, as evaluated here on the CO2 adsorption strength, so that more unstable MXenes, displaying larger Eexf values, display a stronger attachment of species upon.

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.

Spiral galaxies and their rotation curves have key characteristics of differentially spinning objects. Oblate spheroid shapes are a consequence of spin and reasonably describe galaxies, indicating that their matter is distributed in gravitationally interacting homeoidal shells. Previously published equations describing differentially spinning oblate spheroids with radially varying density are here applied to 51 galaxies, mostly spirals. A constant volumetric density (rho, kg m-3) is assumed for each thin homeoid in these formulae, after Newton, which is consistent with RC being reported simply as a function of equatorial radius r. We construct parameter-free inverse models that uniquely specify mass inside any given r, and thus directly constrain rho vs. r solely from velocity v(r) and galactic aspect ratios (assumed as 1:10 when data are unavailable). Except for their innermost zones, rho is proven to be closely proportional to rn, where n for all 36 spirals studied equals -1.80±0.40. Our values for interior densities compare closely with independently measured baryon density in appropriate astronomical environments: for example, calculated rho at galactic edges agrees with estimated rho of intergalactic media (IGM). Our finding that central densities increase with galaxy size is consistent with behavior exhibited by diverse self-gravitating entities. Our calculated mass distributions are consistent with visible luminosity and require no non-baryonic component. Empirical luminosity-velocity relationships for galaxies, such as the Tully-Fisher rule, originate in Newtonian physics.

Redox-flow batteries are rechargeable batteries that store energy in two liquid electrolytes, separated by a membrane. During charging and discharging, the electrolytes flow through the membrane and undergo chemical reactions that generate or consume electrical energy. These batteries are known for their scalability and long cycle life and are versatile energy storage technologies developed to enhance efficiency and lower costs. Deep Eutectic Solvents (DES) are eco-friendly alternatives to traditional electrolytes, and their properties have been studied to improve the performance of redox-flow batteries. We investigated choline chloride/ethylene glycol (ChlCl/Eg) mixtures with LiPF6 salt at four concentrations through experimental and MD simulations. The thermophysical and transport properties of the mixture, including density, diffusion coefficient, viscosity, and ionic conductivity, were calculated across a temperature range of 298.15–398.5 K. Our findings indicate that an increase in salt concentration leads to a decrease in diffusion coefficients and ionic conductivity, while increasing the viscosity of the deep eutectic solvent. This research provides valuable insights into the behavior of DES mixtures and can aid in the design and optimization of DES-based processes for use in redox-flow batteries.

The work carried out first-principles calculations within the framework of density functional theory to study the structural stability of the CsSnI₃ compound and the influence of phase transitions on their electronic and optical properties. Using the GGA and SCAN functionals, the relaxed structures of the CsSnI₃ phases were obtained and their geometric characteristics were assessed. Using the Phonopy code based on VASP, calculations of phonon and thermodynamic properties were performed, and the temperatures of phase transitions of CsSnI₃ were determined. The temperature dependences of the thermodynamic parameters α-, β-, γ- and δ-phases of CsSnI₃ were analyzed. The trends in free energy, entropy, enthalpy, heat of formation energy and heat capacity were justified in terms of the pattern of changes in the total energy of the four phases of CsSnI₃ from VASP calculations. It is shown that at 0 K the non-perovskite structure of the CsSnI₃ compound (δ-CsSnI₃) is the most stable (followed by γ-CsSnI₃), and the tetragonal phase (β) is quite unstable, having the highest energy among the perovskite phases. It was revealed that at temperatures above 450 K the tetragonal phase becomes stable, and when the temperature drops, it transforms into the cubic phase (α-CsSnI₃). The phase transition between the β and γ phase of perovskite occurs in the range of 300-320 K, and at 320 K a black-yellow transformation of CsSnI₃ occurs in which the cubic phase (black perovskite) undergoes a phase transition to a non-perovskite conformation (yellow phase). The presence of temperature phase transitions between two orthorhombic phases of CsSnI₃ at 360 K was discovered, although direct transitions of the α⟷γ and γ⟷δ types have not yet been reported in any experiment, except for γ→δ transitions under the influence of moisture. Based on well-relaxed structures (from the SCAN calculations), the band gap widths for four CsSnI₃ phases were calculated and compared with experimental measurements. Electronic properties and Fermi level shifts as a result of phase transformations of CsSnI₃ were assessed using the HSE06 functional and machine learning prediction. The values of the complex dielectric constant and the refractive index of all phases of the CsSnI₃ were determined.

Fire-tolerant eucalypt forests of south eastern Australia are assumed to fully recover from even the most intense fires but surprisingly very few studies have quantitatively assessed that recovery. Accurate assessment of horizontal and vertical attributes of tree crowns after fire is essential to understand the fire’s legacy effects on tree growth and on forest structure. In this study, we quantitatively assessed individual tree crowns 8.5 years after a 2009 wildfire that burnt extensive areas of eucalypt forest in temperate Australia. We used airborne lidar data validated with field measurements to estimate multiple metrics that quantified the cover, density, and vertical distribution of individual-tree crowns in 51 plots of 0.05 ha in fire-tolerant eucalypt forest across four wildfire severity types (unburnt, low, moderate, high). Significant differences in the field-assessed mean height of fire scarring as a proportion of tree height, and in the proportions of trees with epicormic (stem) resprouts were consistent with the gradation in fire severity. Linear mixed-effects models indicated persistent effects of both moderate- and high-severity wildfire on tree crown architecture. Trees at high-severity sites had significantly less crown projection area and live crown width as a proportion of total crown width than those at unburnt and low-severity sites. Significant differences in lidar-based metrics (crown cover, evenness, leaf area density profiles) indicated that tree crowns at moderate- and high-severity sites were comparatively narrow and more evenly distributed down the tree stem. These conical-shaped crowns contrasted sharply with the rounded crowns of trees at unburnt and low-severity sites, and likely influenced both tree productivity and the accuracy of biomass allometric equations for nearly a decade after the fire. Our data provide a clear example of the utility of airborne lidar data for quantifying the impacts of disturbances at the scale of individual trees. Quantified effects of contrasting fire severities on the structure of resprouter tree crowns provide a strong basis for interpreting post-fire patterns in forest canopies and vegetation profiles in lidar and other remotely-sensed data at larger scales.

Although the concept of additive manufacturing has been proposed for several decades, momentum of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization in SLM to obtain high relative density and low surface roughness simultaneously in the previous literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. The statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. It is noted that the effects of the laser power and scanning speed on the above objective quality show highly significant, while hatch space behaves an insignificant impact. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.

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.

It was demonstrated during the past decade that ultra-short intense laser pulse tightly focused deep inside a transparent dielectric generates the energy density in excess of several MJ/cm$^3$. Such energy concentration with extremely high heating and quenching rates leads to unusual solid-plasma-solid transformation paths overcoming kinetic barriers to formation of previously unknown high-pressure material phases, which are preserved in the surrounding pristine crystal. These results were obtained with the pulse of Gaussian shape in space and in time. Recently it was shown that the Bessel-shaped pulse could transform much larger amount of a material and allegedly create even higher energy density than that was achieved with the Gaussian (GB) pulses. Here we present a succinct review of previous results and discuss the possible routes for achieving higher energy density employing the Bessel beams (BB) and take advantage of its unique properties.

Recently, the demand for electric vehicle is increasing worldwide due to eco-friendly policies and stricter emission regulations. As a traction motor for electric vehicle, interior permanent magnet synchronous motors are mainly used. For the design of the interior permanent magnet synchronous motor, the magnetic equivalent circuit method, which is a method of lumped constant circuit, and the finite element method, which is a method of distributed constant circuit, mainly are used. Magnetic equivalent circuit method is useful for simple design through fast and intuitive parameters, but it cannot derive the distribution of magnetic field. The finite element method can derive an accurate magnetic field distribution, but it takes a long time to analyze and it is difficult to analyze intuitive design parameters. In this paper, magnetic equivalent circuit method and Carter coefficient are mixed for rotor structure design. This design method will be called the hybrid magnetic equivalent circuit method. Intuitive design parameters are derived through this hybrid magnetic equivalent circuit method. We will derive the Air gap flux density distribution according to rotor shape, no-load induced voltage, and cogging torque, and compare and verify it with the finite element method.

Using density functional theory (DFT) and the information-theoretic approach (ITA) quantities to appreciate the energetics and properties of biopolymers is still an unaccomplished and ongoing task. To this end, we studied the building blocks of nucleic acid base pairs and small peptides. For base pairs, we have dissected the relative importance of energetic components by using two energy partition schemes in DFT. Our results convincingly show that the exchange-correlation effect predominantly governs the molecular stability of base pairs while the electrostatic potential plays a minor but indispensable role, and the steric effect is trivial. Furthermore, we have revealed that simple density-based ITA functions are in good relationships with molecular polarizabilities for a series of 30 hydrogen-bonded base pairs and all 20 natural α-amino acids, 400 dipeptides, and 8000 tripeptides. Based on these lines, one can easily predict the molecular polarizabilities of larger peptides, even proteins as long as the total molecular wavefunction is available, rather than solving the computationally demanding coupled-perturbed Hartree-Fock (CPHF) equation or its DFT counterpart coupled-perturbed Kohn-Sham (CPKS) equation.

