Full Structure Research Articles

Recovering crossed random effects in mixed-effects models using model averaging

Random effects contain crucial information to understand the variability of the processes under study in mixed-effects models with crossed random effects (MEMs-CR). Given that model selection makes all-or-nothing decisions regarding to the inclusion of model parameters, we evaluated if model averaging could deal with model uncertainty to recover random effects of MEMs-CR. Specifically, we analyzed the bias and the root mean squared error (RMSE) of the estimations of the variances of random effects using model averaging with Akaike weights and Bayesian model averaging with BIC posterior probabilities, comparing them with two alternative analytical strategies as benchmarks: AIC and BIC model selection, and fitting a full random structure. A simulation study was conducted manipulating sample sizes for subjects and items, and the variance of random effects. Results showed that model averaging, especially Akaike weights, can adequately recover random variances, given a minimum sample size in the modeled clusters. Thus, we endorse using model averaging to deal with model uncertainty in MEMs-CR. An empirical illustration is provided to ease the usability of model averaging.

Third-order optical nonlinearity of one-dimensional Dirac fermions

The optical nonlinearity of Dirac fermions in two and three dimensions show unique properties determined by analytic expressions in the independent particle approximation, which promotes their host materials as potential candidates for providing optical nonlinear functionalities. In this work we theoretically study the third-order optical nonlinearity for one-dimensional Dirac fermions and obtain analytical expressions for third-order optical conductivities at general light frequencies. The conductivity includes many resonant peaks induced by the resonant optical transitions associated with intraband motion as well as one-, two-, and three-photon interband processes. The conductivities for field-induced second harmonic generation and third harmonic generation are discussed in detail. To connect with real materials, we choose armchair graphene nanoribbons, which host one-dimensional Dirac fermions for its low energy electronic excitation, and our analytical expressions are applied to get the third-order conductivity for harmonic generations with different ribbon width. By comparing with numerical results evaluated from a full band structure in a tight binding model, the analytic and numerical results agree pretty well for photon energy below 2.5 eV.

Prediction of DNA rejoining kinetics and cell survival after proton irradiation for V79 cells using Geant4-DNA

Purpose:Track structure Monte Carlo (MC) codes have achieved successful outcomes in the quantitative investigation of radiation-induced initial DNA damage. The aim of the present study is to extend a Geant4-DNA radiobiological application by incorporating a feature allowing for the prediction of DNA rejoining kinetics and corresponding cell surviving fraction along time after irradiation, for a Chinese hamster V79 cell line, which is one of the most popular and widely investigated cell lines in radiobiology. Methods:We implemented the Two-Lesion Kinetics (TLK) model, originally proposed by Stewart, which allows for simulations to calculate residual DNA damage and surviving fraction along time via the number of initial DNA damage and its complexity as inputs. Results:By optimizing the model parameters of the TLK model in accordance to the experimental data on V79, we were able to predict both DNA rejoining kinetics at low linear energy transfers (LET) and cell surviving fraction. Conclusion:This is the first study to demonstrate the implementation of both the cell surviving fraction and the DNA rejoining kinetics with the estimated initial DNA damage, in a realistic cell geometrical model simulated by full track structure MC simulations at DNA level and for various LET. These simulation and model make the link between mechanistic physical/chemical damage processes and these two specific biological endpoints.

A series of nanosized Cu(II) complexes based on sulfonamide azo dye ligands: An insight into complexes molecular structures, antimicrobial, antitumor and catalytic performance for oxidative dimerization of 2‐aminophenol

