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In this paper, we proposed a novel operation to reconstruction tetrahedrons within a certain region, which we call MFRC (Multi-face reconstruction). During the existing tetrahedral mesh improvement methods, the flip operation is one of the very important components. However, due to the limited area affected by the flip, the improvement of the mesh quality by the flip operation is also very limited. The proposed MFRC algorithm solves this problem. MFRC can reconstruct the local mesh in a larger range and can find the optimal tetrahedron division in the target area within acceptable time complexity. Therefore, based on the MFRC algorithm, we combined other operations including smoothing, edge removal, face removal, and vertex insertion/deletion to develop an effective mesh quality improvement method. Numerical experiments of dozens of meshes show that the algorithm can effectively improve the low-quality elements in the tetrahedral mesh, and can effectively reduce the running time, which has important significance for the quality improvement of large-scale mesh.

In this paper 13 elements, both physiological and causing toxic effects, were determined by inductively coupled plasma mass spectrometry in roots of 26 species of herbs used in Traditional Chinese Medicine. The herbs were purchased from online shop in two batches 1 year apart to verify the variability of elemental content in time. The multivariate statistical methods—multiple regression, canonical variates and interaction effect analysis—were applied to interpret the data and to show the relationships between elements and two batches of herb roots. The maximum permissible concentration of Cd (0.3 mg kg−1) was exceeded in 7 herb roots which makes 13% of all specimens. The multiple regression analysis revealed the significant relationships between elements: Mg with Sr; V with Pb, As and Ba; Mn with Pb; Fe with As and Ba; Co with Ni and Sr, Cu with Pb, Cd and As; Zn with Pb, Cd, As and Ba. The canonical variates analysis showed that the statistical inference should not be based solely on the type of herb or number of batch because of the underlying interaction effects between those two variables that may be a source of variability of the content of determined elements.

The paper presents an innovative method of solving the problem of vibration suppression during milling of large-size details. It consists in searching for the best conditions for clamping the workpiece based on a rapid modal identification of the dominant natural frequencies only and requires repetitive changes in the tightening torque of the clamping screws. Then, by estimating the minimum work of the cutting forces acting in the direction of the width of the cutting layer, it is possible to predict the best fixing of the workpiece. Application of the method does not require the creation and identification of a computational model of the process or preliminary numerical simulations. The effectiveness of this method was confirmed by the evaluation of the Root Mean Square (RMS) of the vibration level in the time domain observed during the actual face milling process. The worst results were obtained for the configuration of supports tightened with a torque of 90–110 Nm, and the best—with a torque of 50 Nm.

Transboundary river basins give rise to complex water-sharing decision making that can be analyzed as a game in the sense of dynamic game theory, as done in this work. The sharing of transboundary water resources depends on the long-term shifting interactions between upstream and downstream countries, which has received limited research attention in the past. The water-sharing strategy of a riparian country depends on the strategies of other countries over time. This paper presents an evolutionary game method to analyze the long-term water-sharing strategies of countries encompassing transboundary river basins over time. The method analyzes the evolutionary strategies of riparian countries and investigates evolutionary stable strategies (ESSs) considering the payoff matrix. The evolutionary game method is applied to a river basin shared by three countries assuming two types of benefits and one type of cost to countries as decision variables of a game that reflects water use, economic and political gains, and socio-economic losses of countries. Numerical examples illustrate the strategies resulting from the evolutionary game processes and the role of several parameters on the interaction between riparian countries. The countries’ strategies are analyzed for several levels of benefits and costs, and the convergence of the strategies to a stable point is assessed. Results demonstrate the role that the upstream country’s potential benefits and the cost of conflict (i.e., non-cooperation) to other countries has on reaching a stable point in the game. This work’s results show the potential benefit to the upstream country under cooperative strategy must exceed its benefits from water use under non-cooperative strategy to gain the full stable cooperation of downstream countries. This work provides a method to resolve water-sharing strategies by countries sharing transboundary river basins and to evaluate the implications of cooperation or non-cooperation.

Treatment failure or relapse due to tumor escape caused by reduction in target antigen expression has become a challenge in the field of CART therapy. Target antigen density is closely related to the effectiveness of CART therapy, and reduced or lost target antigen expression limits the efficacy of CART therapy and hinders the durability of CAR T cells. Epigenetic drugs can regulate histones for molecular modifications to regulate the transcriptional, translational and post-translational modification processes of target agents., and we demonstrated for the first time the role in regulating CD22 expression and its effect on the efficacy of CD22 CART. In this paper, we found that Chidamide promoted the expression of CD22 on the surface of B-cell tumor cells in vitro and in vivo, and enhanced the function of CD22 CART. As for mechanisms, we demonstrated that Chidamide did not affect CD22 mRNA transcription, but significantly increased the expression of total CD22 protein, indicating that Chidamide may upregulate cell surface CD22 expression by affecting the distribution of CD22 protein. In summary, our results suggest that Chidamide may enhance the efficacy of CD22 CART by inhibiting histone deacetylases to regulate post-transcriptional modifications that affect protein distribution to increase the expression of CD22 on the cell surface.

In this paper, various multi-layer shields are designed, optimized, and analyzed for electron and proton space environments. The design process is performed for various suitable materials for the local protection of sensitive electronic devices using MCNPX code and the Genetic optimization Algorithm. In the optimizations process, the total ionizing dose is 53.3% and 72% greater than the aluminum shield for proton and electron environments, respectively. Considering the importance of the protons in the LEO orbits, the construction of the shield was based on designing a proton source. A sample shield is built using a combination of Aluminum Bronze and molybdenum layers with a copper carrier to demonstrate the idea. Comparisons of radiation attenuation coefficient results indicate a good agreement between the experimental, simulation, and analytical calculations results. The good specifications of the proposed multi-layer shield prove their capability and ability to use in satellite missions for electronic device protection.

Heavy oil and bitumen play a vital role in the global energy supply, and to unlock such resources, thermal methods, e.g., steam injection, are applied. To improve the performance of these methods, different additives, such as air, solvents, and chemicals, can be used. As a subset of chemicals, surfactants are one of the potential additives for steam-based bitumen recovery methods. Molecular interactions between surfactant/steam/bitumen have not been addressed in the literature. This paper investigates molecular interactions between anionic surfactants, steam, and bitumen in high-temperature and high-pressure conditions. For this purpose, a real Athabasca oil sand composition is employed to assess the phase behavior of surfactant/steam/bitumen under in-situ steam-based bitumen recovery. Two different asphaltene architectures, archipelago and Island, are used to examine the effect of asphaltene type on bitumen's interfacial behavior. The influence of having sulfur heteroatoms in a resin structure and a benzene ring's effect in an anionic surfactant structure on surfactant–steam–bitumen interactions are investigated systematically. The outputs are supported by different analyses, including radial distribution functions (RDFs), mean squared displacement (MSD), radius of gyration, self-diffusion coefficient, solvent accessible surface area (SASA), interfacial thickness, and interaction energies. According to MD outputs, adding surfactant molecules to the steam phase improved the interaction energy between steam and bitumen. Moreover, surfactants can significantly improve steam emulsification capability by decreasing the interfacial tension (IFT) between bitumen and the steam phase. Asphaltene architecture has a considerable effect on the interfacial behavior in such systems. This study provides a better and more in-depth understanding of surfactant–steam–bitumen systems and spotlights the interactions between bitumen fractions and surfactant molecules under thermal recovery conditions.

