Search

The structure of calcium aluminosilicate glasses (CaO)x(Al2O3)y(SiO2)1−x−y with the near tectosilicate compositions x ≃ 0.19 and 1 − x − y ≃ 0.61 or x ≃ 0.26 and 1 − x − y ≃ 0.49 was investigated by in situ high-pressure neutron diffraction and 27Al nuclear magnetic resonance (NMR) spectroscopy. The results show three distinct pressure regimes for the transformation of the aluminum coordination environment from tetrahedral to octahedral, which map onto the deformations observed in the production of permanently densified materials. The oxygen packing fraction serves as a marker for signaling a change to the coordination number of the network forming motifs. For a wide variety of permanently densified aluminosilicates, the aluminum speciation shares a common dependence on the reduced density ρ′ = ρ/ρ0, where ρ is the density and ρ0 is its value for the uncompressed material. The observed increase in the Al–O coordination number with ρ′ originates primarily from the formation of six-coordinated aluminum Al(VI) species, the fraction of which increases rapidly beyond a threshold ρ thr ′ ∼ 1.1. The findings are combined to produce a self-consistent model for pressure-induced structural change. Provided the glass network is depolymerized, one-coordinated non-bridging oxygen atoms are consumed to produce two-coordinated bridging oxygen atoms, thus increasing the network connectivity in accordance with the results from 17O NMR experiments. Otherwise, three-coordinated oxygen atoms or triclusters appear, and their fraction is quantified by reference to the mean coordination number of the silicon plus aluminum species. The impact of treating Al(VI) as a network modifier is discussed. [ABSTRACT FROM AUTHOR]

Musculoskeletal modeling, typically implemented using marker-based systems in laboratory environments, is commonly used for noninvasive estimations of loads. Inertial measurement units (IMUs) have become an alternative for the evaluation of kinematics. However, estimates of spine joint contact forces using IMUs have yet to be thoroughly evaluated. Dynamics tasks and static postures from activities of daily living were captured on 11 healthy subjects using both systems simultaneously. Spine kinematics obtained from IMU- and marker-based systems and L4–L5 joint contact forces were compared. Lateral bending resulted in a weak agreement with significant differences between the 2 systems (P =.02, average root mean-squared error = 4.81), whereas flexion–extension and axial rotation exhibited the highest agreement with no significant differences (P <.05, average root mean-squared error = 5.51 and P <.31, average root mean-squared error = 5.08, respectively). All tasks showed excellent correlations (R2 =.76–.99) in estimated loads between systems. Differences in predicted loads at the L4–L5 were only observed during flexion–extension (1041 N vs 947 N, P =.0004) and walking with weights (814 N vs 727 N, P =.004). Different joint reaction force outcomes were obtained in 2 of the 8 tasks between systems, suggesting that IMUs can be robust tools allowing for convenient and less expensive evaluations and for longitudinal assessments inside and outside the laboratory setting. [ABSTRACT FROM AUTHOR]

High-entropy oxides (HEOs) are single phase solid solutions where five or more metals share the same sublattice, giving rise to unexpected features in various fields of applications. Recently, HEOs have emerged as an alternative conversion electrode anode material for next-generation Li-ion batteries, where the combination of several different elements in a single solid solution can synergistically act to overcome some of its main drawbacks, improving performance. Due to their chemical complexity, x-ray absorption spectroscopy (XAS) emerges as an appropriate technique to study the electronic (x-ray absorption near edge structure, XANES) and local structure (extended x-ray absorption fine structure, EXAFS) of these compounds as a function of cycling. This work aims to highlight the capabilities of XAS as an element-specific probe to understand a material's structure at the atomistic level through EXAFS modeling of (MgFeCoNiCuZn)O high-entropy system and how to extract valuable information about the bond distance, number of near neighbors, and local disorder, which are crucial to a full understanding of the electrochemical reaction mechanisms of such battery electrodes. [ABSTRACT FROM AUTHOR]

Product consumption is an important yet understudied aspect of marketing. Over-the-counter medicines present a unique consumption context because consumers are expected to follow product label instructions. For acetaminophen, a widely consumed over-the-counter drug, the authors study which consumers tend to deviate from the label instructions, why they do so, and the interventions that are most promising to mitigate such deviations. They develop a dynamic structural model of consumption that enables them to investigate the probability of different types of label deviations (e.g., >4 g per day) and drivers of such behaviors. Label deviations are infrequent "tail area" behaviors, and the model uncovers them well. The analysis is based on a unique online consumption diary in which consumers select from two classes of acetaminophen products (single ingredient or a combination of ingredients) to treat their pain or non-pain-related symptoms. Consumers have a higher probability of taking >4 g of acetaminophen when they have multiple symptoms, and a variety of observable factors explain the individual propensity to deviate from the label. The authors propose two interventions—a new label instruction and consumer education—to mitigate the observed label deviations and assess the expected impact of each. [ABSTRACT FROM AUTHOR]

In this work, we investigate how exploiting symmetry when creating and modifying structural models may speed up global atomistic structure optimization. We propose a search strategy in which models start from high symmetry configurations and then gradually evolve into lower symmetry models. The algorithm is named cascading symmetry search and is shown to be highly efficient for a number of known surface reconstructions. We use our method for the sulfur-induced Cu (111) ( 43 × 43 ) surface reconstruction for which we identify a new highly stable structure that conforms with the experimental evidence. [ABSTRACT FROM AUTHOR]

We present a novel formalism to characterize elastic heterogeneities in amorphous solids. In particular, we derive high-order strain-energy expansions for pairwise energies under athermal quasistatic dynamics. We then use the presented formalism to study the statistical properties of pairwise expansion coefficients and their link with the statistics of soft, quasilocalized modes, for a wide range of formation histories in both two- and three-dimensional systems. We further exploit the presented framework to access local yield stress maps by performing a non-linear stress–strain expansion within a cavity embedded in a frozen matrix. We show that our "bond micromechanics" compare well with the original "frozen matrix" method, with the caveat of overestimating large stress activations. We additionally show how local yield rules can be used as an input for a scalar elasto-plastic model (EPM) to predict the stress response of materials ranging from ductile to brittle. Finally, we highlight some of the limits of simple mesoscale models in capturing the aging dynamics of post-yielding systems. Intriguingly, we observe subdiffusive and diffusive shear band growths for particle-based simulations and EPMs, respectively. [ABSTRACT FROM AUTHOR]

We present structural models for three different amyloid fibril polymorphs prepared from amylin20–29 (sequence SNNFGAILSS) and amyloid-β25–35 (Aβ25–35) (sequence GSNKGAIIGLM) peptides. These models are based on the amide C=O bond and Ramachandran ψ-dihedral angle data from Raman spectroscopy, which were used as structural constraints to guide molecular dynamics (MD) simulations. The resulting structural models indicate that the basic structural motif of amylin20–29 and Aβ25–35 fibrils is extended β-strands. Our data indicate that amylin20–29 forms both antiparallel and parallel β-sheet fibril polymorphs, while Aβ25–35 forms a parallel β-sheet fibril structure. Overall, our work lays the foundation for using Raman spectroscopy in conjunction with MD simulations to determine detailed molecular-level structural models of amyloid fibrils in a manner that complements gold-standard techniques, such as solid-state nuclear magnetic resonance and cryogenic electron microscopy. [ABSTRACT FROM AUTHOR]