The two azo dye ligands named 4‐(2,4‐dihydroxy‐5‐formylphen‐1‐ylazo)‐N‐thiazol‐2‐yl‐benzenesulfon amide (H3TPBS) and 4‐(2,4‐dihydroxy‐phenylazo)‐N‐(3,4‐dimethyl‐1,2‐oxazol‐5 yl)benzenesulfonamide (H3IPBS) were employed for the synthesis of a series of Cu(II) chelates through the reaction of the ligands with Cu(II) salts of different anions. Full structure affirmation of all complexes has been done. Analytical results confirmed the formation of the metal chelates in the molar ratio 2:1 (M:L). Ultraviolet–visible spectra and magnetic moment proved the formation of complexes in square planar and square pyramidal geometries. Antimicrobic activity of the synthesized complexes has been assigned and compared with their parent ligands and also compared with standard antibiotic drugs showing enhanced activity over both the ligands and the standard drugs. The antitumor efficacy of the complexes has been also evaluated contra the two cell lines A‐549 cells (human Lung cancer cell line) and Panc‐1 (Pancreatic carcinoma) and compared with the standard drug Vinblastine. Additionally, The Cu(II) chelates were examined for their activity in oxidation coupling of o‐aminophenol (OAP) to 2‐aminophenoxazine‐3‐one (APX) in DMF solvent in open air atmosphere. The examined complexes afforded low to relatively high efficiency with TOF number from 0.27–78.12 h−1 with increased activity for complexes 1, 3, 5 and 7 incorporating Cl− or NO3− anions in their first coordination sphere.

Reconstructing the full modal structure of photonic states by stimulated-emission tomography in the low-gain regime

Stimulated emission tomography (SET) is a powerful and successful technique to both improve the resolution and experimentally simplify the task of determining the modal properties of biphotons. In the present paper we provide a theoretical description of SET valid for any quadratic coupling regime between a nonlinear medium and pump fields generating photons by pairs in the low-gain regime. We use our results to obtain not only information about the associated modal function modulus but also its phase, for any mode, and we discuss the specific case of time-frequency variables as well as the quantities and limitations involved in the measurement resolution.

Influence of Copper-Based Fillers on Structural and Mechanical Properties of Polylactic Acid Composites

The importance of promising composites in modern materials science is constantly increasing. The use of various fillers or additives is associated with their influence not only on the defining properties of the composite, but also on physical and mechanical characteristics of the material. In this case, the distribution of the additive and its wetting with a polymer play an important role. The problem highlighted in this article is the influence of different copper-containing fillers (copper (II) sulphate powder, micro-sized copper (II) oxide powder, and nano-structured copper (II) oxide-based hollow microspheres) on the technological and physical–mechanical properties of the composites based on polylactic acid (PLA). The hollow microspheres of copper (II) oxide have been obtained by ultrasonic spray atomization via pyrolysis of copper (II) nitrate. The structure of the copper-based additives has been studied using X-ray diffraction, scanning electron microscopy, and static light scattering. For the PLA-composites, scanning electron microscopy, differential scanning calorimetry, stress-strain properties testing, and density analysis have been performed. The plasticizing effect of polycaprolactone and polyethylene glycol has been studied for the highly filled PLA/CuSO4 composite. The samples of PLA with over 2 wt.% of CuO microspheres have a full volume-filling and percolation structure of the additive’s particles. Due to the regular spherical shape of the particles and a lower specific volume, CuO hollow microspheres are uniformly distributed in the PLA matrix acting as a structuring and reinforcing modifier. Differential scanning analysis showed heterogeneous crystallization on CuO particles with an increase in the degree of crystallinity and the melting point of the polymer. It has been shown that the pre-masterbatching technology and adding plasticizers to obtain PLA composites contribute minimizing defects and enhance mechanical properties.

LRFFNet: Large Receptive Field Feature Fusion Network for Semantic Segmentation of SAR Images in Building Areas

There are limited studies on the semantic segmentation of high-resolution synthetic aperture radar (SAR) images in building areas due to speckle noise and geometric distortion. For this challenge, we propose the large receptive field feature fusion network (LRFFNet), which contains a feature extractor, a cascade feature pyramid module (CFP), a large receptive field channel attention module (LFCA), and an auxiliary branch. SAR images only contain single-channel information and have a low signal-to-noise ratio. Using only one level of features extracted by the feature extractor will result in poor segmentation results. Therefore, we design the CFP module; it can integrate different levels of features through multi-path connection. Due to the problem of geometric distortion in SAR images, the structural and semantic information is not obvious. In order to pick out feature channels that are useful for segmentation, we design the LFCA module, which can reassign the weight of channels through the channel attention mechanism with a large receptive field to help the network focus on more effective channels. SAR images do not include color information, and the identification of ground object categories is prone to errors, so we design the auxiliary branch. The branch uses the full convolution structure to optimize training results and reduces the phenomenon of recognizing objects outside the building area as buildings. Compared with state-of-the-art (SOTA) methods, our proposed network achieves higher scores in evaluation indicators and shows excellent competitiveness.