The study of the pedogenic process in response to natural evolution, gradual anthropogenic shifts and engineering upheavals is of great significance for understanding, utilizing and transforming nature in the future. Although scholars have considered anthropic activities to be an important factor affecting pedogenesis, research on how and how much anthropic activities influence the soil-forming process is scant. This paper was conducted to analyse pedogenic characteristics dominated by anthropic activities. In this study, the parent materials and soils undergoing natural evolution (NE), tillage perturbation (TP) and engineering perturbation (EP) were selected as research objects. The genetic characteristics of soils undergoing NE, TP and EP are investigated mainly from three aspects: soil profile macromorphological characteristics, soil physical and chemical properties and chemical weathering characteristics. The results indicated that the influence of anthropic activities (TP and EP) on the process of pedogenesis is complicated. First, compared with NE, TP decreases the thickness of topsoil from 22.2 to 21.2 cm, while EP increases the thickness of topsoil from 22.2 to 23.2 cm, and EP causes the soil to have a high profile development index. Second, compared with TP, EP can improve bulk density (BD), soil organic carbon (SOC), total nitrogen (TN) and cation exchange capacity (CEC), Finally, the chemical weathering intensity differed among NE, TP and EP and followed the order of TP > NE > EP. Therefore, in the future, the genetic characteristics of soils dominated by anthropic activities should be considered. This will help us systematically understand the genesis and evolutionary characteristics of soil and lay a foundation for further perfecting the diagnostic horizon and diagnostic characteristics of the Soil Taxonomy and World Reference Base.

We study the binary $q$-voter model with generalized anticonformity on random Erd\H{o}s-R\'enyi graphs. In such a model, two types of social responses, conformity and anticonformity, occur with complementary probabilities and the size of the source of influence $q_c$ in case of conformity is independent from the size of the source of influence $q_a$ in case of anticonformity. For $q_c=q_a=q$ the model reduces to the original $q$-voter model with anticonformity. Previously, such a generalized model was studied only on the complete graph, which corresponds to the mean-field approach. It was shown that it can display discontinuous phase transitions for $q_c \ge q_a + \Delta q$, where $\Delta q=4$ for $q_a \le 3$ and $\Delta q=3$ for $q_a>3$. In this paper, we pose the question if discontinuous phase transitions survive on random graphs with an average node degree $\langle k\rangle \le 150$ observed empirically in social networks. Using the pair approximation, as well as Monte Carlo simulations, we show that discontinuous phase transitions indeed can survive, even for relatively small values of $\langle k\rangle$. Moreover, we show that for $q_a < q_c - 1$ pair approximation results overlap the Monte Carlo ones. On the other hand, for $q_a \ge q_c - 1$ pair approximation gives qualitatively wrong results indicating discontinuous phase transitions neither observed in the simulations nor within the mean-field approach. Finally, we report an intriguing result showing that the difference between the spinodals obtained within the pair approximation and the mean-field approach follows a power law with respect to $\langle k\rangle$, as long as the pair approximation indicates correctly the type of the phase transition., Comment: 10 pages, 6 figures

The COVID-19 global pandemic has significantly impacted every aspect of life all over the world. The United States is reported to have suffered more than 20% of the global casualties from this pandemic. It is imperative to investigate the growth dynamics of the disease in the US based on varying geographical and governmental factors that best manifest itself in each State of the Country. This paper utilizes a hybrid machine learning and continuum deformation-based approach for analyzing the stability and growth rate of the pandemic. To this end, principal stress values of the pandemic continuum body are obtained using Mohr’s Circle method and overlapping, moving windows of data are analysed successively. This helps in finding the correlations between the growth rate and Governments’ action/Public’s reaction. Government actions include “state of emergency”, “shelter at place”, and “phase declarations”. We also consider the vaccination rate milestones, which shows us the coordinated Governments’ action/Public’s reaction. Finally, a number of recommendations are made to the Governments and people for better management of future pandemics.

Ternary metal oxide compounds, such as Ti-Nb and Nb-W oxides, have renewed research interest in energy storage materials because these oxides contain multivalent metal ions that may be able to control the ion transport in solid lithium batteries. One of these oxides is Ti2Nb10O29, which is composed of metal–oxygen octahedra connected through corner-sharing and edge-sharing to form “block structures”. In the early 1970s Von Dreele and Cheetham proposed a metal-atoms ordering in this oxide crystal using Rietveld refined neutron powder diffraction method. Most recent studies on these oxides, however, have not considered cation ordering in evaluating the battery electrode materials. In this paper, by utilizing the latest scanning transmission electron microscopy combined with energy dispersive X-ray spectroscopy imaging technology, the cation chemical ordering in those oxide crystals was directly revealed at atomic resolution.

Risk prediction scores are important tools to support clinical decision-making for patients with coronavirus disease (COVID-19). The objective of this paper was to validate the 4C mortality score, originally developed in the United Kingdom, for a Canadian population, and to examine its performance over time. We conducted an external validation study within a registry of COVID-19 positive hospital admissions in the Kitchener-Waterloo and Hamilton regions of southern Ontario between March 4, 2020 and June 13, 2021. We examined the validity of the 4C score to prognosticate in-hospital mortality using the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals calculated via bootstrapping. The study included 959 individuals, of whom 224 (23.4%) died in-hospital. Median age was 72 years and 524 individuals (55%) were male. The AUC of the 4C score was 0.77, 95% confidence interval 0.79–0.87. Overall mortality rates across the pre-defined risk groups were 0% (Low), 8.0% (Intermediate), 27.2% (High), and 54.2% (Very High). Wave 1, 2 and 3 values of the AUC were 0.81 (0.76, 0.86), 0.74 (0.69, 0.80), and 0.76 (0.69, 0.83) respectively. The 4C score is a valid tool to prognosticate mortality from COVID-19 in Canadian hospitals and can be used to prioritize care and resources for patients at greatest risk of death.