Purpose: To compare the 3D accuracy of three scanning strategies and conventional impressions using an edentulous model with six implants. Materials and Methods: An edentulous maxillary master model was fabricated with six equigingival internal connection implants at 0 degrees of angulation. Ten conventional open-tray splinted implant-level impressions were made and poured in stone. A master model and conventional casts were digitized with a reference scanner. Digital impressions were made by calibrated clinicians with a TRIOS 3 intraoral scanner ([IOS] 3Shape) according to three scanning strategies: DIG1 (occlusal-palatal-lingual), DIG2 (S-type motion from buccal to palatal), and DIG3 (scanning two half arches and connecting them at the midline). Each technique was repeated 10 times on the master model. Deviations from the STL datasets (N = 40) were compared to those of the reference master model using the Hexagon Metrology software system PC-DMIS CAD++. Linear distortions (dX, dY, dZ), global linear distortion (dR), and angular distortions (Absdθx, Absdθy) were calculated. Kruskal-Wallis test and mixed linear and logistic regression models were used to compare the original and binary distortion measures between the techniques. Results: The mean dR ranged from 91 μm (conventional method) to 183 μm (DIG1). The mean angular distortion ranged from 0.20 degrees (Absdθx for DIG2) to 0.69 degrees (Absdθy for DIG3). No scan pattern resulted in a more accurate reproduction in any of the measured parameters than the conventional impression method. There were significant differences between the methods for all distortion measures. Conclusions: No group reproduced the 3D position of the six-implant master model below the thresholds for both global linear and angular distortions. All the digital strategies tested were less accurate than the conventional open-tray splinted implant-level impression technique. [ABSTRACT FROM AUTHOR]

Physical aging is the process of a system evolving toward a new equilibrium, and thus the response to a change in external parameters such as temperature T, pressure p, or static electric field E. Using a static electric field has been shown to access physical aging above the glass transition temperature Tg, in the regime of milliseconds or faster, but the relation to its temperature jump counterpart has not been investigated to date. This work compares temperature and field induced physical aging in the limit of small perturbations for supercooled tributyl phosphate. It is found that both structural recovery dynamics are very similar, and that they match the collective reorientational dynamics as observed by dielectric relaxation. The results facilitate expanding the range of aging experiments to well above Tg, where a comparison with structural relaxation in equilibrium is straightforward, thus improving models of structural recovery and physical aging. [ABSTRACT FROM AUTHOR]

We describe a new quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) protocol for the prediction and refinement of crystal structures, including its design, benchmarking, and application to seven organic HCl salts. Five HCl salts with a limited number of low-energy conformations were chosen as model systems for benchmarking: betaine HCl, glycine HCl, D -alanine HCl, guanidine HCl, and aminoguanidine HCl; two were chosen for blind tests: N,N′-dimethylglycine HCl and metformin HCl. The QNMRX-CSP protocol uses experimental 35Cl solid-state NMR (SSNMR) spectra and X-ray diffraction (XRD) data in tandem with Monte Carlo simulated annealing and dispersion-corrected plane-wave density functional theory (DFT-D2*) calculations. The protocol comprises three modules: (i) the assignment of motion groups, (ii) a Monte Carlo simulated annealing algorithm for generating tens of thousands of candidate structures, and (iii) DFT-D2* geometry optimizations of structural models and concomitant computation of 35Cl EFG tensors. Key benchmarked metrics are used for retaining the best candidate structures, including unit cell parameters, static lattice energies, and EFG distances (ΓEFG). The protocol is shown to generate structural models that are excellent matches with experimental crystal structures that have been DFT-D2* geometry optimized, as validated by crystallographic R-factors (R) and root-mean squared distances (RMSDs) of atomic positions that are well below 10% and 0.2 Å, respectively. Finally, consideration is given to the use of the QNMRX-CSP protocol as a standalone technique or in concert with other NMRX methods and Rietveld refinements, and possible applications employing other quadrupolar nuclei (i.e., 14N and 17O). [ABSTRACT FROM AUTHOR]

Recently, quantile-based structural equation model has enjoyed increasing popularity in various fields and applications. As we know, structural equation model consists of structural model and measurement model in total. In our quantile-based measurement model, the observed variables are considered to be manifestations of an underlying construct with changing relationships going from the latent variable to its observed variables at different quantiles. Based on our model, we propose a quantile-based partial least square algorithm with bag of little bootstraps. All of our model and algorithm are compared to our quantile-based partial least square algorithms with traditional bootstrap in simulations, and applied to part of IMD (International Institute for Management Development) World Competitiveness Yearbook datasets. [ABSTRACT FROM AUTHOR]

For ellipsoidal fiber-reinforced shells of rotation, the upper (kinematic) limit of load-bearing capacity is determined. The structures are clamped along the lower support contour and have rigid polar plate. The material of the components is rigid-plastic with asymmetry in tension and compression. The matrix is orthotropic. The principal axes of matrix anisotropy coincide with meridional, circumferential and transverse directions. Two-layer shell model and refined relations of structural model with two-dimensional stress state in components are used. Extreme problem is formulated and numerically solved for spherical and two different ellipsoidal shells. Influence of reinforcement parameters on limit load is investigated. [ABSTRACT FROM AUTHOR]

Serviceability issues associated with structural lateral vibration are observed frequently, where human–structure interaction (HSI) plays a crucial role. Inverted pendulum (IP) models have attracted much attention from researchers due to their ability to naturally present human mechanical behaviors and significant advantages in studying the mechanisms of HSI. This paper investigates the behaviors of a 3D bipedal spring-loaded inverted pendulum (BSLIP) model while walking on laterally vibrating surfaces. First, we adopt feedback control strategies for the 3D BSLIP human walking model to achieve stable walking. Then, we investigate phase drift, phase pulling, and synchronization behaviors of the human body using the 3D BSLIP. The results indicate that the equivalent damping and mass coefficients of the 3D BSLIP basically agree with the available experimental results from the literature. Compared to the 3D IP model with rigid legs, the equivalent coefficients obtained from the 3D BSLIP exhibit similar ranges and trends as the control parameter increases. Furthermore, the 3D BSLIP and 3D IP models successfully replicate phase pulling and synchronization phenomena. The synchronization phase angles fall within the range of 102.9∘–228.9∘ for the 3D IP and 209∘–349∘ for the 3,D BSLIP model, consistent with the experimental results reported in the existing literature. [ABSTRACT FROM AUTHOR]

Previous research has found that nature connectedness, an experiential close connection to nature with cognitive, affective and physical benefits, profoundly impacts individual wellbeing and subsequently increases pro-environmental behaviors. However, little is known about the personal and contextual factors that predict nature connectedness. Testing theory derived from a qualitative interpretative phenomenological analysis study, this research addresses the lacuna in the literature. A structural equation model analysis finds that interoceptive awareness significantly predicts nature connection, that secure attachment to nature significantly explains this relationship, and that these inter-related constructs predict both pro-environmental behavior and wellbeing. This revised model of nature connection indicates important antecedents for the human-nature bond, illuminating in particular that the interpersonal relational processes foundational for close bonding with humans also occur in bonding with nature. Structural equation modeling indicates that emotional awareness is the dimension of interoceptive awareness that most significantly predicts nature connection, suggesting that the more aware a person is of the connection between inner bodily sensations and emotions, the more likely they can bond with nature. Given that interoceptive awareness indicates a coherent relationship with the self, including effective communication between body, mind and feelings, this process is therefore implicated in the capacity for humans to bond with nature. In sum, this present research points to the efficacy of an embodied, secure attachment with nature to help close both the human-nature disconnection chasm, and the environmental value-action gap. Theoretical and methodological implications for research and policy are discussed. [ABSTRACT FROM AUTHOR]