A hybrid analytic–numerical formulation for the vibration analysis of a cylindrical shell coupled with an internal flexural floor structure

A hybrid analytic–numerical formulation is developed to study the vibration behaviors of a cylindrical shell coupled with an internal flexural floor structure. The full structure is divided into a cylindrical shell, axisymmetric annular plates and a non-axisymmetric floor structure. The cylindrical shell and annular plates are analyzed by the analytic dynamic stiffness method (DSM) while the floor is modeled by the finite element method (FEM), so the line connections between the cylindrical shell and interior floor degrade into discrete point connections. At each coupling point, virtual springs are used to couple the cylindrical shell and interior floor, and coupling conditions at six Dofs are fully taken into consideration. In DSM, the displacement solutions of the cylindrical shell and annular plate are described by exponential functions and Bessel functions, respectively. In FEM, the dynamic condensation technique is adopted to reduce the model Dofs, while the main dynamic characteristic of the FEM model is preserved as much as possible.To verify the accuracy and effectiveness of present formulation, vibration results calculated by present method are compared with those obtained from FEM and a test experiment. Moreover, the effects of ribs, bulkheads, coupling conditions, boundary conditions of the shell and structural damping on the vibration responses are also investigated.

Slit-Strip Ising Boundary Conformal Field Theory 1: Discrete and Continuous Function Spaces

This is the first in a series of articles about recovering the full algebraic structure of a boundary conformal field theory (CFT) from the scaling limit of the critical Ising model in slit-strip geometry. Here, we introduce spaces of holomorphic functions in continuum domains as well as corresponding spaces of discrete holomorphic functions in lattice domains. We find distinguished sets of functions characterized by their singular behavior in the three infinite directions in the slit-strip domains, and note in particular that natural subsets of these functions span analogues of Hardy spaces. We prove convergence results of the distinguished discrete holomorphic functions to the continuum ones. In the subsequent articles, the discrete holomorphic functions will be used for the calculation of the Ising model fusion coefficients (as well as for the diagonalization of the Ising transfer matrix), and the convergence of the functions is used to prove the convergence of the fusion coefficients. It will also be shown that the vertex operator algebra of the boundary conformal field theory can be recovered from the limit of the fusion coefficients via geometric transformations involving the distinguished continuum functions.

A High-Performance Full Adder Design with Low Area, Power and Delay

A new one-bit adder architecture is described that may be used with a variety of logics, including Static CMOS, transmission gates, the Transmission Full Adder (TFA), and the New-14T Gate Diffusion Input Method (GDI). The Modified Gate Diffusion Input Method (MGDI) is used to suggest a novel structure design for a full adder. The full adder circuit is used in the Modified Gate Diffusion Input Method (MGDI), and experimental results demonstrate its superior performance compared to traditional methods. Full adders with multistage arrangements are also considered, as their performance may differ from that of a 1-bit full adder. As a result, two applications of multistage full adder structures, the ripple carry adder (RCA) and 6:2 compressor are used to analyze the findings. The power, area and delay are reduced by around 40% when compared to the existing methods. All the designs are simulated using Tanner EDA. The proposed full adder has a lower transistor count (6 or 7 transistors), lower power dissipation, and less delay than previous designs, according to simulation data.

Large-scale photonic natural language processing

Modern machine-learning applications require huge artificial networks demanding computational power and memory. Light-based platforms promise ultrafast and energy-efficient hardware, which may help realize next-generation data processing devices. However, current photonic networks are limited by the number of input-output nodes that can be processed in a single shot. This restricted network capacity prevents their application to relevant large-scale problems such as natural language processing. Here, we realize a photonic processor for supervised learning with a capacity exceeding 1.5 × 10 10 optical nodes, more than one order of magnitude larger than any previous implementation, which enables photonic large-scale text encoding and classification. By exploiting the full three-dimensional structure of the optical field propagating in free space, we overcome the interpolation threshold and reach the over-parameterized region of machine learning, a condition that allows high-performance sentiment analysis with a minimal fraction of training points. Our results provide a novel solution to scale up light-driven computing and open the route to photonic natural language processing.