The copolyester of 3-hydroxybutyrate (3HB) and 3-hydoxyhexanoate (3HHx), PHBHHx, is a bi-odegradable plastic that has a high flexibility, softness, wide process window and marine bio-degradability. PHBHHx is usually produced from structurally related carbon sources such as vegetable oils or fatty acids but not from inexpensive carbon sources like sugars. In the previous studies, we demonstrated that engineered strains of hydrogen-oxidizing bacterium, Cupriavidus necator synthesized PHBHHx with high cellular content from not only sugars but also from CO2 as the sole carbon source in the flask culture. In this study, highly efficient production of PHBHHx from CO2 was investigated by pH-stat jar cultivation of the recombinant C. necator strains with feeding the substrate gas mixture (H2/O2/CO2=8:1:1) to complete mineral medium in recycled-gas closed-circuit culture system. As the result with the strain MF01/pBPP-ccrMeJAc-emd, the dry cell mass and PHBHHx concentration reached up to 59.62 ± 3.18 g･L-1 and 49.31 ± 3.14 g･L-1, respectively after 212 h of jar cultivation with limited addition of ammonia and phosphate solutions. The 3HHx composition was close to 10 mol% which is suitable for practical applica-tions. It is expected that autotrophic cultivation of the recombinant C. necator can be a feasible process for mass production of PHBHHx from CO2.

Climate change, increasing global food needs, and decreasing global resources brought a new era to human every-day live with a strong turn to circular economy and sustainability. Food packaging and preservation is an important global sector where enchanced research is carried out. New methods such as active packaging and chemical preservatives replacement are of major interest. Many researchers were published studies about active packaging films, replacement of chemical preservatives with natural originated extracts, and novel incorporation procedures. Sequentially to our and other scientists’ previous work, in this paper we present the results of the improvement which was achieved by incorporating the developed nanohybrid of natural-halloysite/carvacrol-extract, the pure natural carvacrol extract and the commonly used low-density-polyethylene. The well known corona-treatment procedure was employed to produced the optimum final film and the results shown that the low-density-polyethylene incorporated with natural-halloysite/carvacrol-extract nanohybrid and coated external with extra carvacrol extract exhibited aproximatelly 100% higher Young-Modulus values, slightly decreased ultimate strength by 20%, and almost stable elonation at break properties. The water-vapor and oxygen barrier increased by 40%. Finally, the antioxidant activity of the corrona-treated film increased by 28% compared to the similar but untreated product because of the lower release rate of the carvacrol.

The work is devoted to the investigation of virus quasispecies evolution and diversification due to mutations, competition for host cells, and cross-reactive immune responses. The model consists of a nonlocal reaction-diffusion equation for the virus density depending on the genotype considered as a continuous variable and on time. This equation contains two integral terms corresponding to the nonlocal effects of virus interaction with host cells and with immune cells. In the model, a virus strain is represented by a localized solution concentrated around some given genotype. Emergence of new strains corresponds to a periodic wave propagating in the space of genotypes. The conditions of appearance of such waves and their dynamics are described.

Global use of single-use non-biodegradable plastics, like bottles made of polyethylene tereph-thalate (PET), have contributed to catastrophic levels of plastic pollution. Fortunately, microbi-al communities are adapting to assimilate plastic waste. Previously, our work showed a full consortium of five bacteria capable of synergistically degrading PET. Using omics approaches we identified key genes implicated in PET degradation within the consortium’s pangenome and transcriptome. This analysis led to the discovery of a novel PETase, EstB, discovered to hydrolyze oligomer BHET, and polymer PET. Besides genes implicated in PET degradation, many other biodegradation genes were discovered. Over 200 plastic and plasticizer degrada-tion related genes were discovered through the Plastic Microbial Biodegradation Database (PMBD). Diverse carbon source utilization was observed by a microbial community-based as-say, which paired with an abundant number of plastic and plasticizer degrading enzymes in-dicates a promising possibility for mixed plastic degradation. Using RNAseq differential analysis, several genes were predicted to be involved in PET degradation including aldehyde dehydrogenases and several classes of hydrolases. Active transcription of PET monomer me-tabolism was also observed, including the generation of polyhydroxyalkanoate (PHA) bi-opolymers. These results present an exciting opportunity for the bio-recycling of mixed plastic waste with upcycling potential.

In this article, the sol-gel method was used as a synthesis method, which shows the physico –chemical nature of the synthesis of a new complex material ferrit Li0.5MnFe1.5O4. The synthesized structure and structure were determined by the method of X-ray phase analysis. According to the analysis indicators, it was found that our compound is single-phase, spinel-structured, and syngony - cubic type. The microstructure of the compound and the quantitative composition of the elements contained were analyzed under a scanning electron microscope (SEM). Through a scanning electron microscope, Microsystems were taken from different parts of l Li0.5MnFe1.5O4-type crystallite, the elemental composition of crystals was analyzed, and the general type of surface layer of complex ferrite was shown. As a result, the fact that the compound consists of a single phase, the clarity of its construction was determined by the topography and chemical composition of the compound. As a result, it was found that the newly synthesized complex ferrites correspond to the Formula Li0.5MnFe1.5O4. The particles of the formed compounds have a large size (between 50.0 μm, 20.0 μm and 10.0 μm). Electro physical measurements were carried out on the LCR - 800 unit at intervals of 293-483 K and at frequencies of 1.5 and 10 kHz. The increase in frequency to 10 kHz led to a decrease in the value ε in the range of the studied temperature (293-483 K).

In this paper we establish some weighted integral inequalities of Ostrowski, Čebyšev and Lupaş type. Applications for continuous probability density functions supported on infinite intervals with two examples are also given.

The current investigation presents porous ceramic materials prepared of cenospheres prepared by spark plasma sintering. The impact of sintering temperature, mould diameter (20 and 30 mm diameter) and cenosphere size on the properties of the sintered material was investigated. Shrinkage of the samples during sintering started at 900 °C. Sample shrinkage during sintering increases with increasing temperature and decreases with increasing mould size; increasing sample sintering temperature increases the apparent density of all sample series CS 63-150 µm in 20 mm mould from 0.97 to 2.3 g·cm-3 at 1050 - 1300 °C, in 30 mm mould 0.81 - 1.87 g·cm-3 at 1050 - 1200 °C, in 50 mm mould 0.54 - 0.75 g·cm-3 at 1050 - 1150 °C, while CS 150-250 µm in 20 mm mould 0.93 - 1.96 g·cm-3 at 1050 - 1200 °C. Total porosity decreases from 61.5% to 3.9% with increasing sintering temperature from 1050 to 1250 °C, while open porosity reduces at lower temperatures, with closed porosity being highest in samples sintered at 1150 °C. When the sintering temperature increases from 1050 to 1300 °C, the compressive strength of the CS 63-150 samples produced in a 20 mm mould increases from 11 MPa to 312 MPa. These results correlate with the Rice model, which describes an exponential dependence of compressive strength on material porosity and fully dense material compressive strength.

Polychlorinated phenoxathiins (PCPTs), polychlorinated dibenzothiophenes (PCDTs), and polychlorinated thianthrenes (PCTAs) are sulfur analogues of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/DFs). Chlorothiophenols(CTPs) and chlorophenols (CPs) are key precursors to form PCTA/PT/DTs, which can form chloro(thio)phenoxy radical, sulfydryl/hydryl-substituted phenyl radical and (thio)phenoxyl diradicals. The available radical/radical PCTA/DT formation mechanism failed to explain the higher concentration of PCDTs than that of PCTAs under the pyrolysis or combustion conditions. Thus in this work, a detailed thermodynamics and kinetic calculations were carried out to investigate the pre-intermediates formation for PCTA/PT/DTs from radial/molecule coupling of 2-C(T)P with their key radical species. Our study found that the radial/molecule mechanism can thermodynamically and kinetically contribute to the gas-phase formation of PCTA/PT/DT/s. The S/C coupling modes to form thioether-(thio)enol intermediats are preferable over the O/C coupling modes to form ether-(thio)enol intermediats. Thus, although the radial/molecule coupling of chlorophenoxy radical with 2-C(T)P have no effect on the PCDD/PTs formation, the radial/molecule coupling of chlorothiophenoxy radical with 2-C(T)P play an important role in the PCDT/PT formation. Most importantly, the pre-PCDT intermediates formation pathways from the coupling of sulfydryl/hydryl-substituted phenyl radical with 2-C(T)P and the coupling of (thio)phenoxyl diradicals with 2-C(T)P are more favorable to pre-PCTA/PT intermediates formation pathways from the coupling of chlorothiophenoxy radical with 2-C(T)P, which can give reasonable explanation for the high PCDT-to-PCTA ratio in the environment.