In this paper, the synthesis, characterization and catalytic application of a novel magnetic silica-supported Ag2CO3 (MS/Ag2CO3) with core–shell structure are developed. The MS/Ag2CO3 nanocomposite was prepared through chemical modification of magnetic MS nanoparticles with AgNO3 under alkaline conditions. The structure, chemical composition and magnetic properties of MS/Ag2CO3 were investigated by using VSM, PXRD, FT-IR, EDX and SEM techniques. The MS/Ag2CO3 nanocomposite was used as an effective catalyst for the Knoevenagel condensation under solvent-free conditions at 60 °C in an ultrasonic bath. The recovery and leaching tests were performed to study the nature of the MS/Ag2CO3 catalyst under applied conditions.

Over the past 50 years, temperatures on the Qinghai-Tibet Plateau (QTP) have risen roughly twice as fast as the global average, making it the most unpredictable region of environmental change due to global warming. In this paper, an Environmental Area Index model was developed using data from the Coupled Model Intercomparison Project to assess the ecological risk faced by QTP ecosystems under the influence of climate factors. The results show that ecological risk gradually decreases from northwest to the southeast, and there are different trends in ecological risk for each class in areas with different elevation gradients. As elevation increased, the proportion of potential risk areas gradually decreased, and the proportion of high- and higher-risk areas gradually increased. We predict that in the period 2021–2100, the overall ecological risk change trend on the QTP will not be obvious, but there will be a more obvious change on the vertical gradient. In general, under the existing global climate change scenario, the ecological risk faced by the QTP show a decreasing trend under the influence of climate factors, and the decrease in ecological risks is much higher at higher elevations than at lower elevations.

Understanding the dynamics of cooperative behavior of individuals in complex societies represents a fundamental research question which puzzles scientists working in heterogeneous fields. Many studies have been developed using the unitary agent assumption, which embeds the idea that when making decisions, individuals share the same socio-cultural parameters. In this paper, we propose the ECHO-EGN model, based on Evolutionary Game Theory, which relaxes this strong assumption by considering the heterogeneity of three fundamental socio-cultural aspects ruling the behavior of groups of people: the propensity to be more cooperative with members of the same group (Endogamic cooperation), the propensity to cooperate with the public domain (Civicness) and the propensity to prefer connections with members of the same group (Homophily). The ECHO-EGN model is shown to have high performance in describing real world behavior of interacting individuals living in complex environments. Extensive numerical experiments allowing the comparison of real data and model simulations confirmed that the introduction of the above mechanisms enhances the realism in the modelling of cooperation dynamics. Additionally, theoretical findings allow us to conclude that endogamic cooperation may limit significantly the emergence of cooperation.

Intravenous recombinant tissue plasminogen activator (rtPA) is, besides mechanical thrombectomy, the highest class evidence based reperfusion treatment of acute ischemic stroke (AIS). The biggest concern of the therapy is symptomatic intracranial hemorrhage (sICH), which occurs in 3–7% of all treated patients, and is associated with worse functional outcome. Finding a method of the powerful identification of patients at highest risk of sICH, in order to increase the percentage of stroke patients safely treated with rtPA, is one of the most important challenges in stroke research. To address this problem, we designed a complex project to identify blood, neuroimaging, and clinical biomarkers combined for prospective assessment of the risk of rtPA-associated ICH. In this paper we present results of blood proteomic and peptide analysis of pilot 41 AIS patients before rtPA administration (the test ICH group, n = 9 or the controls, without ICH, n = 32). We demonstrated that pre-treatment blood profiles of 15 proteins differ depending on whether the patients develop rtPA-associated ICH or not. SWATH-MS quantification of serum or plasma proteins might allow for robust selection of blood biomarkers to increase the prospective assessment of rtPA-associated ICH over that based solely on clinical and neuroimaging characteristics.

Study on the microscopic structure of saline–alkali soil can reveal the change of its permeability more deeply. In this paper, the relationship between permeability and microstructure of saline–alkali soil with different dry densities and water content in the floodplain of southwestern Shandong Province was studied through freeze–thaw cycles. A comprehensive analysis of soil samples was conducted using particle-size distribution, X-ray diffraction, freeze–thaw cycles test, saturated hydraulic conductivity test and mercury intrusion porosimetry. The poor microstructure of soil is the main factor that leads to the category of micro-permeable soil. The porosity of the local soil was only 6.19–11.51%, and ultra-micropores (

Mass-wasting of ocean island volcanoes is a well-documented phenomenon. Massive flank collapses may imply tens to hundreds of km3 and generate mega-tsunamis. However, the causal links between this large-scale, low-frequency instability, and the time–space evolution of magma storage, crystal fractionation/accumulation, lithospheric assimilation, and partial melting remains unclear. This paper aims at tracking time variations and links between lithospheric, crustal and surface processes before and after a major flank collapse (Monte Amarelo collapse ca. 70 ka) of Fogo volcano, Cape Verde Islands, by analysing the chemical composition (major, trace elements, and Sr–Nd–Pb isotopes) and age-controlled stratigraphy (K–Ar and Ar–Ar dating) of lavas along vertical sections (Bordeira caldera walls). The high-resolution sampling allows detecting original variations of composition at different time-scales: (1) a 60 kyrs-long period of increase of magma differentiation before the collapse; (2) a 10 kyrs-long episode of reorganization of magma storage and evacuation of residual magmas (enriched in incompatible elements) after the collapse; and (3) a delayed impact at the lithospheric scale ~ 50 kyrs after the collapse (increasing EM1-like materiel assimilation).

Current research on DNA storage usually focuses on the improvement of storage density by developing effective encoding and decoding schemes while lacking the consideration on the uncertainty in ultra-long-term data storage and retention. Consequently, the current DNA storage systems are often not self-contained, implying that they have to resort to external tools for the restoration of the stored DNA data. This may result in high risks in data loss since the required tools might not be available due to the high uncertainty in far future. To address this issue, we propose in this paper a self-contained DNA storage system that can bring self-explanatory to its stored data without relying on any external tool. To this end, we design a specific DNA file format whereby a separate storage scheme is developed to reduce the data redundancy while an effective indexing is designed for random read operations to the stored data file. We verified through experimental data that the proposed self-contained and self-explanatory method can not only get rid of the reliance on external tools for data restoration but also minimise the data redundancy brought about when the amount of data to be stored reaches a certain scale., Comment: Accepted by Nature Scientific Reports