Process flexibility in the presence of product modularity: Does modularity help?

One of the primary goals of supply chain management is to reduce supply–demand mismatch (SDM). Product variety explosion is a common occurrence across industries and is one of the primary sources of demand uncertainty, resulting in SDM and the associated costs. Researchers and practitioners have investigated the role of process flexibility in addressing SDM caused by product variety. This study investigates the impact of product modularity on the benefits of process flexibility. It answers the critical question: “Does introducing modularity in product structure lead to reduced process flexibility requirements?”. As flexibility investment is costly, the reduced requirement in the presence of product modularity positively impacts financially constrained manufacturing firms (e.g., those belonging to the SME sector or start-up ecosystem). Two stochastic optimization problems are formulated, one with two products and one with multiple products. The results show that in the presence of product modularity, the optimal production policy handles demand uncertainty better and thus reduces SDM cost more than the integrated product case. Further, the need for investment in process flexibility decreases in the presence of modularity. In the multi-product formulation, the researchers investigate the d-chain process flexibility structure requirement. In the presence of product modularity, a 2-chain process flexibility structure is sufficient to almost achieve the performance of a full flexibility structure, in contrast to integrated product scenarios where at least 3 to 4-chains are required.

Resonant Inelastic Soft X-ray Scattering and X-ray Emission Spectroscopy of Solid Proline and Proline Solutions.

The amino group of proline is part of a pyrrolidine ring, which makes it unique among the proteinogenic amino acids. To unravel its full electronic structure, proline in solid state and aqueous solution is investigated using X-ray emission spectroscopy and resonant inelastic soft X-ray scattering. By controlling the pH value of the solution, proline is studied in its cationic, zwitterionic, and anionic configurations. The spectra are analyzed within a "building-block principle" by comparing with suitable reference molecules, i.e., acetic acid, cysteine, and pyrrolidine, as well as with spectral calculations based on density functional theory. We find that the electronic structure of the carboxyl group of proline is very similar to that of other amino acids as well as acetic acid. In contrast, the electronic structure of the amino group is significantly different and strongly influenced by the ring structure of proline.

Mechanism of Melatonin Metabolism by CYP1A1: What Determines the Bifurcation Pathways of Hydroxylation versus Deformylation?

Melatonin, a widely applied cosmetic active ingredient, has a variety of uses as a skin protector through antioxidant and anti-inflammatory functions as well as giving the body UV-induced defenses and immune system support. In the body, melatonin is synthesized from a tryptophan amino acid in a cascade of reactions, but as melatonin is toxic at high concentrations, it is metabolized in the human skin by the cytochrome P450 enzymes. The P450s are diverse heme-based mono-oxygenases that catalyze oxygen atom-transfer processes that trigger metabolism and detoxification reactions in the body. In the catalytic cycle of the P450s, a short-lived high-valent iron(IV)-oxo heme cation radical is formed that has been proposed to be the active oxidant. How and why it activates melatonin in the human body and what the origin of the product distributions is, are unknown. This encouraged us to do a detailed computational study on a typical human P450 isozyme, namely CYP1A1. We initially did a series of molecular dynamics simulations with substrate docked into several orientations. These simulations reveal a number of stable substrate-bound positions in the active site, which may lead to differences in substrate activation channels. Using tunneling analysis on the full protein structures, we show that two of the four binding conformations lead to open substrate-binding pockets. As a result, in these open pockets, the substrate is not tightly bound and can escape back into the solution. In the closed conformations, in contrast, the substrate is mainly oriented with the methoxy group pointing toward the heme, although under a different angle. We then created large quantum cluster models of the enzyme and focused on the chemical reaction mechanisms for melatonin activation, leading to competitive O-demethylation and C6-aromatic hydroxylation pathways. The calculations show that active site positioning determines the product distributions, but the bond that is activated is not necessarily closest to the heme in the enzyme-substrate complex. As such, the docking and molecular dynamics positioning of the substrate versus oxidant can give misleading predictions on product distributions. In particular, in quantum mechanics cluster model I, we observe that through a tight hydrogen bonding network, a preferential 6-hydroxylation of melatonin is obtained. However, O-demethylation becomes possible in alternative substrate-binding orientations that have the C6-aromatic ring position shielded. Finally, we investigated enzymatic and non-enzymatic O-demethylation processes and show that the hydrogen bonding network in the substrate-binding pocket can assist and perform this step prior to product release from the enzyme.