The ultrasonic vibration assisted pressing process can improve the fluidity, the uneven distribution of density and particle size of WC-Co powder. However, the microscopic mechanism of ultrasonic vibration on the powder remains unclear. In this paper, WC and Co particles are simulated by three-dimensional spherical models of two particle sizes with the aide of the secondary development of Python. At the same time, the forming process of powder at mesoscale is simulated in the virtue of the finite element analysis software ABAQUS. The influence of vibration amplitude on the fluidity, the filling density and the stress distribution of WC-Co powder is investigated when the ultrasonic vibration is applied to the conventional pressing process. From simulation results, the ultrasonic vibration amplitude has great influences on the density of the compact. With the increase of the ultrasonic amplitude, the compact density also increases gradually. At the initial stage of the compaction, the particles move violently under the action of ultrasonic vibration, the fluidity is obviously enhanced, the arch bridge effect between particles is destroyed, the fine particles quickly fill the pores between the large particles, which increase the density, and the residual stress in the billet decreases after the compaction. From the experimental results, the size distribution of the billet is more uniform, the elastic aftereffect is reduced, the dimensional instability is improved, and the density curves obtained by experiment and simulation are within a reasonable error range.

Learning disorders (LD) are diagnosed in children whose academic skills of reading, writing or mathematics are impaired and lagged according to their age, schooling and intelligence. Children with LD experience substantial working memory (WM) deficits, even more pronounced if more than one of the academic skills is affected. We compared the task-related EEG power spectral density of children with LD (n= 23), with a control group of children with good academic achievement (n= 22), during the performance of a WM task. sLoreta was used to estimate the current distribution at the sources, and 18 brain regions of interests (ROIs) were chosen with an extended version of the eigenvector centrality mapping technique. In this way, we lessen some drawbacks of the traditional EEG at the sensor space by an analysis at the brain sources level over data-driven selected ROIs. Results: The LD group showed fewer correct responses at the WM task, an overall slower EEG with more theta activity in all ROIs, less upper-alpha power at posterior areas, and less high-frequency beta activity in frontal areas. We explain these EEG patterns in LD children as indices of an inefficient neural resource management related with a delay in the neural development.

Low dietary intake of calcium, vitamin D, vitamin C and magnesium has been associated with increased risk of osteoporosis. The purpose of the study was to evaluate changes in several bone health indicators and metabolic biomarkers in postmenopausal women, with high osteopenia or osteoporosis, followed by a nutritional intervention program. 115 apparently healthy postmenopausal women (52±8 years old) were randomized into four groups: group I (n=40) received daily 1000 mg vitamin C, 100 mcg vitamin D3, 500 mg calcium(Ca) and 300 mg magnesium (Mg); group II (n=42) received daily 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg; group III (n=18) received daily 5 mg bisphosphonates, 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg; and group IV (n=15) received daily about 364 mg polyphenols via an innovative functional food (50 g olive paste enriched with mountain tea extract) along with 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg. Groups I -III received supplementation for a year whereas group IV for 5 months. Changes in bone health indicators and metabolic biomarkers were assessed at the beginning and at the end of the study. Anthropometric indices and whole-body bone mineral density (BMD) were also evaluated at the beginning and at the end of the intervention period. The results revealed improved elevated levels of 25(OH)D3, in groups II, III and IV (+3,71% and +1.45% and +5.62% respectively). Significant positive changes were recorded, for whole-body BMD, in all four study groups. Significant beneficial changes for total cholesterol were observed in group IV (-2.07%, P<0.05) and positive changes in group I for HDL biomarker (+61.62%, P<0.05). Additional larger-scale clinical trials and intervention studies are considered essential, to fully investigate and elucidate associations between dietary components and biochemical indices of bone health.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.

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.

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%.

The study of photonic crystals has emerged as an attractive area of research in nanoscience in the last years. In this work we study the properties of a two-dimensional photonic crystal composed of dielectric rods. The unit cell of the system is composed of six rods organized on the sites of a C6 triangular lattice. We induce a topological phase by introducing an angular perturbation ϕ in the pristine system. The topology of the system is then determined by using the so-called k.p perturbed model. Our results show that the system presents a topological and a trivial phases, depending on the sign of the angular perturbation ϕ. The topological character of the system is probed by evaluating the electromagnetic energy density and analyzing its distribution in the real space, in particular on the maximal Wyckoff points. We also find two edge modes at the interface between the trivial and topological photonic crystals, which present a pseudospin topological behavior. By applying the Bulk-Edge correspondence, we study the pseudospin edge modes and conclude that they are robust against defects, disorder and reflection. Moreover, the localization of the edge modes leads to the confinement of light and the interface behaves as a waveguide for the propagation of electromagnetic waves. Finally, we show that the two edge modes present energy flux propagating in opposite directions, which is the photonic analogue of the quantum spin Hall effect.

Hydrogen-bond (H-bond) energies in 310-helices of short alanine peptides were systematically examined by precise DFT calculations with the negative fragmentation approach (NFA), a modified method based on the molecular tailoring approach. The contribution of each H-bond was evaluated in detail from the 310-helical conformation of total energies (whole helical model; WH3-10 model), and the results were compared with the property of H-bond in a-helix from our previous study. The H-bond energies of the WH3-10 model exhibited tendencies different from those exhibited by the -helix, in that they depended on the helical position of the relevant H-bond pair. H-bond pairs adjacent to the terminal H-bond pairs were observed to be strongly destabilized. The analysis of electronic structures indicated that structural characteristics cause the destabilization of the H-bond in 310-helices. We also found that the longer the helix length, the more stable the H-bond in the terminal pairs of the WH3-10 model, suggesting the action of H-bond cooperativity.

Celiac disease (CD) is an autoimmune disorder triggered by gluten ingestion in genetically predisposed individuals. In addition to the typical gastrointestinal symptoms such as diarrhea, bloating, or chronic abdominal pain, CD may also present a wide spectrum of manifestations, including low bone mineral density (BMD) and osteoporosis. This review aims to describe the role of CD in the development of skeletal alterations, underlying important clinical aspects and therapeutic implications. The etiopathology of bone lesions in CD is multifactorial and their management is challenging. Here, we provide gastroenterologists and orthopedics with an up-to-date overview on the link between CD and osteoporosis to improve the management of the CD condition.

Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure and dynamics. Here, we introduce the multiscale emergent functional state, which can be represented as a network where links encode the flow exchange between the nodes, calculated using diffusion processes on top of the network. We analyze the emergent functional state to study the distribution of the flow among components of 92 fungal networks, identifying their functional modules at different scales and, more importantly, demonstrating the importance of functional modules for information content of networks, quantified in terms of network spectral entropy. Our results suggest that the topological complexity of fungal networks guarantees the existence of functional modules at different scales keeping the information entropy, and functional diversity, high.

We work with reference to a well-known semiclassical model, in which quantum degrees of freedom interact with classical ones. We show that, in the classical limit, it is possible to represent classical results (e.g., classical chaos) by means a pure-state density matrix.

Crowd density estimation is an important task for crowd monitoring. Many efforts have been done to automate the process of estimating crowd density from images and videos. Despite series of efforts, it remains a challenging task. In this paper, we proposes a new texture feature-based approach for the estimation of crowd density based on Completed Local Binary Pattern (CLBP). We first divide the image into blocks and then re-divide the blocks into cells. For each cell, we compute CLBP and then concatenate them to describe the texture of the corresponding block. We then train a multi-class Support Vector Machine (SVM) classifier, which classifies each block of image into one of four categories, i.e. Very Low, Low, Medium, and High. We evaluate our technique on the PETS 2009 dataset, and from the experiments, we show to achieve 95% accuracy for the proposed descriptor. We also compare other state-of-the-art texture descriptors and from the experimental results, we show that our proposed method outperforms other state-of-the-art methods.

This paper considers estimating the ratio of two distributions with different parameters and common supports. We consider a Bayesian approach based on the Log--Huber loss function which is resistant to outliers and useful to find robust M-estimators. We propose two different types of Bayesian density ratio estimators and compare their performance in terms of Bayesian risk function with themselves as well as the usual plug-in density ratio estimators. Some applications such as classification and divergence function estimation are addressed.

In the present work, a superlattice structure comprising superconducting and insulator layers is studied. Here, if a magnetic field is applied parallel to the layers, the lack of a pinning center leads to a novel transition; in particular, as the applied magnetic field is reduced, the stationary wave surrounding the magnetic flux quantum in the superconducting layer eventually collides with the superconducting–insulating interfaces on both sides because its radius becomes larger than the width of the superconducting layer. At this instant, the stationary wave will collapse, and a transition will occur: the magnetic quanta are collapsed and thus the uniform magnetic field distribution is achieved, which corresponds to the transition from the superconducting state to the normal state over critical current. Considering a one-dimensional model of the structure, a critical current density equation is derived that indicates an increase in the critical current density for increased applied magnetic field. Subsequently, the same calculation was conducted after changing the direction of the magnetic field component, and the combination of these two calculations expresses the anisotropic property of the structure. The phenomenon is also predicted for anisotropic critical current density. This phenomenon is an important discovery that helps manufacture high-temperature superconducting tape as well as large high-temperature superconducting coils.