In this work, we present a robust and powerful method for the verification, with arbitrary accuracy, of Monte Carlo codes for simulating random walks in complex media. Such random walks are typical of photon propagation in turbid media, scattering of particles, i.e., neutrons in a nuclear reactor or animal/humans’ migration. Among the numerous applications, Monte Carlo method is also considered a gold standard for numerically “solving” the scalar radiative transport equation even in complex geometries and distributions of the optical properties. In this work, we apply the verification method to a Monte Carlo code which is a forward problem solver extensively used for typical applications in the field of tissue optics. The method is based on the well-known law of average path length invariance when the entrance of the entities/particles in a medium obeys to a simple cosine law, i.e., Lambertian entrance, and annihilation of particles inside the medium is absent. By using this law we achieve two important points: (1) the invariance of the average path length guarantees that the expected value is known regardless of the complexity of the medium; (2) the accuracy of a Monte Carlo code can be assessed by simple statistical tests. We will show that we can reach an arbitrary accuracy of the estimated average pathlength as the number of simulated trajectories increases. The method can be applied in complete generality versus the scattering and geometrical properties of the medium, as well as in presence of refractive index mismatches in the optical case. In particular, this verification method is reliable to detect inaccuracies in the treatment of boundaries of finite media. The results presented in this paper, obtained by a standard computer machine, show a verification of our Monte Carlo code up to the sixth decimal digit. We discuss how this method can provide a fundamental tool for the verification of Monte Carlo codes in the geometry of interest, without resorting to simpler geometries and uniform distribution of the scattering properties.

Synthetic homogeneous system known to date performing methane to methanol conversion using O2 as terminal oxidant is unique and based on copper complex with piperazine-based ligand (Cu3L in Fig. 1) in a medium of acetonitrile. Prior work have shown that in order to achieve catalytic turnover, hydrogen peroxide is needed to regenerate the active site. We show in this paper that reaction solvent based on organic nitrile decompose concurrently with methane activation and that in the absence of either acetonitrile, Cu complex or hydrogen peroxide, the catalytic turnover does not happen. We show in this manuscript that the direct methane oxidation to methanol might have been mediated by catalytic Radziszewski oxidation between acetonitrile and H2O2. Additionally we have discovered that in the absence of methane, peroxide mediated acetonitrile decomposition also makes methanol via a background reaction which was hitherto unknown.

In recent years, considerable attention has been paid in time–frequency analysis (TFA) methods, which is an effective technology in processing the vibration signal of rotating machinery. However, TFA techniques are not sufficient to handle signals having a strong non-stationary characteristic. To overcome this drawback, taking short-time Fourier transform as a link, a TFA methods that using the generalized Warblet transform (GWT) in combination with the second order synchroextracting transform (SSET) is proposed in this study. Firstly, based on the GWT and SSET theories, this paper proposes a method combining the two TFA methods to improve the TFA concentration, named GWT–SSET. Secondly, the method is verified numerically with single-component and multi-component signals, respectively. Quantized indicators, Rényi entropy and mean relative error (MRE) are used to analyze the concentration of TFA and accuracy of instantly frequency (IF) estimation, respectively. Finally, the proposed method is applied to analyze nonstationary signals in variable speed. The numerical and experimental results illustrate the effectiveness of the GWT–SSET method.

Cancer tumor classification based on morphological characteristics alone has been shown to have serious limitations. Breast, lung, colorectal, thyroid, and ovarian are the most commonly diagnosed cancers among women. Precise classification of cancers into their types is considered a vital problem for cancer diagnosis and therapy. In this paper, we proposed a stacking ensemble deep learning model based on one-dimensional convolutional neural network (1D-CNN) to perform a multi-class classification on the five common cancers among women based on RNASeq data. The RNASeq gene expression data was downloaded from Pan-Cancer Atlas using GDCquery function of the TCGAbiolinks package in the R software. We used least absolute shrinkage and selection operator (LASSO) as feature selection method. We compared the results of the new proposed model with and without LASSO with the results of the single 1D-CNN and machine learning methods which include support vector machines with radial basis function, linear, and polynomial kernels; artificial neural networks; k-nearest neighbors; bagging trees. The results show that the proposed model with and without LASSO has a better performance compared to other classifiers. Also, the results show that the machine learning methods (SVM-R, SVM-L, SVM-P, ANN, KNN, and bagging trees) with under-sampling have better performance than with over-sampling techniques. This is supported by the statistical significance test of accuracy where the p-values for differences between the SVM-R and SVM-P, SVM-R and ANN, SVM-R and KNN are found to be p = 0.003, p = p = p = 0.009. Moreover, SVM-P and ANN, SVM-P and KNN are found to be significantly different with p-values p = p = p-values p = p = 0.004, respectively. Thus, the proposed model can help in the early detection and diagnosis of cancer in women, and hence aid in designing early treatment strategies to improve survival.

It is hypothesized that vitamin D deficiency could be related to ovarian reserve. This systematic review and meta-analysis was undertaken to analyze the possible association between vitamin D and ovarian reserve among adolescent and adult women. All eligible studies identified through the ISI Web of Science, PubMed, and Scopus were included up to May 2021. A random-effects meta-analysis model was implemented and a weighted mean difference (WMD) and 95% confidence interval (CI) were calculated. A total of 38 papers covering 8608 individuals were enrolled in this systematic review and meta-analysis. Antral follicle count (AFC) was significantly lower among Asians (WMD − 0.65; 95% CI − 1.28 to − 0.01; P = 0.04; I2 = 0.0%) and luteinizing hormone (LH) levels were higher in non-Asians (WMD 2.16 IU/L; 95% CI 0.20 to 4.12; P = 0.031; I2 = 9.3%) with vitamin D insufficiency/deficiency. Also, there was a negative correlation between vitamin D and LH/FSH ratio in women with normal body mass index (BMI) (Fisher’s Z: − 0.18; 95% CI − 0.37 to − 0.008; P = 0.041; I2 = 51.5%). Although there were no significant associations between serum vitamin D levels and any of the intended ovarian reserve markers, subgroup analyses have found significant findings regarding AFC, LH, and LH/FSH ratio. In order to understand the underlying mechanisms of vitamin D in female reproduction, further attempts are needed.