SAR Target Recognition Based on Inception and Fully Convolutional Neural Network Combining Amplitude Domain Multiplicative Filtering Method

The research of Synthetic aperture radar (SAR) target recognition plays a significant role in military and civilian fields. However, for small sample SAR target recognition, there are some problems that need to be solved urgently, including low recognition accuracy, slow training convergence rate, and serious overfitting. Aiming at the above problems, we propose a recognition method based on Inception and Fully Convolutional Neural Network (IFCNN) combined with Amplitude Domain Multiplicative Filtering (ADMF) image processing. To improve the recognition accuracy and convergence rate, the ADMF method is utilized to construct the pretraining set, and the initial parameters of the network are optimized by pretraining. In addition, this paper builds the IFCNN model by introducing the Inception structure and the mixed progressive convolution layer into the FCNN. The full convolution structure of FCNN is effective to alleviate the problem of network overfitting. The Inception structure can enhance the sparsity of features and improve the network classification ability. Meanwhile, the mixed progressive convolution layers can accelerate training. Based on the MSTAR dataset, the experimental results show that the method proposed achieves an average precision of 88.95% and the training convergence rate is significantly improved in small sample scenarios.

Experience of interaction with the ecological framework of a modern city

The article considers various aspects of constructing and applying the concept of urban ecological framework, and also practices of direct interaction. The environmental discourse assumes a more reflexive attitude towards the flora and fauna representatives, regarding them as full social structure subjects. Taking into account high rates of urbanization, it tends to be more topical to analyze human interaction with the plants within the urban space. In the scope of this paper, we reviewed theoretical approaches to the conceptualization of the concepts related to urban vegetation, highlighting the concept of city ecological framework as the most optimally corresponding to the New Ecological Paradigm. Further, the author analyzed the urban planning documents of 15 Russian million cities where the city garden problems are reviewed at various reflective levels. Besides, the work presents the results of an experiment on the environmental audit of urban areas, when participants analyzed the structure of urban ecological framework and its separate elements. The experiment showed a low level of the participants ecological culture, because the identification of specific plant species caused serious difficulties, and the scenarios of personal interaction with plants were rather poor and were limited to passive perception. However, the informing orientation of the experiment encouraged the participants to self-reflect, that raised the participants awareness about the structure and functions of the ecological framework and expanded personal strategies for interacting with it.

Influence of torsional stiffness in double-angle open-web joist and joist girder chords

The double angle chords of open-web steel joists are often designed to efficiently support loading with relatively slender sections, which introduces buckling instabilities that are treated differently by various design standards. This study investigates the buckling behavior of double angles, focusing on the importance of flexural–torsional buckling. A theoretical inelastic buckling investigation considering current design practices and known steel behavior demonstrates how flexural–torsional buckling does not control for all double angle configurations. Subsequent investigation focuses on double angles theoretically susceptible to flexural–torsional buckling, while implementing finite element modeling of full joist structures and isolated chord segments. The resulting elastic eigenbuckling analysis and geometrically and materially nonlinear analysis with imperfections captures significant twisting of individual angles in the built-up section; however, global flexural–torsional buckling was not observed to control. Most double angle configurations are controlled by flexural buckling due to an increased flexural–torsional buckling capacity. This result is attributed to the observed increased torsional stiffness of the chords, which is typically not considered in design. A supplementary investigation indicated this torsional stiffness was primarily a result of torsion being transferred through the stiff chord-to-chord connections, which do not exist in all double angle members. Accounting for the additional torsional stiffness in a theoretical inelastic buckling calculation leads to flexural–torsional buckling not controlling the design of most double angle cross sections considered in this study. Overall, this study indicates that designing double angles in joist structures by only considering flexural buckling with local buckling is reasonable with current industry practices.