Low-lying coastal communities are often threatened by compound flooding (CF), which can be determined through the joint occurrence of storm surges, rainfall and river discharge either successively or in close succession. The trivariate distribution can demonstrate the risk of the compound phenomenon more realistically rather than considering each contributing factor independently or in a pairwise dependency. Recently vine copula has been recognized as the highly flexible approach to constructing a higher dimensional joint density framework. In such construction, parametric class copula with parametric univariate marginal distributions is often involved. Such incorporation can lack flexibility due to parametric functions with prior distribution assumptions about their univariate marginal and/or copula joint density. This study introduces the vine copula approach in a nonparametric setting by introducing Bernstein and Beta kernel copula density in establishing trivariate flood dependence. The proposed model is applied to 46 years of flood characteristics collected on the west coast of Canada. The univariate flood marginal distribution is modelled using nonparametric kernel density estimation (KDE). The 2-D Bernstein estimator and Beta kernel copulas estimator are tested independently in capturing pairwise dependencies to establish D-vine structure in a stage-wise nesting approach in three alternative ways, each by permutating the location of the conditioning variable. The best-fitted vine structure is selected using goodness-of-fit (GOF) test statistics. The performance of the nonparametric vine approach is also compared with the vine constructed in the parametric and semiparametric fitting procedure. Investigation reveals that the D-vine constructed using Bernstein copula with normal KDE marginals nonparametrically performed well in capturing dependence of the compound events. Finally, the derived nonparametric model is used in the estimation of trivariate OR- and AND-joint return periods, further employed in estimating failure probability (FP) statistics. The trivariate return periods for the AND-joint case are higher than for the OR-joint case for the same flood combination. Also, the trivariate flood hazard results in a high-value FP than bivariate and univariate events. Ignoring the trivariate dependence could result in the underestimation of FP

new subsonic blower wind tunnel design has been studied both numerically and experimentally, it is also referred to as “blower” wind tunnel. This paper, is initially aimed to address each sequential stage of the wind tunnel design process. Rather than applying the standard method of modelling solely the flow in the test section, a large-scale CFD model of the whole wind tunnel was employed. The loss of every constituent element was calculated and then all the losses are added up to determine the power needed for the wind tunnel operation which is used as “intake fan” boundary conditions in the CFD model. Then, flow uniformity and turbulent intensity measurements in an empty test section using a Pitot-static tube and hot wire anemometer (HWA) were introduced to validate the CFD results. The results showed that flow quality was significantly affected by boundary layer controllers (honeycomb and mesh screens) in the settling chamber and wide-angle diffuser. Investigations were also conducted to evaluate the flow deficit in the wake area behind a convex hump model using HWA. This was additional experimental tests carried out to validate the suitability of the wind tunnel flow aerodynamic research.

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

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

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.

Prebiotic organic synthesis reactions catalyzed by Earth-abundant metal sulfides are key processes for understanding the evolution of biochemistry from inorganic molecules, yet the catalytic functions of sulfides have remained poorly explored in the context of the origins of life. Past studies on prebiotic chemistry have mostly focused on a few types of metal sulfide catalysts, such as FeS or NiS, which form limited types of products with inferior activity and selectivity. To explore the potential of metal sulfides on catalyzing prebiotic chemical reactions, here, the chemical diversity (variations in chemical composition and phase structure) of 304 natural metal sulfide minerals in a mineralogy database was surveyed and approaches to rationally predict the catalytic functions of metal sulfides are discussed based on advanced theories and analytical tools of electrocatalysis such as proton-coupled electron transfer, structural comparisons between enzymes and minerals, and in-situ spectroscopy. To this end, we introduce a model of geo-electrochemistry driven prebiotic synthesis for chemical evolution, as it helps us to predict kinetics and selectivity of targeted prebiotic chemistry under “chemically messy conditions”. We expect that combining the data-mining of mineral databases with experimental methods and theories developed in the field of electrocatalysis will facilitate the prediction and verification of catalytic performance under a wide range of pH and Eh conditions, and aid in the rational screening of mineral catalysts involved in the origins of life.

We propose a model for gravity based on the gravitational polarization of space. With this model, we can relate the density parameters within the Friedmann model, and show that dark matter is bound mass formed from massive dipoles set up within the vacuum surrounding ordinary matter. Aggregate matter induces a gravitational field within the surrounding space, which reinforces the original field. Dark energy, on the other hand, is the energy density associated with gravitational fields both for ordinary matter, and bound, or induced dipole matter. At high CBR temperatures, the cosmic susceptibility, induced by ordinary matter vanishes, as it is a smeared or average value for the cosmos as a whole. Even though gravitational dipoles do exist, no large scale alignment or ordering is possible. Our model assumes that space, i.e., the vacuum, is filled with a vast assembly (sea) of positive and negative mass particles having Planck mass, called planckions, which is based on extensive work by Winterberg. These original particles form a very stiff two component superfluid, where positive and negative mass species neutralize one another already at the submicroscopic level, leading to zero net mass, zero net gravitational pressure, and zero net entropy, for the undisturbed medium. It is theorized that the gravitational dipoles form from such material positive and negative particles, and moreover, this causes an intrinsic polarization of the vacuum for the universe as a whole. We calculate that in the present epoch, the smeared or average susceptibility of the cosmos equals, , and the overall resulting polarization equals, . Moreover, due to all the ordinary mass in the universe, made up of quarks and leptons, we calculate a net gravitational field having magnitude, . This smeared or average value permeates all of space, and can be deduced by any observer, irrespective of location within the universe. This net gravitational field is forced upon us by Gauss’s law, and although technically a surface gravitational field, it is argued that this surface, smeared value holds point for point in the observable universe. A complete theory of gravitational polarization is presented. In contrast to electrostatics, gravistatics leads to anti-screening of the original source field, increasing the original value, , to, , where is the induced or polarized field. In the present epoch, this leads to a bound mass, , where is the sum of all ordinary source matter in the universe, and equals the relative permittivity. A new radius, and new mass, for the observable universe is dictated by the density parameters in Friedmann's equation, and Gauss’s law. These lead to the very precise values, , and, , respectively, somewhat larger than current less accurate estimates.

Bipolar disorder is a severe mood disorder and is one of the top 20 reasons of disability in the world. It causes a huge burden on society. In this study, the prediction models of bipolar disorder were constructed based on the concept of knowledge distillation. The input data consisted of patients of bipolar disorder and matched controls, all of which were selected from the open database MIMIC. The method of kernel density estimation (KDE) was exploited to generate probability density functions (PDF) which identify distributions of input data. The PDF values referred to as the soft labels were combined with the input data to construct the prediction models of bipolar disorder using decision tree and artificial neural network respectively. According to the evaluation results, indicators for identifying positive samples of bipolar disorder were improved. Meanwhile, the indicators for identifying negative samples have also been advanced. In addition, the branching attributes selected by the decision trees can be mapped back to specific disease diagnoses, which are all associated with bipolar disorder. In conclusion, using KDE to generate the soft label information of the input data can make knowledge distillation work and has improved the performances of prediction models for bipolar disorder.

In swarm-robotics foraging, the purpose of task allocation is to adjust the number of active foraging robots dynamically based on the task demands and changing environment. It is a difficult challenge to generate self-organized foraging behavior in which each robot can adapt to environmental changes. To complete the foraging task efficiently, this paper presents a novel self-organized task allocation strategy known as the dynamic response threshold model (DRTM). To adjust the behavior of the active foraging robots, the proposed DRTM newly introduces the traffic flow density, which can be used to evaluate the robot density. First, the traffic flow density and the amount of obstacle avoidance are used to adjust the threshold which determines the tendency of a robot to respond to a stimulus in the environment. Then, each individual robot uses the threshold and external stimulus to calculate the foraging probability that determines whether or not to go foraging. Simulation and physical experiments are carried out to evaluate the performance of the proposed method. The experimental results show that the DRTM is superior to and more efficient than the adaptive response threshold model (ARTM) in swarm foraging.

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.

Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial ingredients for enabling comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based ‘digital twin’ approach which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves towards larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space. At the same time, the retention rate of a rotationally actuated CP-DF siphon valve and, most challenging, its band width related to unavoidable tolerances of experimental input parameters, need to slot into a defined interval of the practically allowed frequency envelope. To accomplish particular design goals, a set of parametrized metrics is defined, which are to be met within their practical boundaries while (numerically) minimizing the band width in the frequency domain. While each LSI scenario needs to be addressed individually on the basis of the digital twin, a suite of qualitative design rules and instructive showcases structures are presented.

The Sulfur Dioxide (SO2) compound is a primary environmental pollutant worldwide, whereas elemental Sulfur (S) is a global commodity possessing a variety of industrial as well as commercial functions. The chemical relationship between poisonous SO2 and commercially viable elemental S has motivated this investigation using Density Functional Theory calculation of the relative transition state barriers for the 2-step Dehydro-sulfurization oxidation-reduction reaction. Additionally, doubly-charged nanoscale platelet Molybdenum Disulfide (MoS2), Armchair (6,6) Carbon Nanotube, 28-atom Graphene nanoflake (GR-28), and Fullerene C-60 are utilized as catalysts. The optimal heterogeneous and homogeneous catalysis pathways of the 2-step oxidation-reduction from SO2 to elemental S are further inspired by the biomimicry of the honeybee species multi-step bio-catalysis of pollen conversion to organic honey. Potential applications include environmental depollution, the mining of elemental sulfur, and the functionalization of novel technologies such as the recently patented aerial and amphibious Lynchpin TM drones.