In the design process of large adaptive mirrors numerical simulations represent the first step to evaluate the system design compliance in terms of performance, stability and robustness. For the next generation of Extremely Large Telescopes increased system dimensions and bandwidths lead to the need of modeling not only the deformable mirror alone, but also all the system supporting structure or even the full telescope. The capability to perform the simulations with an acceptable amount of time and computational resources is highly dependent on finding appropriate methods to reduce the size of the resulting dynamic models. In this paper we present a framework developed together with the company Microgate to create a reduced order structural model of a large adaptive mirror as a preprocessing step to the control system simulations. The reduced dynamic model is then combined with the remaining system components allowing to simulate the full adaptive mirror in a computationally efficient way. We analyze the feasibility of our reduced models for Microgate's prototype of the adaptive mirror of the Giant Magellan Telescope. [ABSTRACT FROM AUTHOR]

The rapid development of mass entrepreneurship and innovation in China has substantially influenced the entrepreneurial environment, particularly among university students who are emerging as a vital entrepreneurial force. This study aimed to explore and identify the key characteristics and structural framework of entrepreneurial talents among university student entrepreneurs in China, specifically concerning their capacity to discover entrepreneurial opportunities. To achieve this, we conducted interviews with 21 exceptional university student entrepreneurs. A structural model was subsequently developed based on grounded theory, with data coded at three levels and tested for theoretical saturation. The results demonstrated that Chinese university students possess implicit and explicit capacities to detect business possibilities. Implicit abilities largely encompass the innate qualities of entrepreneurial drive and environmental intelligence, while explicit abilities comprise the acquired skills of learning, networking, and integration. This model can be used as a benchmark for assessing and enhancing the capacity of Chinese university students who are aspiring entrepreneurs to identify and exploit entrepreneurial opportunities. [ABSTRACT FROM AUTHOR]

Objective: While most xenograft wound matrices are flat sheets not designed for deep or tunnelling wounds, three-dimensional acellular collagen matrices (3D-ACM) can fill deep wound beds and enable full wound wall apposition. This case series examines the use of 3D-ACM in treating diabetic foot ulcers (DFUs) that are deep, tunnelling, undermining, or irregularly shaped. We report outcomes of cases where 3D-ACM was applied to deep or tunnelling DFUs present for at least four weeks. Method: In this retrospective case series, 3D-ACM was applied, healing was monitored and measurements were collected. Additional 3D-ACM was applied as needed. Results: In total, 11 patients with 13 wounds were treated. Improved wound appearance and reduced size were observed at most follow-ups. Mean initial wound depth was 1.6cm, and several wounds showed significant depth reductions shortly after therapy initiation. In total, 62% of wounds (8/13) reached 50% closure by four weeks. Additionally, 54% (7/13) were fully closed by 12 weeks. The remaining 46% (6/13) took between 12–22.3 weeks to heal. Overall mean therapy time was 13.1 weeks (range: 2.0–22.3 weeks). Deeper wounds generally took longer to close. Conclusion: The findings of this case series showed that 3D-ACM could offer a protective microenvironment for wound management for deep or tunnelling DFUs. While some took >12 weeks to close, this may be attributable to large initial depths and volumes, rather than a failure to respond to the treatment modality. Other wounds that require a conforming 3D matrix, enabling full wound wall apposition, may benefit from 3D-ACM. Further investigations would be beneficial to understand the capabilities of this treatment modality. [ABSTRACT FROM AUTHOR]

Identifying protective factors that promote academic resilience is vital. Nevertheless, due to the variations in the operationalizations of academic resilience, timeframes, data sources, and employed research methods, it remains unclear whether the impact of protective factors identified across studies can be attributed to the factors themselves or to these variations. By addressing these uncertainties, this study aims to provide an overview of the protective factors that have been extensively investigated in academic resilience and their degree of influence. A literature search found 119 empirical studies on protective factors in education settings for children and adolescents. The review analyzed five protective factors groups (individual, family, school, peer, community), three operationalizations of academic resilience (simultaneous, progressive, instrumental), two timeframes (longitudinal, non-longitudinal), three data sources (self-collected, national/local assessments, international large-scale assessments), and commonly employed research methods. The studies analyzed in this review yielded mixed results regarding the impact of the examined protective factors, with measurement instruments and statistical power playing a significant role in explaining the variations. Individual and school-level characteristics emerged as the most well-studied protective factors; individual characteristics were often investigated through "instrumental" operationalization and structural equational models, whereas school-level characteristics were typically explored through "simultaneous" or "progressive" operationalizations and multilevel modeling. Approximately 31 and 16% of the studies utilized national assessments and international large-scale assessment data, respectively. Both data sources promoted the exploration of school-level factors, with the former facilitating the exploration of protective factors across time and the latter contributing to the investigation of teaching-related factors. [ABSTRACT FROM AUTHOR]

Purpose: Health care is advancing toward a collaborative and integrative approach that promotes general health and wellness while addressing health inequities through the consideration of broader social and economic factors that influence the well-being of the entire population. Recently, there has been growing evidence of public health concept applications in fields related to speech, language, and hearing. However, there is an outstanding need to explicitly define the intersection of public health, including prevention and health promotion, and the discipline of communication sciences and disorders (CSD) across the areas of education, clinical practice, research, and policy. The authors propose a definition for this intersection using the new term communication public health. Method: This tutorial provides guidance on how to conceptualize communication public health and invites refinement and expansion of the intersection between public health and CSD. Because readers are experts in CSD, this tutorial aims to supplement existing knowledge with information on public health to achieve three main objectives: (a) increase knowledge of the application of public health concepts among speech, language, hearing, and related professionals (SLHP+); (b) introduce the concept of communication public health; and (c) discuss the relevance of communication public health across domains within CSD. The authors utilize the socioecological model to provide examples of applications. Results: The concept of communication public health is proposed as the collaborative area of CSD and public health, which encompasses prevention and promotion of equity in communication health through individual-, community-, and population-level efforts. The goals of communication public health are achieved through applications of public health principles in CSD education, clinical practice, research, and policy. Conclusion: Communication public health defines an area of collaboration between public health and CSD in which SLHP+ can apply public health concepts to both advance communication health and address health disparities. [ABSTRACT FROM AUTHOR]