Power Factor Compensation for a Single-Phase AC-DC Hybrid Micro-Grid

A single-phase AC-DC Hybrid Micro-Grid (HMG) power flow control strategy is modeled and simulated in this paper. Two AC and two DC zones are separated by a bidirectional interlinking converter (BIC) in the full bridge IGBT structure, which is a typical H-Bridge inverter/rectifier, in the proposed HMG system topology. Based on the DQ transformation theory, the BIC's switching pattern comes from one voltage loop (Vdc) and two power control loops. The transfer of both active and reactive power between the HMG and the public AC Grid is controlled by this control strategy. Additionally, this can be accomplished in either rectifying or inverting modes by utilizing the bidirectional converter. Matlab-Simulink is used to implement and test the simulation model.

Development of a new hydrophobic magnetic biochar for removing oil spills on the water surface

More technologies are urgently needed for combined use to effectively eliminate the effect of oil spills, an environmental problem of widespread concern. Among these technologies, sorption methods are available to remove residual oil and prevent the further spread on the water surface. In this study, biochars, prepared from different feedstock materials and pyrolysis temperatures, were screened and further modified to improve their application in the water environment. Among cornstalk biochar (CSBC), corncob biochar (CCBC), Sophora sawdust biochar (SSBC), and rice husk biochar (RHBC), the CSBC had excellent oil sorption capacity, especially prepared at 350℃ (CSBC350), which has a complete and full pore structure. Furthermore, magnetic and silane agent modifications of CSBC350 (OMBC) were performed to enhance the properties of the magnetic field controllability and hydrophobicity to increase oil sorption. The OMBC exhibited satisfactory oil sorption capacities to crude oil, diesel oil, and engine oil in the water-oil system of 8.77 g g−1, 4.01 g g−1, and 4.44 g g−1, respectively. The sorption process of CSBC350 and OMBC complied with the pseudo-second-order kinetics (R2 > 0.97) and the Langmuir isotherm models (R2 > 0.80) based on the highest regression coefficients. The sorption mechanisms are dominated by hydrophobic forces, pore intercepts, and hydrogen-bond interactions. The biochar adsorbent can availably cooperate with other physical methods to eliminate oil contaminants, which can be an outstanding fuel source for producing heat.Graphical

Development of weld filler material to match the advanced martensitic heat resistance steel G115 and tailoring the performance by tempering temperature

The lack of filler materials is the crucial issue that restricts the wide application of the advanced heat-resistance steel G115 in ultra-super critical (USC) power plants. In the present work, a new welding filler material with alloying system of 8.8Cr-2.7W-2.8Co was successfully developed to fabricate the G115 steel welded joint by the gas tungsten arc welding (GTAW), and post weld heat treatments (PWHT) involving different temperatures were proposed to tailor the mechanical properties. The filler material exhibited perfect compatibility with the base material (BM), and the manufactured welded joint displayed satisfactory appearance and defect-free weld section. After PWHT, full martensitic lath structure decorated with high density of dislocations and dispersed strengthening precipitates M23C6 and MX formed in the weld metal (WM), which was similar with that of the BM. Meanwhile, the welded joint was sensitive to the PWHT temperature, and an optimal combination of hardness (∼240 HV), tensile strength (∼679.9 MPa at 25 °C, and ∼344.6 MPa at 650 °C), elongation (∼13.1% at 25 °C, and ∼15.6% at 650 °C) and impact toughness (∼73.8 J/cm2) could be achieved after PWHT at 760 °C for 240 min. Comprehensively considering the obtained results, the designed filler material was feasible and reliable for matching the novel G115 steel, and satisfied the service demands of the G115 steel pipes in USC power plants.