The movements of ancient crop and animal domesticates across prehistoric Eurasia are well-documented in the archaeological record. What is less well understood are the precise mechanisms that farmers and herders employed to incorporate newly introduced domesticates into their long-standing husbandry and culinary traditions. This paper presents stable isotope values (δ

A vertical annular configuration with differently heated cylindrical surfaces and horizontal adiabatic boundaries is systematically studied in view to their industrial applications. In this paper, we investigate the effects of conjugate buoyant heat transport in water based nanofluids with different nanoparticles such as alumina, titania or copper, and is filled in the enclosed annular gap. The annulus space is formed by a thick inner cylinder having a uniform high temperature, an exterior cylindrical tube with a constant lower temperature, and thermally insulated upper and lower surfaces. By investigating heat transport for broad spectrum of Rayleigh number, solid wall thickness, thermal conductivity ratio and nanoparticle volume fraction, we found that the influence of wall thickness on thermal dissipation rate along wall and interface greatly depends on conductivity ratio and vice-versa. In particular, we uncover that the choice of nanoparticle in a nanofluid and its concentration are key factors in enhancing the thermal transport along the interface. Specially, copper based nanofluids produces higher heat transport among other nanoparticles, and for the range of nanoparticle concentration chosen in this analysis, enhanced thermal dissipation along the interface has been detected as nanoparticle volume fraction is increased. Our results are applicable to choose nanofluids along with other critical parameters for the desired heat transport.

In this paper, the natural convection heat transfer of water/alumina nanofluid is investigated in a closed square cavity. An oblique magnetic field is applied on the cavity of angle $$\gamma$$ γ . There is also radiation heat transfer in the cavity. The cavity includes a high-temperature source of L-shape. A low-temperature source as a quadrant of a circle is placed at the corner of the cavity. All other walls are well insulated. The novelty of this work is a low-temperature obstacle embedded in the cavity. Simulations are conducted with a Fortran code based on the control volume method and simple algorithm. Entropy generation rate, Bejan number, and heat transfer are studied by changing different parameters. Results indicate that the highest rates of heat transfer and entropy generation have occurred for the perpendicular magnetic field at high values of the Rayleigh number. At these Rayleigh numbers, the minimum value of the Bejan number is obtained for 15° magnetic field. The magnetic field variation can lead to a change up to 53% in Nusselt number and up to 34% in generated entropy. In a weak magnetic field, the involvement of the radiation heat transfer mechanism leads to an increase in the heat transfer rate so that the Nusselt number can be increased by ten units considering the radiation heat transfer when there is no magnetic field. The maximum heat transfer rate occurs in the horizontal cavity and the minimum value in the cavity of 60° angle. For water, these values are 10.75 and 9.98 for 0 and 60 angles, respectively. Moreover, a weak magnetic field increases the heat transfer rate in the absence of the radiation mechanism, while it is reduced by considering a strong magnetic field.

With the application of advanced composite materials in High-Aspect-Ratio wings (HARW), the randomness of structural parameters, such as elastic modulus and Poisson's ratio, is enhanced. Hence, in order to explore the whole picture of aeroelastic problems, it is of great significance to study the role of random structural parameters in aeroelastic problems. In this paper, the dynamic response of flexible HARW considering random structural parameters is analyzed. An aeroelastic model of a one-dimensional cantilevered Euler–Bernoulli beam considering aerodynamic forces acting on the wing is established based on Hamilton's principle. Adopted the idea of simplifying calculation, the effect of random structural parameters is analyzed. Then, considering the elastic modulus and torsional stiffness as continuously one-dimensional random field functions, and discretized by local method. The first and second order recursive stochastic nonlinear finite element equations of wing are derived by using perturbation method. Based on it, statistical expression of aeroelastic effects of the wing is derived. Monte Carlo method is adopted to verify the effectiveness of the method. Numerical simulations indicate that the method proposed can well mirror the statistical characteristics of aeroelastic response.

In general, the electro-spinning of lignin requires it to be functionalised and/or blended with synthetic or natural polymers. This paper reports on the use of solvent fractionated lignin-lignin blend to electro-spin BioChoice softwood Kraft lignin. The blend consisted of acetone-soluble and ethanol-soluble lignin in a binary solvent of acetone and DMSO. Solvent fractionation was used to purify lignin where the ash content was reduced in the soluble lignin fractions from 1.24 to ~ 0.1%. The corresponding value after conventional acid-washing in sulphuric acid was 0.34%. A custom-made electro-spinning apparatus was used to produce the nano-fibres. Heat treatment procedures were developed for drying the electro-spun fibres prior to oxidation and carbonisation; this was done to prevent fibre fusion. The lignin fibres were oxidised at 250 °C, carbonised at 1000 °C, 1200 °C and 1500 °C. The cross-section of the fibres was circular and they were observed to be void-free. The longitudinal sections showed that the fibres were not fused. Thus, this procedure demonstrated that solvent fractionated lignin can be electro-spun without using plasticisers or polymer blends using common laboratory solvents and subsequently carbonised to produce carbon fibres with a circular cross-section.

Reconfiguration of protein conformation in a micro and nano particle (MNP) protein corona due to interaction is an often-overlooked aspect in drug design and nano-medicine. Mostly, MNP-Protein corona studies focus on the toxicity of nano particles (NPs) in a biological environment to analyze biocompatibility. However, preserving functional specificity of proteins in an NP corona becomes critical for effective translation of nano-medicine. This paper investigates the non-classical interaction between insulin and ZnO MNPs using a classical electrical characterization technique at GHz frequency with an objective to understand the effect of the micro particle (MP) and nanoparticle (NP) morphology on the electrical characteristics of the MNP-Protein corona and therefore the conformation and functional specificity of protein. The MNP-Protein corona was subjected to thermal and enzymatic (papain) perturbation to study the denaturation of the protein. Experimental results demonstrate that the morphology of ZnO particles plays an important role in preserving the electrical characteristics of insulin.

Simple tests of infectiousness that return results in minutes and directly from samples even with low viral loads could be a potential game-changer in the fight against COVID-19. Here, we describe an improved isothermal nucleic acid amplification assay, termed the RICCA (RNAIsothermalCo-assisted andCoupledAmplification) reaction, that consists of a simple one-pot format of ‘sample-in and result-out’ with a primary focus on the detection of low copy numbers of RNA virus directly from saliva without the need for laboratory processing. We demonstrate our assay by detecting 16S rRNA directly fromE. colicells with a sensitivity as low as 8 CFU/μL and RNA fragments from a synthetic template of SARS-CoV-2 with a sensitivity as low as 1740 copies/μL. We further demonstrate the applicability of our assay for real-time testing at the point of care by designing a closed format for paper-based lateral flow assay and detecting heat-inactivated SARS-COV-2 virus in human saliva at concentrations ranging from 28,000 to 2.8 copies/μL with a total assay time of 15–30 min.