Some evidence supports the influence of the implant macro-design and primary stability. Additionally, tactile perception can be used to assess implant stability when placing the implant. This research aimed to quantify the primary and secondary stability of three implant systems with two different macro geometries (cylindrical and conical) determined through the insertion torque and the implant stability quotient (ISQ) at the moment of implant placement as a function of implant-related factors (length, width, dental arch, and implant location in the arch), intraoperative factors (bone density determined subjectively by the clinician's tactile perception), and patient-related factors (age, gender and bone density determined objectively in the cone beam computed tomography (CBCT). Methods: 102 implants of three implant systems with two different macro geometries (conical and cylindrical) were placed in 53 patients. The insertion torque, the ISQ at the implant placement (ISQ0), and bone quality according to the clinician's tactile sensation were recorded on the day of the surgery. After a three-month healing period, the ISQ was re-evaluated (ISQ3). Results: Cylindrical implants exhibited significantly higher insertion torque and ISQ at the moment of the surgery and after three months than conical implants. Cylindrical implants also showed significantly lower indices of tactile evaluation of bone quality during the implant placement surgery. However, no differences were demonstrated in the bone density measured objectively in the CBCT. (4) Conclusions: The cylindrical implants achieved the highest values for primary stability (Ncm and ISQ) and secondary stability (ISQ after three months). Insertion torque was the variable that most influenced ISQ on the day of the surgery. Implant location (incisors-canines, bicuspids-molars) and the implant macro geometry were the variables that most influenced the secondary stability (ISQ at three months).

We primarily investigate the existence of solutions for fractional neutral integro-differential equations subjected to Neumann-type boundary conditions, which is crucial for understanding natural phenomena. Taking into account factors such as neutral type, fractional-order integrals, and fractional-order derivatives, we employ probability density functions, Laplace transforms, and resolvent operators to formulate a well-defined concept of a mild solution for the specified equation. Following this, by integrating fixed point theorems, we establish the existence of mild solutions under more relaxed conditions.

Transportation is the primary consumer of oil, accounting for a significant portion of global energy consumption (34%) and CO2 emissions (40%). Electrifying road transportation is crucial to mitigate the effects of global warming. The abundant potential of renewable energy sources like solar and wind is hindered by their intermittent nature and incongruity with peak energy demands. This calls for the development of sophisticated energy storage solutions. Metal-air batteries (MABs), emerging as viable alternatives to lithium-ion batteries (LIBs), have attracted considerable attention due to their promising applications in the transportation sector. Despite substantial progress in MAB development over the past two decades, overcoming critical challenges such as electrolyte decomposition, carbon cathode degradation, anodic dendrite growth, and air impurities remains essential for their commercial viability. This mini-review provides a comprehensive overview of MAB fundamentals and the challenges associated with their development. The insights presented in this review serve to illuminate the current landscape and future prospects of MABs in the transportation sector.

This paper presents the tensor properties of joint probability densities on a Riemannian manifold. Initially we develop a binary data matrix to record variables' values of a large number of particles confining in a closed system at a certain time in order to retrieve the joint probability densities of related variables. By introducing the particle oriented coordinate and generalized inner product as a multi-linear operation on the basis of this coordinate, we extract the set of joint probabilities and prove them to meet covariant tensor properties on a general Riemannian space of variables. Based on the Taylor expansion of scalar field in Riemannian manifolds, it has been shown that the symmetrized iterative covariant derivatives of cumulative probability function defined on Riemannian manifold also gives the set of related joint probability densities equivalent to the aforementioned multi-linear method. We show these covariant tensors reduce to classical ordinary partial derivatives in ordinary Euclidean space with Cartesian coordinates and gives the formal definition of joint probabilities by partial derivatives of cumulative distribution function. The equivalence between symmetrized covariant derivative and generalized inner product has been concluded. Some examples of well-known physical tensors clarify that many deterministic physical variables are presented as tensor densities with an interpretation similar to probability densities.

A 4×2 factorial experiment was conducted to evaluate the potential of feeding dietary gamma-oryzanol and vitamin E tocotrienols in hens reared in 840 (low cage density; LCD) or 420 cm2/hen (high cage density; HCD). A total of 120 hens were allocated into eight groups with five replicates. Diets were a control (CON) or the control diet supplemented with 200 ppm gamma-oryzanol (GO-200), 200 ppm vitamin E tocotrienols (VE-200) or 200 ppm gamma-oryzanol + 200 ppm vitamin E tocotrienols (GE-400). Results showed that HCD-housed hens decreased (P < 0.01) egg performance and quality. Average egg weight (AEW), egg mass and FCR improved in all supplemented treatments. Results on the AEW, FCR, and eggshell qualities of birds kept at the HCD revealed the best responses in the GE-400 group (P < 0.01). Among hens kept on an HCD, there was a noticeable decrease in HMGCR mRNA abundance in the VE-200 group, while the highest IFN-γ mRNA abundance was found in hens fed the GO-200 diet (P < 0.05). Thus, this study suggested that dietary GO or VE at 200 ppm either individually or in combination could improve performance and egg quality as well as regulate the abundance of immune- and stress-related genes.

The pinning force density FpJc,B=Jc×B (where Jc is the critical current density and B is the applied magnetic field) is one of the main parameters that characterize the resilience of a superconductor to carry a dissipative-free transport current in an applied magnetic field. Kramer (1973 J. Appl. Phys. 44 1360), and Dew-Hughes (1974 Phil. Mag. 30 293) proposed a widely used scaling law for the pinning force density amplitude: FpB=Fp,max×p+qp+qppqq×BBc2p×1-BBc2q, where Fp,max, Bc2, p, and q are free-fitting parameters. Since the late 1970-s till now, several research groups have reported experimental data on the dependence of Fp,max on the average grain size, d, in Nb3Sn-based conductors. Godeke (2006 Supercond. Sci. Techn. 19 R68) proposed that the dependence obeys the law Fp,maxd=A×ln1d+B. However, this scaling law has several problems, for instance, the logarithm is taken from a non-dimensionless variable, and Fp,maxd<0 for large grain sizes, and Fp,maxd→∞ for d→0. Here, we reanalysed the full inventory of publicly available Fp,maxd data for Nb3Sn conductors and found that the dependence can be described by Fp,maxd=Fp,max0×exp-dδ law, where the characteristic length, δ, varies within a remarkably narrow range, that is, δ=175±13 nm, for samples fabricated by different technologies. The interpretation of the result is based on the idea that the in-field supercurrent flows within a thin surface layer (thickness of δ) near the grain boundary surfaces (similar to London’s law, where the self-field supercurrent flows within a thin surface layer with a thickness of the London penetration depth, λ, and the surface is a superconductor-vacuum surface). An alternative interpretation is that δ represents the characteristic length of the exponential decay flux pinning potential from the dominant defects in Nb3Sn superconductors, which are grain boundaries.

High-level quantum-chemical computations (G4MP2) are carried out in the study of complexes featuring tetrel bonding between the carbon atom in the carbenoid CB11H11 - obtained by hydride removal in the C-H bond of the known closo-monocarbadodecaborate anion CB11H12() and acting as Lewis acid (LA) - and Lewis bases (LB) of different type; the electron donor groups in the tetrel bond feature carbon, nitrogen, oxygen, fluorine, silicon, phosphorus, sulphur and chlorine atomic centers in neutral molecules as well as anions H(-), OH(-) and F(-). The empty radial 2pr vacant orbital on the carbon center in CB11H11 , which corresponds to the LUMO, acts as a Lewis acid or electron attractor, as shown by the molecular electrostatic potential (MEP) and electron localization funcion (ELF). The thermochemistry and topological analysis of the complexes {CB11H11:LB} are comprehensively analyzed, and classified according to sharing or closed-shell interactions. ELF analysis shows that the tetrel C···X bond ranges from very polarised bonds, as in H11B11C:F() to very weak interactions as in H11B11C···FH and H11B11C···O=C=O.

We have an aversion to density in America. Density is a continual trope in this country, blamed for all of the ills of urban life, from crime and racial unrest in the middle of the 20th century to public health concerns today. In the early stages of the COVID pandemic density was the culprit, even though we’ve subsequently seen outbreaks in rural areas and sprawling cities across the United States. This paper will look into the root of America’s problems with density and argue that density is not the problem but the solution to the challenges of today’s and tomorrow’s cities. As we deplete the resources of the planet, density is our most direct pathway to recover some balance with nature. Dense living is more efficient, less carbon intensive and more environmentally sustainable. As geospatial differentiations matter less due to advances in communication technology, it's the density of people and ideas that will continue to fuel innovation. Finally, in a world that is increasingly dominated by pluralism, denser living promotes openness, tolerance and diversity.