Bonding effects among non-contacting particles are key phenomena that drive the mechanical behavior and fracture process of structural loess. The existing discontinuous deformation analysis (DDA) methods are incapable of taking into account these microstructural interactions. This work presents a modified DDA method considering the bonding effect to analyze the role of bonds in structural loess at the microscale. Spring elements are used to calculate the bonding forces acting on the particle surface covered by bond materials. The proposed modified DDA method is validated through three benchmark tests: the bending of a cantilever beam, the Brazilian disc test and the compression of rods bonded by epoxy. The results show that the numerical solution agrees well with analytical and experimental data. Microstructure models of a structural loess sample with different contents of bond material are also studied and compression tests are simulated using these models. The results indicate that the content of bond material significantly influences the evolution pattern of the pore structure, which determines the deformation behavior of loess. In addition, structural yield stress and pore stability of loess increase with increasing bond content. It is also shown that the modified DDA method can capture the main pore deformation behaviors in real loess during compression. Finally, the study reveals that the bonding effect is crucial for maintaining the stability of the microstructure of loess. [ABSTRACT FROM AUTHOR]

For the research on real-time accurate testing technology for the explosion point spatial coordinate of munitions, its currently commonly used methods such as acoustic–electric detection or high-speed imaging are limited by the field conditions, response rate, cost, and other factors. In this paper, a method of spatial coordinate testing for the explosion point based on a 2D PSD (position-sensitive detector) intersection is proposed, which has the advantages of a faster response, better real-time performance, and a lower cost. Firstly, a mathematical model of the spatial coordinate testing system was constructed, and an error propagation model for structural parameters was developed. The influence of the position of the optical axes' intersection as well as the azimuth angle and pitch angle on the test accuracy of the system was simulated and analyzed, thus obtaining the distribution and variation trend of the overall error propagation coefficient of the system. Finally, experiments were designed to obtain the test error of the system for validation. The results show that the system test accuracy is high when the azimuth angle is 20°–50°, the overall error propagation coefficient does not exceed 48.80, and the average test error is 56.17 mm. When the pitch angle is −2.5°–2.5°, the system has a higher test accuracy, with the overall error propagation coefficient not exceeding 44.82, and the average test error is 41.87 mm. The test accuracy of the system is higher when the position of the optical axes' intersection is chosen to make sure that explosion points fall in the region of the negative half-axis of the Z w -axis of the world coordinate system, with an overall error propagation coefficient of less than 44.78 and an average test error of 73.38 mm. It is shown that a reasonable selection of system structure parameters can significantly improve the system test accuracy and optimize the system deployment mode under the long-distance field conditions so as to improve the deployment efficiency. [ABSTRACT FROM AUTHOR]

Precise forecasts of carbon prices are crucial for reducing greenhouse gas emissions and promoting sustainable, low-carbon development. To mitigate noise interference in carbon price data, hybrid models integrating data decomposition techniques are commonly utilized. However, it has been observed that the improper utilization of data decomposition techniques can lead to data leakage, thereby invalidating the model's practical applicability. This study introduces a leakage-free hybrid model for carbon price forecasting based on the sliding window empirical wavelet transform (SWEWT) algorithm and the gated recurrent unit (GRU) network. First, the carbon price data are sampled using a sliding window approach and then decomposed into more stable and regular subcomponents through the EWT algorithm. By exclusively employing the data from the end of the window as input, the proposed method can effectively mitigate the risk of data leakage. Subsequently, the input data are passed into a multi-layer GRU model to extract patterns and features from the carbon price data. Finally, the optimized hybrid model is obtained by iteratively optimizing the hyperparameters of the model using the tree-structured Parzen estimator (TPE) algorithm, and the final prediction results are generated by the model. When used to forecast the closing price of the Guangdong Carbon Emission Allowance (GDEA) for the last nine years, the proposed hybrid model achieves outstanding performance with an R2 value of 0.969, significantly outperforming other structural variants. Furthermore, comparative experiments from various perspectives have validated the model's structural rationality, practical applicability, and generalization capability, confirming that the proposed framework is a reliable choice for carbon price forecasting. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) enables the acquisition of high-resolution imagery even under severe meteorological and illumination conditions. Its utility is evident across a spectrum of applications, particularly in automatic target recognition (ATR). Since SAR samples are often scarce in practical ATR applications, there is an urgent need to develop sample-efficient augmentation techniques to augment the SAR images. However, most of the existing generative approaches require an excessive amount of training samples for effective modeling of the SAR imaging characteristics. Additionally, they show limitations in augmenting the interesting target samples while maintaining image recognizability. In this study, we introduce an innovative single-sample image generation approach tailored to SAR data augmentation. To closely approximate the target distribution across both the spatial layout and local texture, a multi-level Generative Adversarial Network (GAN) architecture is constructed. It comprises three distinct GANs that independently model the structural, semantic, and texture patterns. Furthermore, we introduce multiple constraints including prior-regularized noise sampling and perceptual loss optimization to enhance the fidelity and stability of the generation process. Comparative evaluations against the state-of-the-art generative methods demonstrate the superior performance of the proposed method in terms of generation diversity, recognizability, and stability. In particular, its advantages over the baseline method are up to 0.2 and 0.22 in the SIFID and SSIM, respectively. It also exhibits stronger robustness in the generation of images across varying spatial sizes. [ABSTRACT FROM AUTHOR]

Aims: The cerebellum is involved in higher‐order mental processing as well as sensorimotor functions. Although structural abnormalities in the cerebellum have been demonstrated in schizophrenia, neuroimaging techniques are not yet applicable to identify them given the lack of biomarkers. We aimed to develop a robust diagnostic model for schizophrenia using radiomic features from T1‐weighted magnetic resonance imaging (T1‐MRI) of the cerebellum. Methods: A total of 336 participants (174 schizophrenia; 162 healthy controls [HCs]) were allocated to training (122 schizophrenia; 115 HCs) and test (52 schizophrenia; 47 HCs) cohorts. We obtained 2568 radiomic features from T1‐MRI of the cerebellar subregions. After feature selection, a light gradient boosting machine classifier was trained. The discrimination and calibration of the model were evaluated. SHapley Additive exPlanations (SHAP) was applied to determine model interpretability. Results: We identified 17 radiomic features to differentiate participants with schizophrenia from HCs. In the test cohort, the radiomics model had an area under the curve, accuracy, sensitivity, and specificity of 0.89 (95% confidence interval: 0.82–0.95), 78.8%, 88.5%, and 75.4%, respectively. The model explanation by SHAP suggested that the second‐order size zone non‐uniformity feature from the right lobule IX and first‐order energy feature from the right lobules V and VI were highly associated with the risk of schizophrenia. Conclusion: The radiomics model focused on the cerebellum demonstrates robustness in diagnosing schizophrenia. Our results suggest that microcircuit disruption in the posterior cerebellum is a disease‐defining feature of schizophrenia, and radiomics modeling has potential for supporting biomarker‐based decision‐making in clinical practice. [ABSTRACT FROM AUTHOR]

Subsea systems for oil exploitation and renewable offshore energy generally employ cables, hoses, risers, umbilical and power energy cables, mooring lines, among other slender components. From the global modeling perspective, all such "lines" can be well represented by classes of structural models according to phenomena of interest for each analysis—eg.: bending/torsion and/or tension/compression loads. In this context, one is frequently interested in static and dynamic effects. Moreover, geometric nonlinearities, hydrodynamic loads and contact with the seabed can play an important role. The present work proposes a general and robust numerical methodology able to establish and analyze complete offshore systems, composed of numerous lines attached to a floating unit. Catenary, lazy-wave, vertical, or other geometric configurations can be considered for each line. The initial guess for the system configuration is produced by a set of analytical solutions, considering a multi-segment extensible catenary formulation. This is implemented into an in-house numerical finite element framework, which models and solves the statics and dynamics of the system. We employ geometrically exact beam and truss models, handling all external loads of interest and contact interactions with the seabed. Case studies following the proposed methodology are exemplified, discussing details on modeling aspects, such as comparing results with other tools/methodologies. [ABSTRACT FROM AUTHOR]