In this paper, we introduce a nanocomposite as a humidity-sensitive sound absorber. The nanocomposites were prepared using hydrogel polymer (HP) as a matrix and graphene oxide (GO) as a filler. Results show that the surface energy of the nanocomposite is 58.4 mJ m−2, and GO sheets increase the nanocomposite porosity from 2.6716 cm2 g−1 (for HP) up to 3.246 cm2 g−1. In addition, the diameter of nanocomposite pores is 8.5202 nm lower than that of HP (10.274 nm). To study the effect of humidity on the sound absorption, we exposed them to moisture for 30 and 60 min and then measured sound absorption. Results show an absorption peak for the HP at 1022 Hz with an attenuation value of 30%, while the nanocomposite shows two main peaks around 1898 and 3300 Hz. In addition, results show that sound absorption peaks shift to higher frequencies according to humidification time.

Device-to-device (D2D) communications and mobile edge computing (MEC) used to resolve traffic overload problems is a trend in the cellular network. By jointly considering the computation capability and the maximum delay, resource-constrained terminals offload parts of their computation-intensive tasks to one nearby device via a D2D connection or an edge server deployed at a base station via a cellular connection. In this paper, a novel method of cellular D2D–MEC system is proposed, which enables task offloading and resource allocation meanwhile improving the execution efficiency of each device with a low latency. We consider the partial offloading strategy and divide the task into local and remote computing, both of which can be executed in parallel through different computational modes. Instead of allocating system resources from a macroscopic view, we innovatively study both the task offloading strategy and the computing efficiency of each device from a microscopic perspective. By taking both task offloading policy and computation resource allocation into consideration, the optimization problem is formulated as that of maximized computing efficiency. As the formulated problem is a mixed-integer non-linear problem, we thus propose a two-phase heuristic algorithm by jointly considering helper selection and computation resources allocation. In the first phase, we obtain the suboptimal helper selection policy. In the second phase, the MEC computation resources allocation strategy is achieved. The proposed low complexity dichotomy algorithm (LCDA) is used to match the subtask-helper pair. The simulation results demonstrate the superiority of the proposed D2D-enhanced MEC system over some traditional D2D–MEC algorithms.

Interstitial fluid (ISF) is a body fluid that fills, surrounds cells and contains various biomarkers, but it has been challenging to extract ISF in a reliable and sufficient amount with high speed. To address the issues, we developed the tilted microneedle ISF collecting system (TMICS) fabricated by 3D printing. In this system, the microneedle (MN) was inserted at 66° to the skin by TMICS so that the MN length could be extended within a safe range of skin penetration. Moreover, TMICS incorporating three MN patches created reliable ISF collecting conditions by penetrating the skin at consistent angle and force, 4.9 N. Due to the MN length increase and the patch number expansion, the surface area of the penetrated tissue was increased, thereby confirming that ISF extraction efficiency was improved. Skin ISF was collected into the paper reservoir on the patch, and the absorbed area was converted into a volume. ISF extraction from the rat skin in vivo by TMICS was well tolerated, and the 2.9 μL of ISF was obtained within 30 s. Therefore, TMICS is promising to apply in the diagnosis of multiple biomarkers in ISF with high speed and stability.

The diatom shell is an example of complex siliceous structure which is a suitable model to demonstrate the process of digging into the third dimension using modern visualization techniques. This paper demonstrates importance of a comprehensive multi-length scale approach to the bio-structures/materials with the usage of state-of-the-art imaging techniques. Imaging of diatoms applying visible light, electron and X-ray microscopy provide a deeper insight into the morphology of their frustules.

The main contribution of this paper is to study the spin caloritronic effects in defected graphene/silicene nanoribbon (GSNR) junctions. Each step-like GSNR is subjected to the ferromagnetic exchange and local external electric fields, and their responses are determined using the nonequilibrium Greens function (NEGF) approach. To further study the thermoelectric (TE) properties of the GSNRs, three defect arrangements of divacancies (DVs) are also considered for a larger system, and their responses are re-evaluated. The results demonstrate that the defected GSNRs with the DVs can provide an almost perfect thermal spin filtering effect (SFE), and spin switching. A negative differential thermoelectric resistance (NDTR) effect and high spin polarization efficiency (SPE) larger than 99.99 percent are obtained. The system with the DV defects can show a large spin-dependent Seebeck coefficient, equal to 1.2 mV/K, which is relatively large and acceptable. Appropriate thermal and electronic properties of the GSNRs can also be obtained by tuning up the DV orientation in the device region. Accordingly, the step-like GSNRs can be employed to produce high efficiency spin caloritronic devices with various features in practical applications., Comment: 23 pages, 9 figures

Accuracy in copying a figure is one of the most sensitive measures of visuo-constructional ability. However, drawing tasks also involve other cognitive and motor abilities, which may influence the final graphic produced. Nevertheless, these aspects are not taken into account in conventional scoring methodologies. In this study, we have implemented a novel Tablet-based assessment, acquiring data and information for the entire execution of the Rey Complex Figure copy task (T-RCF). This system extracts 12 indices capturing various dimensions of drawing abilities. We have also analysed the structure of relationships between these indices and provided insights into the constructs that they capture. 102 healthy adults completed the T-RCF. A subgroup of 35 participants also completed a paper-and-pencil drawing battery from which constructional, procedural, and motor measures were obtained. Principal component analysis of the T-RCF indices was performed, identifying spatial, procedural and kinematic components as distinct dimensions of drawing execution. Accordingly, a composite score for each dimension was determined. Correlational analyses provided indications of their validity by showing that spatial, procedural, and kinematic scores were associated with constructional, organisational and motor measures of drawing, respectively. Importantly, final copy accuracy was found to be associated with all of these aspects of drawing. In conclusion, copying complex figures entails an interplay of multiple functions. T-RCF provides a unique opportunity to analyse the entire drawing process and to extract scores for three critical dimensions of drawing execution.

With the widely application of cluster analysis, the number of clusters is gradually increasing, as is the difficulty in selecting the judgment indicators of cluster numbers. Also, small clusters are crucial to discovering the extreme characteristics of data samples, but current clustering algorithms focus mainly on analyzing large clusters. In this paper, a bidirectional clustering algorithm based on local density (BCALoD) is proposed. BCALoD establishes the connection between data points based on local density, can automatically determine the number of clusters, is more sensitive to small clusters, and can reduce the adjusted parameters to a minimum. On the basis of the robustness of cluster number to noise, a denoising method suitable for BCALoD is proposed. Different cutoff distance and cutoff density are assigned to each data cluster, which results in improved clustering performance. Clustering ability of BCALoD is verified by randomly generated datasets and city light satellite images.