Rapid increase in digital data coupled with advances in deep learning algorithms is opening unprecedented opportunities for incorporating multiple data sources for modeling spatial dynamics of human infectious diseases. We used Convolutional Neural Networks (CNN) in conjunction with satellite imagery-based urban housing and socio-economic data to predict disease density in a developing country setting. We explored both single (uni) and multiple input (multimodality) network architectures for this purpose. We achieved maximum test set accuracy of 81.6 per cent using a single input CNN model built with one convolutional layer and trained using housing image data. However, this fairly good performance was biased in favor of specific disease density classes due to an unbalanced data set despite our use of methods to address the problem. These results suggest CNN are promising for modeling spatial dynamics of human infectious diseases, especially in a developing country setting. Urban housing signals extracted from satellite imagery seem suitable for this purpose, under the same context.

Hydroxyapatite (HAP) is the main mineral component of bones and teeth. It is widely used in medicine as a bone filler and coating for implants to promote new bone growth. Ion substitutions into the HAP structure highly affect its properties. One of the important substituents is manganese. This paper presents the new results obtained by high-precision density functional theory calculations using hybrid functionals, for studies of the Mn/Ca substitutions in HAP in a wide manganese concentration range within 2x2x2 supercell model. The experimental data on the mechanochemical synthesis of HAP-Mn samples with different Mn concentrations are also presented. The comparison between experiment and theory showed good agreement: the HAP-Mg unit cell parameters and volume decrease with increasing degree of Mn/Ca substitution. It is shown that electronic energy levels appear inside the band gap Eg of HAP, which depend on the concentration of Mn and change the photo-excitation energy of HAP, making its effective value Eg* less than the band gap Eg, and generally changing the photoelectronic properties of HAP. It was established that the energies of formation of the substitutions Mn/Ca depend on the position of the Ca atom (Ca1 or Ca2) and on the concentration of manganese. It has been shown that the replacement of calcium cations with manganese occurs predominantly at the Ca2 position.

The hard open problem of finding the lower bound for the Fokker Planck Kolmogorov’s time-dependent controller parameter probability density function is addressed for the first time in literature in this work. This revolutionary exposition will put control theory and other related inter-disciplinary fields to a higher level towards contemporary control theory. Notably, based on the influential role of control theory in both engineering and industry, this paper will be of great value to all engineering and industry professionals who seek to know more about advanced trends within control theory settings. On the other remit of the spectrum, Fokker Planck Kolmogorov(FPK) equations are of high importance to physicists as well as mathematicians, based on their multiple applicability to multi-interdisciplinary fields of human knowledge, and beyond. So, this by default adds more taste and credibility to this study. Concluding thoughts are included at the end of the work along with a difficult outstanding problem and the direction of future work.

Optimum design and accurate control of the internal structure of the laser target materials remain an important goal for various laser physics experiments, especially for generating high flux photon and neutron beams. The low-density material is considered to be one of the most difficult for X-ray study due to its high transparency and imperceptible contrast. To produce clear visualization of foam containing sparse structures we used a high-quality monochromatic X-ray beam of synchrotron radiation source PETRA-III at DESY. The X-ray beam parameters allow tomographic scanning with application of phase contrast retrieval algorithms. A series of 3D images of foam-suspended glass microsphere inside the plastic cylinder were obtained with the quality high enough to observe the internal structure and to visualize uniformity, displacement and surface roughness on both sides of the microsphere. The main object under investigation was a CH-plastic capillary including 10 mg/cc CHO-foam with the centered glass microsphere. The results of this work demonstrate that tomographic visualization based on a high quality X-ray radiation and phase contrast analysis is an effective and useful technique for development of new laser targets containing structured low density materials.

This paper presents sufficient conditions for almost global stability of nonlinear switched systems consisting of both stable and unstable subsystems. Techniques from the stability analysis of switched systems have been combined with the multiple Lyapunov density approach - recently proposed by the authors for the almost global stability of nonlinear switched systems composed of stable subsystems. By using slow switching for stable subsystems and fast switching for unstable subsystems lower and upper bounds for mode-dependent average dwell times are obtained. In addition to that, by allowing each subsystem to perform slow switching and using some restrictions on total operation time of unstable subsystems and stable subsystems, we have obtained a lower bound for an average dwell time.

With reference to Planck scale, increasing support for large scale cosmic anisotropy and preferred directions and by considering an increasing ratio of Hubble parameter to angular velocity, right from the beginning of Planck scale, we make an attempt to estimate ordinary matter density ratio, dark matter density ratio, mass, radius, temperature, age and expansion velocity (from and about the baby universe in all directions). We would like suggest that, from the beginning of Planck scale, 1) Dark matter can be considered as a kind of cosmic foam responsible for formation of galaxies. 2) Cosmic angular velocity decreases with square of the decreasing cosmic temperature. 3) Increasing ratio of Hubble parameter to angular velocity plays a crucial role in estimating increasing cosmic expansion velocity and decreasing density ratios of dark matter and ordinary matter. 4) There is no need to consider dark energy for understanding cosmic acceleration.

Estrogens play a protective role during early life stages. However, endogenous 17β-estradiol (E2) can accelerate atherosclerosis progression in low-grade inflammatory conditions like established atherosclerosis. Our single-center cohort study assessed sex-specific associations of gonadal hormones with oxidative stress, inflammation, and myocardial injury markers in 111 patients (37% women) diagnosed with acute myocardial infarction (MI) between July 2011 and December 2013. Blood samples were collected within 48 hours of symptom onset, and we measured sex steroids (E2, total testosterone [T]), oxidized low-density lipoproteins, high-sensitive C-reactive protein (CRP), white blood cell counts (WBC), and cardiac enzymes (creatine kinase [CK], the CK Muscle-Brain fraction [CK-MB], and high-sensitive troponin T [hsTnT]). The SYNTAX score gauged coronary disease severity from coronary angiography results. In men with acute MI, peak cardiac enzyme levels were predicted by post-percutaneous coronary intervention (PCI) E2 plasma levels (OR 1.011, p=0.047 - CK; OR 1.018, p=0.013 - CK- MB; OR 1.019, p=0.005 - TnT), peak WBC count (OR 1.487, p=0.015 - CK ; OR 1,709, p=0,005 - CK- MB; OR 1.391, p=0.012 - TnT), and peak CRP plasma levels (OR 1.040, p=0.033 - CK; OR 1.024, p=0.029 - CK-MB; OR 1.063, p=0.006 - TnT). T levels and E2/T ratio were associated with post-PCI CRP in these men (OR 0.980, p = 0.024 - T, OR 1.010, p = 0.076 - CRP). For women, peak WBC was a marker of highest testosterone (OR 1.348, p = 0.062), and only WBC was a significant indicator of myocardial injury extent (OR 1.426, p=0.039 - CK; OR 1.384, p=0.036 - CK-MB; OR 1.299, p=0.048 - TnT). During acute MI, elevated endogenous estradiol levels correlate with myocardial necrosis severity in men, while in women, increased leukocyte levels indicate acute myocardial damage. Elevated plasma T is associated with increased WBC in women. In men, post-PCI plasma CRP specifically indicates endogenous T levels and E2/T ratio during the acute phase.

In the context of the Korean building structure standard KDS2022, wind loads can be readily calculated in terms of the along-wind, across-wind, and torsional components, based on a single wind direction. However, this approach falls short in accurately and safely evaluating the impact of winds from various directions. Therefore, in this study, we developed a Wind Load Calculation Program (WCP) capable of predicting wind loads with relative precision during the preliminary design phase. First, wind tunnel tests were conducted to identify the essential factors necessary for calculating wind loads and the variables influencing these factors. The building shape considered was a square, and the wind force coefficients and power spectral density were measured by combining 4 ground roughness values, 11 side ratios (), 4 aspect ratios (), and wind directions ranging from 0° to 90°. Subsequently, a generalized formulation was devised to facilitate wind load calculations across diverse conditions and a method for calculating load combination coefficients, considering response correlation and load simultaneity, was presented. Finally, the wind loads obtained from the wind tunnel tests were compared with those predicted by the WCP using an actual project model.

The Density Wave Theory, which aims to explain the formation of spiral arms in disc galaxies, has been subject to discussion. According to this theory, at the co-rotation circle, the rotational velocity of the density waves or spiral arms matches that of the galactic matter. Consequently, this alignment should impede the formation of new stars within this co-rotation circle, leading to the presence of dark or dim gaps within the spiral arms. Additionally, the theory predicts the occurrence of the front side trail effect in the inner region of the co-rotation circle and the rear side trail effect in the outer region. However, despite these expectations, no such spiral patterns have been observed, prompting the need for revision or reconsideration of the Density Wave Theory.