The different approximating assumptions used in deriving models for structural analysis by dimensional reduction of a 3d continuum to structural components like beams and plates or shells limit the applicability of these models by geometrical constraints. Hence, caution should be exercised when transitioning from the application range of one type of structure model to another one. This should be taken into account especially when stability analyses are performed. In order to demonstrate this, in this note, buckling of annular plates under tensile loading at the inner edge is treated as an example. The ratio between inner and outer radius is varied. For ratios approaching 1.0, plate buckling turns into buckling of circular beams. This is not only a question of accuracy of the solution but can lead to a substantial qualitative change of the character of buckling. Such considerations might be interesting from a theoretical point of view; in any case they are important from the engineering point of view. [ABSTRACT FROM AUTHOR]

This study tested the structural influence model of communication in the context of the 2022 global outbreak of the Mpox virus among young sexual minority men. The primary objective was to understand how distinct social determinants, including education, race/ethnicity, and interpersonal discrimination, influenced exposure to Mpox messages in daily life and affected health anxiety concerning the Mpox virus in the United States. We also explored the significance of LGBTQ+ community connectedness as a crucial form of social capital during the outbreak. We collected a three-wave longitudinal dataset and examined within-person and between-person associations using a random-intercept cross-lagged panel model. Participants (N = 254) reported that internet sources and social media were their primary information sources for Mpox messages during the outbreak. Educational attainment, racial minority status, and LGBTQ+ community connectedness were significantly associated with message exposure. Young sexual minority men who faced greater interpersonal discrimination in their daily lives also reported higher rates of Mpox-related health anxiety. Longitudinal analysis indicated that (at the within-person level) Mpox anxiety was significantly associated with greater Mpox message exposure in the month following the outbreak, but that relationship waned in the subsequent month. The theoretical implications highlight the relevance of minority stress variables in the structural influence model of communication framework and suggest the importance of community connectedness as a distinct form of social capital shaping message exposure and health anxiety during the Mpox outbreak in the United States. [ABSTRACT FROM AUTHOR]

Cilia are slender, micrometer‐long organelles present on the surface of eukaryotic cells. They function in signaling and locomotion and are constructed by intraflagellar transport (IFT). The assembly of IFT complexes into so‐called IFT trains to initiate ciliary entry at the base of the cilium remains a matter of debate. Here, we use structural modeling to provide an architectural framework for how RabL2 is anchored at the ciliary base via CEP19 before being handed over to IFT trains for ciliary entry. Our models suggest that the N‐terminal domain of CEP43 forms a homo‐dimer to anchor at the subdistal appendages of cilia through a direct interaction with CEP350. A long linker region separates the N‐terminal domain of CEP43 from the C‐terminal domain, which captures CEP19 above the subdistal appendages and close to the distal appendages. Furthermore, we present a structural model for how RabL2‐CEP19 associates with the IFT‐B complex, providing insight into how RabL2 is handed over from CEP19 to the IFT complex. Interestingly, RabL2 association with the IFT‐B complex appears to induce a significant conformational change in the IFT complex via a kink in the coiled‐coils of the IFT81/74 proteins, which may prime the IFT machinery for entry into cilia. [ABSTRACT FROM AUTHOR]

Help seeking has traditionally been studied in face‐to‐face settings using self‐report instruments measuring learners' internal inclinations for help seeking (eg, perceived benefits and threats). Much less is known about help seeking in online learning. Furthermore, external environmental factors such as a positive climate were found to encourage help seeking. Utilizing peer‐help analytics as well as self‐report measures, this study simultaneously modelled the structural relationships among students' perceived class climate, internal help‐seeking inclinations, help‐seeking engagement, participation in peer help and performance in an online class. Results from structural equation modelling indicated that students' perceived goal structure of an online class had a significant influence on their internal help‐seeking inclinations, which subsequently affected their help‐seeking engagement, participation in peer help and learning outcomes. Instructors of online classes should pay particular attention to fostering a mastery‐oriented climate in order to encourage help seeking and improve academic performance. Practitioner notesWhat is already known about this topic Help seeking is important for academic success.Due to a variety of individual and contextual factors, students often do not seek help despite the need.Existing research on help seeking focuses on the face‐to‐face setting and relies on self‐report measures.Students' help‐seeking inclinations and patterns may differ between in‐person classes and the online environment.What this paper adds This study examined help seeking in an online class through self‐report measures and objective analytics data.This study modelled the structural relationships among the external climate of an online class, students' internal help‐seeking inclinations, engagement in help seeking, participation in peer help and course performance.Structural equation modelling found that the goal structure of an online class influenced students' internal help‐seeking inclinations.Online students' internal help‐seeking inclinations affected their grades through their participation in help seeking.Implications for practice and/or policy A mastery‐oriented class climate elicits online learners' positive help‐seeking inclinations while discouraging negative ones.The design and teaching of online classes should aim to foster a mastery‐oriented climate.Online classes should offer peer‐help opportunities and encourage student participation, which is conducive to academic performance. [ABSTRACT FROM AUTHOR]

Objective: Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test a magnetic resonance imaging (MRI)‐based joint space (JS) radiomic model (RM) to predict radiographic KOA incidence through neural networks by integrating meniscus and femorotibial cartilage radiomic features. Methods: In the Osteoarthritis Initiative cohort, participants with knees without radiographic KOA at baseline but at high risk for radiographic KOA were included. Patients' knees developed radiographic KOA, whereas control knees did not over four years. We randomly split the participants into development and test cohorts (8:2) and extracted features from baseline three‐dimensional double‐echo steady‐state sequence MRI. Model performance was evaluated using an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity in both cohorts. Nine resident surgeons performed the reader experiment without/with the JS‐RM aid. Results: Our study included 549 knees in the development cohort (275 knees of patients with KOA vs 274 knees of controls) and 137 knees in the test cohort (68 knees of patients with KOA vs 69 knees of controls). In the test cohort, JS‐RM had a favorable accuracy for predicting the radiographic KOA incidence with an AUC of 0.931 (95% confidence interval [CI] 0.876–0.963), a sensitivity of 84.4% (95% CI 83.9%–84.9%), and a specificity of 85.6% (95% CI 85.2%–86.0%). The mean specificity and sensitivity of resident surgeons through MRI reading in predicting radiographic KOA incidence were increased from 0.474 (95% CI 0.333–0.614) and 0.586 (95% CI 0.429–0.743) without the assistance of JS‐RM to 0.874 (95% CI 0.847–0.901) and 0.812 (95% CI 0.742–0.881) with JS‐RM assistance, respectively (P < 0.001). Conclusion: JS‐RM integrating the features of the meniscus and cartilage showed improved predictive values in radiographic KOA incidence. [ABSTRACT FROM AUTHOR]