In this paper, we investigate the Yangian relations of Heisenberg spin chain systems. Firstly, we consider the closed XXZ spin chain model, through the Heisenberg spin XXZ model, we found the Hamiltonians for one kind system of three adjacent partial particles interaction systems. The model’s constitution rules of energy levels and energy states which expand from the few-particle system to multi-particle system have good regularity. In this system, we found Yangian’s law and illustrate it through graphs. Secondly, we further consider the closed XXZ spin chain’s generalization of other three neighboring particles interaction systems from few-particle system to multi-particle system. Finally, we also discussed the laws of the three adjacent particles system of some models, they are the XXZ model with twist boundary condition, the open XXZ spin chain model and the XXZ model containing the next neighbor. In addition, not only XXZ model, XXX model, XY model and Ising model, but the relevant laws of spin-1 systems of these models were also discussed, they have similar rules to the XXZ model. Through calculation and research, the eigensystems of these models all have good Yangian and constitution laws.

Warm thanks to Jacqui Sykoff for substantially improving the readability of former versions of the manuscript. GM was supported by the Hungarian Ministry for Innovation and Technology within the framework of the Thematic Excellence Programme 2020 (TKP2020-IKA-12, TKP2020-NKA-16).. KT was supported by institutional research funding IUT (34-8) of the Estonian Ministry of Education and Research. This paper is a contribution to the project URBILAND (PID2019-107423GA-I00/SRA 1013039/501100011033), funded by the Spanish Research Agency., Climate and land use are rapidly changing environmental conditions. Behavioral responses to such global perturbations can be used to incorporate interspecific interactions into predictive models of population responses to global change. Flight initiation distance (FID) reflects antipredator behaviour defined as the distance at which an individual takes flight when approached by a human, under standardized conditions. This behavioural trait results from a balance between disturbance, predation risk, food availability and physiological needs, and it is related to geographical range and population trends in European birds. Using 32,145 records of flight initiation distances for 229 bird species during 2006-2019 in 24 European localities, we show that FIDs decreased with increasing temperature and precipitation, as expected if foraging success decreased under warm and humid conditions. Trends were further altered by latitude, urbanisation and body mass, as expected if climate effects on FIDs were mediated by food abundance and need, differing according to position in food webs, supporting foraging models. This provides evidence for a role of behavioural responses within food webs on how bird populations and communities are affected by global change., Hungarian Ministry for Innovation and Technology TKP2020-IKA-12 TKP2020-NKA-16, Ministry of Education and Research, Estonia 34-8, Spanish Research Agency PID2019-107423GA-I00/SRA 1013039/501100011033

Evaluating the effect of porosity and ambient temperature on mechanical characteristics and thermal conductivity is vital for practical application and fundamental material property. Here we report that ambient temperature and porosity greatly influence fracture behavior and material properties. With the existence of the pore, the most significant stresses will be concentrated around the pore position during the uniaxial and biaxial processes, making fracture easier to occur than when tensing the perfect sheet. Ultimate strength and Young’s modulus degrade as porosity increases. The ultimate strength and Young's modulus in the zigzag direction is lower than the armchair one, proving that the borophene membrane has anisotropy characteristics. The deformation behavior of borophene sheets when stretching biaxial is more complicated and rough than that of uniaxial tension. In addition, the results show that the ultimate strength, failure strain, and Young’s modulus degrade with growing temperature. Besides the tensile test, this paper also uses the non-equilibrium molecular dynamics (NEMD) approach to investigate the effects of length size, porosity, and temperature on the thermal conductivity (κ) of borophene membranes. The result points out that κ increases as the length increases. As the ambient temperature increases, κ decreases. Interestingly, the more porosity increases, the more κ decreases. Moreover, the results also show that the borophene membrane is anisotropic in heat transfer.

Quantum computers and algorithms can offer exponential performance improvement over some NP-complete programs which cannot be run efficiently through a Von Neumann computing approach. In this paper, we present BayeSyn, which utilizes an enhanced stochastic program synthesis and Bayesian optimization to automatically generate quantum programs from high-level languages subject to certain constraints. We find that stochastic synthesis can comparatively and efficiently generate a program with a lower cost from the high dimensional program space. We also realize that hyperparameters used in stochastic synthesis play a significant role in determining the optimal program. Therefore, BayeSyn utilizes Bayesian optimization to fine-tune such parameters to generate a suitable quantum program.

Rett Syndrome (RTT), which affects approximately 1:10.000 live births, is a X-linked pervasive neuro-developmental disorder which is caused, in the vast majority of cases, by a sporadic mutation in the Methyl-CpG-binding protein-2 (MeCP2) gene. This is a transcriptional activator/repressor with presumed pleiotropic activities. The broad tissue expression of MeCP2 suggests that it may be involved in several metabolic pathways, but the molecular mechanisms which provoke the onset and progression of the syndrome are largely unknown. In this paper, we report that primary fibroblasts that have been isolated from RTT patients display a defective formation of autophagosomes under conditions of nutrient starvation and that the mature Red Blood Cells of some RTT patients retain mitochondria. Moreover, we provide evidence regarding the accumulation of the p62/SQSTM1 protein and ubiquitin-aggregated structures in the cerebellum of Mecp2 knockout mouse model (Mecp2

In this paper, we first synthesis three-dimensional jasmine-like Cu@L-aspartic acid(L-ASP) inorganic–organic hybrid nanoflowers to load palladium-platinum nanoparticles (Pd–Pt NPs) as the signal enhancer in order to quantify intracellular speckle-type POZ domain protein. Scanning electron microscope, fourier transform infrared, energy dispersive spectrometer, X-ray photoelectron spectroscopy analysis was used to characterize the newly synthesized materials. The newly formed Cu@L-Asp/Pd-PtNPs can catalyze the decomposition of hydrogen peroxide and exhibit excellent catalytic performance. When different concentration of speckle-type POZ domain protein is captured by speckle-type POZ domain protein antibody linked to the surface of Cu@L-Asp/Pd–Pt NPs, the current signal decreases with the increase concentration of speckle-type POZ domain protein. After optimization, the speckle-type POZ domain protein immunosensor exhibited a good linear response over a concentration range from 0.1–1 ng mL−1 with a low detection limit of 19 fg mL−1. The proposed sensor demonstrates good stability within 28 days, acceptable reproducibility (RSD = 0.52%) and selectivity to the speckle-type POZ domain protein in the presence of possible interfering substances and has potential application for detecting other intracellular macromolecular substances.

Epiretinal prostheses aim at electrically stimulating the inner most surviving retinal cells-retinal ganglion cells (RGCs)-to restore partial sight to the blind. Recent tests in patients with epiretinal implants have revealed that electrical stimulation of the retina results in the percept of color of the elicited phosphenes, which depends on the frequency of stimulation. This paper presents computational results that are predictive of this finding and further support our understanding of the mechanisms of color encoding in electrical stimulation of retina, which could prove pivotal for the design of advanced retinal prosthetics that elicit both percept and color. This provides, for the first time, a directly applicable "amplitude-frequency" stimulation strategy to "encode color" in future retinal prosthetics through a predictive computational tool to selectively target small bistratified cells, which have been shown to contribute to "blue-yellow" color opponency in the retinal circuitry. The presented results are validated with experimental data reported in the literature and correlated with findings in blind patients with a retinal prosthetic implant collected by our group.