In view of the preparation for a post-LHC collider, the high-energy physics (HEP) community started from 2010 to discuss various options, including the use of HTS for very high field dipoles. Therefore, a small program was set in Europe aiming at exploring the possibility of using HTS for accelerator quality magnets. Based on various EU funded programs, though at modest levels, has enabled the European community of accelerator magnets to start getting experience in HTS and addressing a few issues. The program was based on use of REBCO tapes to form 10 kA Roebel cables, to be used to wind small dipoles of 30-40 mm aperture in the 5 T range. The dipoles are designed to be later inserted in a background dipole field (in Nb3Sn), to reach eventually a field level in the 16-20 T range, beyond the reach of LTS. The program is currently underway: more than 1 km tape of high performance (Je > 500 A/mm2 at 20 T, 4.2 K has been manufactured and characterized, various 30 m long Roebel cables have been assembled and validated up to 13 kA, a few dipoles have been wound and tested, reaching at present 4.5 T in stand-alone (while a dipole made from race track coils with no-bore exceeded 5 T using stacked tape cable) and a test in a background field is being organized.

Real-time evolution of the electron densities under excitations in La₂CuO₄ was calculated by the time-dependent density functional theory (TDDFT). The author found, for the first time, under excitations, the electron cloud of Cu²⁺ changes obviously and the characteristic frequencies are 83 meV and 36 meV, respectively, for two different modes. The results are unexpected and close to that of lattice vibrations. The results show that the electron cloud of Cu²⁺ (just like the lattice) can be the electron-pairing medium in high temperature copper oxide superconductors.

There are currently around 78 Nuclear Power Plants (NPP) in the world based on Boiling Water Reactors (BWR). The current parameter to assess BWR instability issues is the linear Decay Ratio (DR). However, it is well known that BWRs are complex non-linear dynamical systems that may even exhibit chaotic dynamics that normally preclude the use of the DR when the BWR is working at a specific operating point during instability. In this work a novel methodology based on an adaptive Shannon Entropy estimator and on Noise Assisted Empirical Mode Decomposition variants is presented. This methodology was developed for real-time implementation of a stability monitor. This methodology was applied to a set of signals stemming from several NPPs reactors (Ringhals-Sweden, Forsmark-Sweden and Laguna Verde-Mexico) under commercial operating conditions, that experienced instabilities events, each one of a different nature

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).

The total enthalpies of the 16 different spin configurations that can be realized in the unit cell of the archetype spin crossover complex [Fe(phen)₂(NCS)₂] (phen=1,2-phenanthroline) were calculated applying periodic density functional theory combined with the Hubbard model and the Grimme-D2 dispersion correction (DFT+U/D2). The obtained enthalpy differences between the individual spin configurations were used to determine spin couplings of an Ising-like model and subsequent Monte Carlo simulations for this model allowed to estimate the phenomenological interaction parameter Г of the Slichter-Drickamer model, which is commonly used to describe the cooperativity of the spin transition. The calculational procedure described here, which led to an estimate of about 3 kJ/mol⁻¹ for Г, in good agreement with experiment, may be used to predict from first principles how modifications of spin crossover complexes can change the character of the spin transition from gradual to abrupt and vice versa.

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.

Background: The mechanisms underlying the effect of estradiol (E2) on low-density lipoprotein cholesterol (LDL-C) levels are not completely understood, although a role for proprotein con-vertase subtilisin/kexin type 9 (PCSK9) has been proposed. We aimed to investigate the association between levels of E2, PCSK9 and lipid parameters in premenopausal women undergoing in vitro fertilization (IVF). Methods: Healthy women undergoing IVF in the Department of Obstetrics and Gynecology of the University General Hospital of Ioannina were recruited. Levels of E2, pro-protein convertase subtilisin/kexin type 9 (PCSK9), total cholesterol (TCHOL), high-density lip-oprotein cholesterol (HDL-C), LDL-C, and triglycerides (TGs) were measured 10 days after ovarian depression (E2min) and 7 days after ovarian stimulation (E2max). Results: A total of 34 consecutive healthy women aged 38 (26-46) years old who underwent a full IVF cycle were included. E2 levels increased by 329.6% from E2min to E2max (108 [47-346] to 464 [241-2471] pg/mL, p<0.05). At the same time, serum PCSK9 levels significantly decreased by 30.8% (245 ± 80 to 170 ± 64 ng/mL, p<0.05). No significant changes in TCHOL, LDL-C, TGs and HDL-C were found (-0.4%, -3.8%, -2.2%, and +5.3%, p >0.05). Conclusions: The increase in endogenous E2 production during an IVF cycle was associated with a significant decrease in serum PCSK9 levels during a 7-day period.

The selection equation (replicator equation) has been independently discovered not only in various fields of biology (population genetics, ecology, prebiotic evolution, and sociobiology), but also in laser theory, where it accounts for the emergence of coherent light. Selection theory (replicator dynamics) is an ensemble theory, i. e., it describes the entire system rather than individual events, neglecting details in favor of a statistical view. However, the underlying processes at the individual level are well known in biology. For light quanta, this is not the case, because quantum theory says nothing about individual events. In the Copenhagen interpretation even the existence of causality on "quantum level" is denied. A large number of recent publications, however, makes this interpretation seem questionable.In the present paper, therefore, an attempt is made to describe the basic interactions between light and matter, as far as they are relevant for the emergence of coherent light in the laser (a photon pair interaction mediated by matter is postulated), and to apply replicator dynamics on this basis. Starting point are papers of A. Einstein about the interaction of light and matter as well as the photoelectric effect. Both theories are slightly modified. Furthermore, the double-slit experiment is investigated and finally the emergence of coherent light by density-dependent selection of photons of different phase in a laser-like model. The relationship between “mean fitness”, information content of the photon ensemble and the amplitude of the light is also analyzed.

This paper addresses the issues of how we can quantify structural information for nonparametric distributions and how we can detect its changes. Structural information refers to an index for a global understanding of a data distribution. When we consider the problem of clustering using a parametric model such as a Gaussian mixture model, the number of mixture components (clusters) can be thought of as structural information in the model. However, there does not exist any notion of structural information for nonparametric modeling of data. In this paper we introduce a novel notion of {\em kernel complexity} (KC) as structural information in the nonparametric setting. The key idea of KC is to combine the information bias inspired by the Gini index with the information quantity measured in terms of the normalized maximum likelihood (NML) code length. We empirically show that KC has a property similar to the number of clusters in a parametric model. We further propose a framework for structural change detection with KC in nonparametric distributions. With synthetic and real data sets we empirically demonstrate that our framework enables us to detect structural changes underlying the data and their early warning signals.

With reference to Planck scale, Mach’s relation, increasing support for large scale cosmic anisotropy and preferred directions and by introducing two new parameters Gamma and Beta, right from the beginning of Planck scale, we make an attempt to estimate ordinary matter density ratio, dark matter density ratio, mass, radius, temperature, age and expansion velocity (from and about the baby universe in all directions). We would like suggest that, from the beginning of Planck scale, 1) Dark matter can be considered as a kind of cosmic foam responsible for formation of galaxies. 2) Cosmic angular velocity is directly proportional to squared cosmic temperature. 3) Ratio of critical temperature to actual temperature plays a heuristic role in understanding ordinary and dark matter density ratios. 4) Cosmic expansion velocity increases with decreasing total matter density ratio. 5) There is no need to consider dark energy for understanding cosmic acceleration.

In this paper, we investigate the structural, microstructural, dielectric, and energy storage properties of Nd and Mn co-doped Ba0.7Sr0.3TiO3 [(Ba0.7Sr0.3)1-xNdxTi1-yMnyO3 (BSNTM) ceramics (x = 0, 0.005, and y = 0, 0.0025, 0.005, and 0.01)] via a defect dipole engineering method. The complex defect dipoles (MnTi"-VO∙∙)∙ and (MnTi"-VO∙∙) between acceptor ions and oxygen vacancies capture electrons, enhancing the breakdown electric field and energy storage performances. XRD, Raman spectroscopy, and microscopic investigations of BSNTM ceramics revealed the formation of a tetragonal phase, increased oxygen vacancies, and reduced grain size with Mn dopant, respectively. The BSNTM ceramics with x=0.005 and y=0 exhibit a high dielectric constant of 2058 and a dielectric loss of 0.026 at 1 kHz. These values gradually decreased to 1876 and 0.019 for x=0.005 and y=0.01 due to the Mn2+ ions at Ti4+-site, which facilitates the formation of oxygen vacancies, and prevents the decrease of Ti4+. In addition, the defect dipoles act as a driving force for depolarization to tailor the domain formation energy and domain wall energy, which provides a high difference between the maximum polarization of Pmax and remnant polarization of Pr (ΔP=10.39 µC/cm2). Moreover, the complex defect dipoles with optimum oxygen vacancies in BSNTM ceramics can provide not only a high ΔP but also reduce grain size, which together improve the breakdown strength from 60.4 to 110.6 kV/cm, giving rise to a high energy storage density of 0.41 J/cm3 and high efficiency of 84.6% for x=0.005 and y=0.01. These findings demonstrate that defect dipoles engineering is an effective method to enhance the energy storage performance of dielectrics for capacitor applications.