High-strength steel has been extensively used in numerous structures or high-rise buildings because of its high strength, ductility, and weldability. However, high-strength steel structures are vulnerable to fire hazards, so the ability to predict structural behavior is crucial in structural fire safety design. Creep behavior is one of the primary factors influencing the response of steel at high temperatures. This paper presents numerical studies using the fire dynamics simulator (FDS) and finite element method (FEM) coupling models to predict the structural behavior of a protected beam with a cavity for H-SA700 high-strength steel at elevated temperatures, including the creep effect. A comparison between simulation and experiment results demonstrates the validity of the process. In detail, based on a set of tensile tests conducted at six constant temperatures between 23°C and 600°C, the creep model is proposed. Subsequently, because creep is temperature-dependent, the heat transfer model used to predict the temperature distribution of the steel is developed. The effect of the partially damaged protection cover is discussed. Finally, it is found that with the temperature distribution from FDS-FEM integration and the proposed creep models, the collapse time of the beam can be defined. This study provides a practical approach for developing the creep model without creep tests and applying it to complex structures during fires. [ABSTRACT FROM AUTHOR]

Although researchers have devoted great effort to explore the antecedents of altruistic behaviours (a type of organisational citizenship behaviours), the important role of technical factors (social media) remains unclear. Drawing on social comparison and organisational support theory, this study explored how social media affordances influence employees' altruistic behaviours from both positive and negative perspectives. In this study, 302 employees from organisations in China were surveyed. We found that social media affordances could facilitate employees' perceived organisational support and social comparison of ability. Perceived organisational support positively mediated the relationship between social media affordances and altruistic behaviours. Although the evidence did not support the notion that social comparison of ability could directly dampen altruistic behaviours, a post-hoc analysis found that it could dampen the positive impact of perceived organisational support on developing altruistic behaviours. This study expanded previous research focusing on only positive or negative effects of social media use in the workplace by investigating the dual effects and the interaction effect in between. Here, we discuss the results and provide practical guidance for managers and organisations. [ABSTRACT FROM AUTHOR]

Live streaming shopping (LSS) has become a means of increasing sales and has become a crucial research topic. Drawing on uncertainty reduction theory, parasocial relationship theory, and social influence theory, this study develops a research model to investigate the factors affecting LSS viewers' continued watching and purchase intentions. The results indicate that the real-time multiparty interactivity of LSS offers information from two sources that can satisfy the long-term viewers' needs for information. The first is the viewer's perceived affinity with the streamer based on the information shared by the streamer. These perceptions lead to the development of a parasocial relationship, promoting identification with the streamer. The second is the shared communication network (SCN) comprising the audience watching the LSS content. This SCN generates social influence; coviewers' endorsements and trustworthiness are internalised and influence the perceived credibility of the streamer and can promote identification with the streamer. Parasocial relationships, credibility, and identification with the streamer increase viewers' intention to continue to watch LSS content and to purchase the products sold by the streamer. This study contributes to the LSS literature by investigating the influence of viewer–viewer interactions and highlighting the importance of the SCN in maintaining streamer–viewer relationships. [ABSTRACT FROM AUTHOR]

In this paper, we use a previously developed measles model to forecast measles in Turkey for the period 1970–2021. We study the structural identifiability of the model both by hand and using software. By hand, we assume the prevalence and the total population size are given. Using software, we assume the incidence and the total population size are given. The model is structurally identifiable if one of the three parameters is fixed. We notice that Turkey has a significant change in time of the immigration rate and vaccination proportions, so we assume these two quantities are time-dependent. We fit the nonautonomous model to the measles incidences in Turkey for 1970–2021. We perform practical identifiability of the fitted model, and find that all parameters but one are practically identifiable. When fixing the unidentifiable parameter to a value derived from additional data, we obtain that all parameters are practically identifiable. [ABSTRACT FROM AUTHOR]

Obicetrapib is a selective inhibitor of cholesteryl ester transfer protein that is currently in phase 3 of development for the treatment of dyslipidemia as adjunct therapy. The purpose of this study was to comprehensively characterize the pharmacokinetic (PK) and pharmacodynamic (PD) disposition of obicetrapib. Data from 7 clinical trials conducted in healthy adults and those with varying degrees of dyslipidemia were included for model development. The structural model that best described obicetrapib PK was a 3‐compartment model with 4‐compartment transit absorption and first‐order elimination. Body weight was the only covariate found to significantly explain observed variability and was therefore included using allometric scaling on all disposition parameters. For a typical patient weighing 75 kg, the estimated apparent total body clearance and apparent volume of distribution of the central compartment was 0.81 L/h and 36.1 L, respectively. The final PK model parameters were estimated with good precision and were ultimately leveraged to sequentially inform 2 turnover models that describe obicetrapib's effect on low‐density lipoprotein cholesterol (LDL‐C) and high‐density lipoprotein cholesterol (HDL‐C) concentrations. The maximum stimulatory effect of obicetrapib on LDL‐C loss was estimated to be 1.046, while the maximum inhibitory effect of obicetrapib on HDL‐C loss was 0.691. This corresponds to a predicted typical maximum percent change from baseline LDL‐C and HDL‐C of 51.1% and 224%, respectively. The final sequential model described obicetrapib PKPD well and was ultimately able to both demonstrate evidence of internal consistency and support decision‐making throughout the development lifecycle. [ABSTRACT FROM AUTHOR]

It is critical that clinical social workers become actively aware of the endemic processes and manifestations of racism, social inequities, structures and dynamics of white supremacy within and across organizational, supervisory and clinical relationships. The Structural-Clinical Model (SCM) is presented, providing a multi-layered and theoretically rich pathway for clinical social workers to examine the intricate, and multifaceted interconnections expressing racialized oppressive forces across macro, meso and micro systems that impact the totality of clinical practice. SCM integrates critical race theory, liberation psychology, and relational theories bridging long standing theoretical and conceptual divides. The SCM aims to de-pathologize clients, recognizing instead the pathology of white supremacy, racism, and other oppressive structural forces affecting organizations, relationships and people's lives, particularly those most racially, ethnically and historically marginalized within our society. The SCM is introduced with a structural assessment framework designed to explore how structural social inequalities produced by white supremacy impact social work organizations, the clinical supervisory relationship and the supervisor-therapist-client relationship. A multilevel case example is provided to demonstrate how structural power dynamics that influence service delivery can be identified through critical dialogue using the SCM in the clinical supervisory relationship and between the clinical social worker and client. [ABSTRACT FROM AUTHOR]

This work provides new insights into the nature of the polaronic transport in xV2O5–(100−x)P2O5, 41 ≤ x ≤ 89 mol% glasses from analysis of their conductivity over a wide range of frequencies and temperatures, and correlation of the electrical parameters to the structural models of these materials. The results show that the linear increase in direct current (DC) conductivity with the increase in V2O5 could be related to the formation of a vanadate subnetwork, which is characterized by a length distribution of V–O bonds and variations in linkages between different vanadate units. Such a structurally complex network offers multiple conduction pathways which are favorable for polaron hopping. The Summerfield scaling of conductivity spectra reveals a temperature‐invariant mechanism of polaron transport for all glasses and the same local structural environment of polarons at higher V2O5 contents due to the same ratio of vanadate units present in the network. Also, this study highlights the similarities and differences in the nature of the polaronic transport of vanadate–phosphate glasses and other polaronically conducting phosphate glasses containing WO3, MoO3, and Fe2O3, and pins down a pivotal role of the glass structure in electrical processes in these materials. [ABSTRACT FROM AUTHOR]