This paper presents a miniaturized ultra-wideband (UWB) antipodal Vivaldi antenna (AVA) array with low-scattering characteristics integrated a hybrid diffusive-absorptive metasurface. Periodic elliptical slots at the outer edges and a dielectric lens are utilized for antenna element to improve performances including miniaturized size, wide bandwidth, and high gain. The optimized element is fabricated and measured, the results demonstrate that the − 10 dB impedance bandwidth is 4.5–50 GHz with a ratio bandwidth (fH/fL) of 11.1:1, and the maximum gain at 35 GHz is 12.7 dBi, which are in good agreement with simulation. By loading an optimized Minkowski-shaped metasurface as the ground reflector, which combines the multielement phase cancellation (MEPC) and EM absorption technology, the 4 × 4 array realizes a low radar cross section (RCS) without the radiation performance degradation. Simulated and measured results show that the proposed low-scattering array has a 10-dB RCS reduction band ranging from 5 to 50 GHz at normal incidence for both polarizations. Furthermore, the array structure shows extremely low-observable capability, which is larger than 15 dB of the RCS reduction from 7.1 to 50 GHz with a ratio bandwidth of 7.0:1. The results verify the feasibility of improving the performance of antenna and the UWB low-scattering functionality.

Soilless cultivation systems that provide plant management in soilless conditions in which the supply of water and of minerals is carried out by nutrient solution, with or without a growing medium. The main aim of this paper was to investigate the possibility of growing basil under three soilless systems (aeroponic, hydroponic and peatmoss slab systems). A model was developed to predict the nutrients consumption by basil plants. Shoot and root height, fresh and dry mass of whole plant, nutrients uptake, and oil content were studied during the growth period (after 4 and 7 weeks from transplanting). The results indicated that the shoot lengths of basil plants were 62.00 ± 2.65, 57.83 ± 7.42 and 48.77 ± 2.89 cm after 4 weeks and 71.67 ± 2.89, 65.67 ± 1.15 and 62.33 ± 2.31cm after 7 weeks from transplanting for aeroponic, hydroponic and peatmoss slabs, respectively. The highest value of root height of basil plants was 37.67 ± 6.66 cm for aeroponic system. The dry mass of shoot of basil plants ranged from 28.48 ± 0.91 to 44.77 ± 0.97 and 72.98 ± 0.83 to 117.93 ± 1.40 g plant-1 after 4 and 7weeks from transplanting, respectively. The highest values of the N, P, K, Ca and Mg uptakes were 262.50 ± 6.84, 74.34 ± 2.90, 195.13 ± 4.09, 132.41 ± 1.54 and 41.81 ± 0.83 mg plant-1 and 753.99 ± 5.65, 224.88 ± 3.05, 449.75 ± 4.59, 529.12 ± 6.63 and 112.44 ± 1.67 mg plant-1 after 4 and 7 weeks from transplanting, respectively. The basil oil content ranged from 1.129 ± 0.020 to 2.520 ± 0.021 and 2.664 ± 0.291 to 6.318 ± 0.375 g plant-1 after 4 and 7weeks from transplanting, respectively at the same pervious order. The production costs of basil plant were 2.93, 5.27 and 6.24 EGP kg-1 of plant. The model results were in a reasonable agreement with the experimental ones.

In this paper, influence of InP coupling cavity on Fano resonance of sub wavelength MIM waveguide was studied by FDTD. It was observed that the resonant wavelengths of mode mj (j = 1, 2, 3) were closely related with the height H2 of InP coupling cavity. In addition, before and after the addition of air cavity, the relative farfield intensities I was a function of height H2. Therefore, InP as discrete state could be used as the filling dielectrics of Fano resonance in the MIM waveguide.

Neural modelling tools are increasingly employed to describe, explain, and predict the human brain’s behavior. Among them, spiking neural networks (SNNs) make possible the simulation of neural activity at the level of single neurons, but their use is often threatened by the resources needed in terms of processing capabilities and memory. Emerging applications where a low energy burden is required (e.g. implanted neuroprostheses) motivate the exploration of new strategies able to capture the relevant principles of neuronal dynamics in reduced and efficient models. The recent Leaky Integrate-and-Fire with Latency (LIFL) spiking neuron model shows some realistic neuronal features and efficiency at the same time, a combination of characteristics that may result appealing for SNN-based brain modelling. In this paper we introduce FNS, the first LIFL-based SNN framework, which combines spiking/synaptic modelling with the event-driven approach, allowing us to define heterogeneous neuron groups and multi-scale connectivity, with delayed connections and plastic synapses. FNS allows multi-thread, precise simulations, integrating a novel parallelization strategy and a mechanism of periodic dumping. We evaluate the performance of FNS in terms of simulation time and used memory, and compare it with those obtained with neuronal models having a similar neurocomputational profile, implemented in NEST, showing that FNS performs better in both scenarios. FNS can be advantageously used to explore the interaction within and between populations of spiking neurons, even for long time-scales and with a limited hardware configuration.

In this paper, the distribution of relaxation times (DRTs) functions are calculated numerically in Matlab for synthetic impedance data from single parallel $$RC$$ RC circuit and two parallel $$RC$$ RC circuits connected in series, experimental impedance data from supercapacitors and α-LiFeO2 anode based Li ion batteries. The quality of the impedance data is checked with the Kramers–Krönig (KK) relations. The DRTs are calculated within the KK compatible regime for all the systems using Tikhonov regularization (TR) method. Here we use a fast and simple L-curve method to estimate the TR parameter (λ) for regularization of the Fredholm integral equations of first kind in impedance. Estimation of the regularization parameters are performed effectively from the offset of the global corner of the L-curve rather than simply using the global corner. The physical significances of DRT peaks are also discussed by calculating the effective resistances and capacitances coupled with peak fitting program. For instance, two peaks in the DRTs justify the electrical double layer capacitance and ion diffusion phenomena for supercapacitors in low to intermediate frequencies respectively. Moreover, the surface film effect, Li/electrolyte and electrode/electrolyte charge transfer related processes are identified for α-LiFeO2 anode based Li-ion batteries. This estimation of the offset of the global corner extends the L-curve approach coupled with the Tikhonov regularization in the field of electrochemistry and can also be applied in similar process detection methods.