We report a preliminary exploration on the low-pressure Ar-O2 plasma generated by low-frequency alternating current (AC) power supply in the low-temperature Plasma Experimental Power Supply (CTP-2000S) for the first time. The electron density 〖(n〗_e), the electron temperature 〖(T〗_e) and the electron energy distribution function (EEDF) are measured by the single Langmuir probe in this experiment. Experimental results show that the ne increases with gas pressure rising, while the ne decreases with the oxygen concentrations rising. And, a plasma density peak is also observed with the AC power supply increase. A comparison between this work and the previous results by RF source suggests that the low-frequency AC power supply may be very fruitful exploration to generate the low-pressure plasma.

The Folla Redonda grape is indigenous to the region of Rias Bajas in Galicia, Spain. This grape is distinguished by its characteristic acid flavor and pulp of remarkable coloration. Despite the wine obtained from this grape is highly valued by consumers of this region for its surprising acidic notes and thickness, it is important to note that it is not a variety of Vitis vinifera and its production is not legally regulated. In the present study, an evaluation of the physicochemical properties of the Folla Redonda grape (pH, °Brix, °Bé, density, acidity, sugar content, etc.) as well as its content in bioactive compounds (total polyphenols and anthocyanins) was carried out. Additionally, the antioxidant potential of the extracts obtained from this grape was demonstrated. This study proved the interesting organoleptic characteristics of the grape, along with a high content of compounds of interest and an important antioxidant activity comparable to that of Vitis vinifera grapes. Therefore, the grape's natural consumption and its application in different industries such as nutraceutical or pharmacological would result in an important revaluation of the grape and significant health benefits. In case that the production of wine from this variety is legalized, consumers will not only be able to enjoy a wine with a characteristic dense reddish color and important acid tones, but also with interesting concentrations of bioactive compounds.

The aim of this study was to investigate the role of DNA methylation in the regulation of in vitro and in vivo cartilage formation. Based on the data of an RNA chip-assay performed on chondrifying BMP2-overexpressing C3H10T1/2 cells, the relative expression of Tet1 (tet methylcytosine dioxygenase 1), Dnmt3a (DNA methyltransferase 3) and Ogt (O-linked N-acetylglucosamine transferase) genes was examined with RT-qPCR in mouse cell-line based and primary micromass cultures. RNA probes for in situ hybridization were used on frozen sections of 15-day-old mouse embryos. DNA methylation was inhibited with 5-azacytidine during culturing. We found very strong but gradually decreasing expression of Tet1 throughout the entire course of in vitro cartilage differentiation along with strong signals in the cartilaginous embryonic skeleton. Dnmt3a and Ogt expressions did not show significant changes with RT-qPCR and gave weak in situ hybridization signals. Inhibition of DNA methylation applied during early stages of differentiation reduced cartilage-specific gene expression and cartilage formation. In contrast, it had stimulatory effect when added to differentiated chondrocytes. Our results indicate that the DNA demethylation-inducing Tet1 is a significant epigenetic factor of chondrogenesis, and inhibition of DNA methylation exerts distinct effects in different phases of in vitro cartilage formation.

Pyrocumulonimbus (pyroCb) thunderclouds, produced from extreme bushfires, can initiate frequent cloud-to-ground (CG) lightning strikes containing extended continuing currents. This, in turn, can ignite new spotfires and inflict massive harm on the environment and infrastructures. This study presents a 3D numerical thundercloud model for estimating the lightning of different types and its striking zone for the conceptual tripole thundercloud structure which is theorized to elucidate the lightning phenomenon in pyroCb storms. More emphasis is given to the lower positive charge structure thundercloud to thoroughly examine various electrical parameters including the longitudinal electric field, electric potential, and surface charge density. The simulation outcomes on pyroCb thunderclouds with a tripole structure confirm the presence of negative longitudinal electric field initiation at the cloud’s lower region. This initiation is accompanied by enhancing the lower positive charge region, resulting in an overall positive electric potential increase. Consequently, negative surface charge density appears underneath the pyroCb thundercloud which has the potential to induce positive cloud-to-ground (+CG) lightning flashes. The suggested model would establish the basis for identifying the potential area impacted by lightning and could also be expanded to analyze the dangerous conditions that may arise in wind energy farms or power substations in times of severe pyroCb events.

A formulation of the Density Functional Theory (DFT) is constructed as an application of the method of maximum entropy for an inhomogeneous fluid in thermal equilibrium. The use of entropy as a systematic method to generate optimal approximations is extended from the classical to the quantum domain. This process introduces a family of trial density operators that are parametrized by the particle density. The optimal density operator is that which maximizes the quantum entropy relative to the exact canonical density operator. This approach reproduces the variational principle of DFT and allows a simple proof of the Hohenberg-Kohn theorem at finite temperature. Finally, as an illustration, we discuss the Kohn-Sham approximation scheme at finite temperature

Rural areas, as a system, face multiple challenges. Among these are population decline and attendant economic and social maladies namely demographic issues considering a scarce population. Pull factors for immigrants to go to other countries are known, nevertheless, to comprehend factors for remaining in rural areas after arriving could support a strategic local policy, and for an informed practice. The purpose of the study is to explore motivations shaping immigrants’ intentions to stay in the Alentejo, a depopulated region in Portugal, using a qualitative approach. Research questions are: What motivates immigrants to remain living in depopulated regions in Portugal? Furthermore, what contributions can practitioners and immigrants give for local policy and practice? Eight practitioners and fifteen non-European Union immigrants living in this region were interviewed between 2020 and 2021. Empirical data were analysed, supported by MaxQDA software. Results point out that the intention to remain in rural areas arise from a progressive construction, it is a process that immigrants experience to become motivated to stay long-term. Factors influencing the process include four components: 1. instrumental and material motivations; 2. emotional and social motivations; 3. motivations based on quality of life; and 4. motivations based on political dimensions. Components are conditioned by the availability of : stable and suitable jobs, access to decent and affordable housing, as well as quality of education and health services for their children; additionally to socio-emotional satisfaction, as family reunification, migrants network, integration and real intercultural living in the host community, close relationships to practitioners from social services; and quality of life, such as lower rents, peaceful and secure living conditions, granted a better future for their children as in any another place in Europe, associated finally to the simplified policy enabling one to become a legal citizen. Conclusions highlight implications for policy and practice, suggesting more investment for rural regions to reverse depopulation reality.

In this study, graphite, the most stable form of carbon, was examined for its hexagonal crystalline structure with specific dimensions (ao=2.46 Ǻ; co=6.70 Ǻ). Its framework comprises parallel carbon atom planes forming regular hexagons (side length 1.415 Ǻ) and 120° angles between adjacent atoms. Two structural variations exist: hexagonal symmetry (1-2-1-2-1-2 planes) and rhomboidal symmetry (1-2-3-1-2-3 planes). The research aimed to produce high-density graphite utilizing carbonaceous raw materials. Graphite-based materials often exhibit high porosity, necessitating additional treatments. The study successfully obtained mesophase tar pitch (yield: 45%), a pivotal raw material, and high-density graphite. The resulting graphite underwent characterization for physical properties (apparent and real density, porosity and compression strength), demonstrating conformity with existing literature data.

Accurate and efficient determination of excited-state polarizabilities (α) is an open problem both experimentally and computationally. Following our previous work, [Phys. Chem. Chem. Phys. 2023, 25, 2131−2141], where one can employ simple ground-state density-based functions from the information-theoretic approach (ITA) to accurately and efficiently predict the macromolecular polarizabilities, we aim to predict the lowest excited-state polarizabilities in this work. The philosophy is to use density-based functions to depict the excited-state polarizabilities. As a proof-of-principle application, employing 2-(2′-hydroxyphenyl)benzimidazole and its derivatives as model systems, we have verified that either with the ground-state (S0) or excited-state (S1) densities as input, ITA quantities can be strongly correlated with the excited-state polarizabilities. When the transition densities are considered, both S0 and S1 polarizabilities are in good relationships with some ITA quantities. Furthermore, excitation and emission energies can be predicted based on multivariant linear regression equations of ITA quantities.

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.

We introduce a number of techniques in quantitative convergent-beam electron diffraction under development by our group and discuss the basis for measuring interatomic electrostatic potentials (and therefore also electron densities), localised at sub-nanometre scales, with sufficient accuracy and precision to map chemical bonds in and around nanostructures in nanostructured materials. This has never before been possible as experimental measurements of bonding in quantum crystallography have hitherto always been restricted to homogeneous single-phased crystals.

This paper describes the packaging models that are fundamental for the design of ultra-high-performance concrete (UHPC), and their evolution. They are divided into two large groups: continuous and discrete models. The latter are those that provide the best answer in obtaining an adequate simulation of the packing of the particles up to nanometric size. This includes the interaction among the particles by means of loosening and wall coefficients, allowing a simulation of the virtual and real compactness of such particles. In addition, a relationship between virtual and real compactness is obtained, through the compaction index, which may simulate the energy of compaction that the particles undergo in their placement in the mold. The use of last-generation additives allows such models to be implemented with water-cement (w/c) ratios close to 0.18. However, the premise of maximum packing as a basic pillar for the production of UHPC should not be the only one. The cement hydration process affected by nanoadditions and the ensuing effectiveness in the properties in both fresh and hardened state according to the respective percentages in the mixture should also be studied. An adequate ratio and proportion of these additions may lead to an obtaining of better results even with lower levels of compactness.