Developing constitutive models that can be used to model composite structural systems subjected to impact loads where modeling damage, failure, and delamination are critical is a challenging task. Often processing experimental data to develop the composite material model and, especially, the delamination model can be tedious, subjective, and error prone. In this paper, procedures for characterizing the behavior of laminated unidirectional composites (UDCs) are explained. First, laboratory tests are conducted to obtain the orthotropic material properties of a commonly used composite, IM7-8552. The obtained data are used in the MAT_213 model in LS-DYNA. Second, fracture-related tests, i.e., double-cantilever beam (DCB) and end-notched flexure (ENF) tests, are conducted to obtain the load-displacement responses. Finally, an inverse analysis approach is used by combining response surface methodology (RSM) and gradient-based numerical optimization to find the optimal values of the traction-separation law (TSL) parameters to build the constitutive model for modeling delamination. The developed cohesive zone element (CZE) model is then validated using the experimental results of a quasi-isotropic tension test. It is shown that the overall process of analyzing the experimental data and building a finite-element model is simpler, and the results from the validation test indicate that the developed methodology can yield accurate predictions. [ABSTRACT FROM AUTHOR]

The use of experimental data is a relevant topic in aeroelasticity. A new aircraft prototype design and certification involve both flutter analysis and tests. The latter is essential to assess a proper finite element (FE) model for the aeroelastic analysis. The current work perfectly fits in this framework, presenting a novel methodology exploiting data from ground vibration testing (GVT) for flutter calculations. The first application relies on the only experimental modal parameters employed to perform aerodynamic flutter calculation. This method does not necessitate a consistent structural model, allowing fast and reliable computation of the flutter clearance just based on GVT results. This application is especially valuable when it is not possible for a structural dynamic model development, e.g., in the absence of a sufficient amount of technical data. The method also allows combinations of experimental and numerical mode shapes to perform flutter calculations. All or some modal parameters can be incorporated in the standard numerical flutter model, adjusting the computed numerical modes, or adding/deleting a few. The method allows a real true correlation between the GVT results and the numerical model, which is usually very difficult to obtain. This work represents the first case based on a combination of experimental and numerical results, paving the way to various possible levels of hybridization to perform aeroelastic analyses. [ABSTRACT FROM AUTHOR]

Functionally graded materials with porosity have received increased application in satellites, space vehicles, aircraft, and other transportation systems. The multi-physics coupled modeling technique for structural response analysis remains a big challenge. This paper develops a finite element formulation based on the first-order shear deformation (FOSD) hypothesis for evaluation of the static and dynamic behavior of functionally graded magneto-electro-elastic porous (FG-MEEP) cylindrical shells under thermal loads. Four types of thermal loads such as uniform, linear, sinusoidal, and heat conduction temperature rise are included in the FE model. Furthermore, FG-U, FG-V, FG-O, and FG-X distributions of porosity is considered. The material parameters of FG-MEEP are obtained by modified power law. Two forms of material gradation in the framework of 'B'-rich bottom and 'F'-rich bottom are used. The correctness of the present model is verified by comparing with the results of literature. Finally, parametric studies are adopted to analyze the static and dynamic response of FG-MEEP cylindrical shell by varying functionally graded pattern, gradient index, porosity volume, temperature, porosity distribution, etc. These numerical results can serve as benchmarks for the future study of porous structures in thermal environment. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impacts of climate extremes on the production and trade of apples. Apple production being notoriously sensitive to climate shocks, we show that March and April temperatures and precipitations beyond estimated thresholds cause large yield reductions in Quebec and Ontario. In years when climate shocks are large and highly correlated across space, large variations in national production cause major variations in trade flows. Hence, we exploit the theoretical foundations of a sectoral structural gravity model to implement counterfactual trade experiments about harvest shocks in Canada and the United States. We report changes in tariffs, imports, exports, farmgate prices, and in consumer welfare. The shocks greatly impact trade between North American countries but have little impact on other countries except for Chile and New Zealand which see their exports grow. [ABSTRACT FROM AUTHOR]

This review focuses on the synthetic inorganic chemistry of structural and functional models of Mo-Cu CO dehydrogenase (CODH). Mo-Cu CODH is an aerobic enzyme that catalyzes CO oxidation. The active site of Mo-Cu CODH demonstrates a structural motif unprecedented in inorganic chemistry: dithiolene-ligated MoVIO2S linked to a two-coordinate Cu(I) through a single bridging sulfido, {MoVIO2(μ2-S)CuI}. There is significant interest in understanding how this unusual active site structure enables reactivity. Structural analogues of varying accuracy have been reported by several research groups and are discussed in this review. Most of the modeling chemistry indicates that the single sulfido-bridged MoVI-(μ2-S)-CuI structure is unstable when the metals are coordinatively unsaturated, generally collapsing into the stable MoVI-(μ2-S)2-CuI or MoVI-(μ2-S)(μ2-O)-CuI diamond cores outside of the protein environments. Whereas singly bridged {MoVIO2(μ2-S)CuI} oxidizes CO and inserts CNR (isocyanide) efficiently, no biomimetic CODH-relevant reactivity was observed for the synthetic analogues containing the aforementioned diamond cores. An alternative synthetic approach pursuing a "bioinspired" functional model is also discussed. In this approach, two relevant metal sites (hypothesized to be primarily responsible for the reactivity) are combined into a heterobimetallic complex using appropriate heterodinucleating ligands. Syntheses, structures, and cooperative bimetallic reactivity of these heterobimetallic complexes will be discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mg is an efficient alternative element of Co for high performance LiNi 0.95 M 0.05 O 2 cathodes. • Pair distribution function and reverse Monte Carlo modelling are used to reveal the local structure of Ni-rich cathodes. • Jahn-Teller distortion promoted by the size effects and coulomb interactions of foreign ions in M 3b O 2 layer deteriorates the electrochemical performances of Ni-rich cathodes. • The ordered lattice host framework (M 3b O 2) and active guest Li+ improve the cycle stability and rate capability of Ni-rich cathodes. Recently, due to high price, resource shortage and unstable supply of cobalt, the development of low-cost cobalt-free Ni-rich cathodes has attracted extensive attention with the ever-increasing lithium-ion batteries (LIBs) industry. Selecting cost-effective elements to replace cobalt in Ni-rich cathodes is urgent. However, the principle of structural design of Ni-rich cathode remains unclear, hampering the selection of alternative elements. Herein, the cobalt-free cathodes of LiNi 0.95 Mg 0.05 O 2 (NiMg) and LiNi 0.95 Mn 0.05 O 2 (NiMn) are designed as alternatives to LiNi 0.96 Co 0.04 O 2 (NiCo). NiMg has comparable cycle stability with NiCo, while NiMn has inferior cycle performance. Reverse Monte Carlo modelling was used to generate structural model and uncover local structure by fitting pair distribution function. It reveals Mn causes more severe Jahn-Teller distortions and disordered lattice host framework (Ni 0.95 M 0.05 O 2 , M = Co/Mn/Mg) than Co and Mg due to the strong size effect and coulomb interactions of Mn in Ni 0.95 Mn 0.05 O 2 layer. The outstanding cycle stability of NiMg and NiCo originates from the ordered lattice host frameworks, which relieve stress and inhibit particle breakage during cycle. Meanwhile, the ordered lattice host framework induced guest Li+ disordering reduces Li+ diffusion energy barrier, improving the rate capability. This study provides a new perspective for the structural design of cobalt-free Ni-rich cathodes. [ABSTRACT FROM AUTHOR]

Certolizumab pegol (CZP; CIMZIA™) is the only Fc‐free tumor necrosis factor inhibitor with data from a clinical study demonstrating no to minimal placental transfer. The pharmacokinetics (PK) of certolizumab pegol during pregnancy and postpartum in women with chronic inflammatory diseases were assessed using a population PK model based on data from the CHERISH study (NCT04163016), a longitudinal, prospective, open‐label PK phase IB study. Model development was performed in NONMEM using a frequentist prior approach, with prior information based on a population PK model for certolizumab pegol in non‐pregnant adult patients (NCT04740814). A one‐compartment model with first‐order absorption (Ka = 0.236 1/day) and linear elimination (CL/F = 0.416 L/day) from the central compartment (V/F = 7.86 L) best described certolizumab pegol PK in the CHERISH study. The structural model parameters were estimated with good precision (RSE < 25%). Baseline BW was included as a covariate on CL/F and V/F. Pregnancy trimester and time‐varying log‐transformed anti‐drug antibody (ADA) titer were identified as the only significant covariates for CL/F with a comparable influence on CL/F. Individuals with higher ADA titer (75th percentile) during pregnancy exhibited CL/F up to 1.43‐fold higher relative to individuals postpartum that showed median levels of ADA titer. However, the confidence interval for the combined effect of pregnancy stage and ADA titer effects on CL/F overlapped with the CL/F range of the typical individual postpartum. In addition, simulations showed a large overlap in certolizumab pegol concentrations between pregnant and non‐pregnant adults. The findings of this population PK analysis support the maintenance of established certolizumab pegol dosing regimens throughout pregnancy. [ABSTRACT FROM AUTHOR]

Prenatal tobacco exposure (PTE) and tobacco–cannabis coexposure (PTCE) co-occur with negative maternal emotional functioning (termed prenatal risks) and together increase risk for child regulatory problems at early school age (ESA). Little is known about developmental processes in early childhood that may mediate this association. We examined two hypothesized mediational processes linking prenatal risks to ESA emotion regulation (ER) and lability–negativity; parasympathetic functioning at toddler age and chronic risk reflected by continued postnatal maternal negative emotional functioning (i.e., depression, anger/hostility, and emotion dysregulation) and substance exposure. Congruent with differential susceptibility theory, we examined interactions between sensitive parenting and toddler parasympathetic functioning predicting ESA ER. Finally, we explored the role of child sex as a moderator. Mothers (N = 247; 53% male infants; 51% Black, 31% White, 19% Hispanic, and 8% other or mixed race) were recruited in the first trimester of pregnancy into one of three groups: PTE (n = 81), PTCE (n = 97), and no substance exposure (n = 69) matched on age and education. Substance exposure was assessed using multiple methods, maternal negative emotional functioning via self-reports, parenting with observations, and child ER using teacher, maternal, and lab assessor reports. Results supported a chronic risk pathway with less support for a parasympathetic pathway. Toddlers who demonstrated respiratory sinus arrhythmia withdrawal to frustration were susceptible to the positive context of sensitive parenting in predicting higher ER. Results emphasize the importance of chronicity of postnatal risks including substance exposure and evaluating the differential impact of positive environments for children with substance exposure. Public Significance Statement: Prenatal coexposure to cannabis and tobacco is increasingly common and is associated with poorer emotion regulation at early school age. The current study evaluated a chronic postnatal risk pathway and a parasympathetic nervous system pathway from prenatal coexposure and associated risks to school age emotion regulation. Results provided support for chronic postnatal maternal mood and substance exposure risk pathways and for interactions between parasympathetic nervous system functioning and sensitive caregiving in associations with school age emotion regulation. [ABSTRACT FROM AUTHOR]

Structural design synthesis considering discrete elements can be formulated as a sequential decision process solved using deep reinforcement learning, as shown in prior work. By modeling structural design synthesis as a Markov decision process (MDP), the states correspond to specific structural designs, the discrete actions correspond to specific design alterations, and the rewards are related to the improvement in the altered design's performance with respect to the design objective and specified constraints. Here, the MDP action definition is extended by integrating parametric design grammars that further enable the design agent to not only alter a given structural design's topology, but also its element parameters. In considering topological and parametric actions, both the dimensionality of the state and action space and the diversity of the action types available to the agent in each state significantly increase, making the overall MDP learning task more challenging. Hence, this paper also addresses discrete design synthesis problems with large state and action spaces by significantly extending the network architecture. Specifically, a hierarchical-inspired deep neural network architecture is developed to allow the agent to learn the type of action, topological or parametric, to apply, thus reducing the complexity of possible action choices in a given state. This extended framework is applied to the design synthesis of planar structures considering both discrete elements and cross-sectional areas, and it is observed to adeptly learn policies that synthesize high performing design solutions. [ABSTRACT FROM AUTHOR]

Background and Aims Lidar is a promising tool for fast and accurate measurements of trees. There are several approaches to estimate above-ground woody biomass using lidar point clouds. One of the most widely used methods involves fitting geometric primitives (e.g. cylinders) to the point cloud, thereby reconstructing both the geometry and topology of the tree. However, current algorithms are not suited for accurate estimation of the volume of finer branches, because of the unreliable point dispersions from, for example, beam footprint compared to the structure diameter. Method We propose a new method that couples point cloud-based skeletonization and multi-linear statistical modelling based on structural data to make a model (structural model) that accurately estimates the above-ground woody biomass of trees from high-quality lidar point clouds, including finer branches. The structural model was tested at segment, axis and branch level, and compared to a cylinder fitting algorithm and to the pipe model theory. Key Results The model accurately predicted the biomass with 1.6 % normalized root mean square error (nRMSE) at the segment scale from a k -fold cross-validation. It also gave satisfactory results when scaled up to the branch level with a significantly lower error (13 % nRMSE) and bias (−5 %) compared to conventional cylinder fitting to the point cloud (nRMSE: 92 %, bias: 82 %), or using the pipe model theory (nRMSE: 31 %, bias: −27 %). The model was then applied to the whole-tree scale and showed that the sampled trees had more than 1.7 km of structures on average and that 96 % of that length was coming from the twigs (i.e. <5 cm diameter). Our results showed that neglecting twigs can lead to a significant underestimation of tree above-ground woody biomass (−21 %). Conclusions The structural model approach is an effective method that allows a more accurate estimation of the volumes of smaller branches from lidar point clouds. This method is versatile but requires manual measurements on branches for calibration. Nevertheless, once the model is calibrated, it can provide unbiased and large-scale estimations of tree structure volumes, making it an excellent choice for accurate 3D reconstruction of trees and estimating standing biomass. [ABSTRACT FROM AUTHOR]