Component Model Research Articles

Designing 3D-printed concrete structures with scaled fabrication models

This article proposes using scaled fabrication models to assist the design research of 3D-printed discrete concrete structures where full-scale fabrication tests are costly and time-consuming. A scaled fabrication model (SFM) is a scaled model 3D-printed the same way as in actual construction to reflect its fabrication details and acquire alike layer line textures. The components of a 1:10 SFM can be eas- ily produced by consumer-level desktop 3D printers with minimal modification. SFMs assist the design communication and make possible quick tests of dis- tinct fabrication designs that are hard to assess in digital modeling [Response to 1.1] during the conceptual design phase. A case study of a discrete compression- dominant funicular floor derived from graphic statics is presented to illustrate the contribution of SFM to the design research of force-informed toolpathing where the printing direction of a component is aligned to the principal stress line. The design iterations encompass a sequence of component, partial, and full model SFM printing tests to explore and optimize the fabrication schemes where par- allel, non-parallel, and creased slicing methods to create toolpaths are compared and chosen to adapt different discrete components.

Hierarchical Bayesian modeling for calibration and uncertainty quantification of constitutive material models: Application to a uniaxial steel material model

Constitutive material models play an integral role in finite element (FE) modeling of structural components and systems and are governed by a set of parameters. The values of the material model parameters are important for the FE model to be able to predict the real structural behavior as closely as possible. Realistic cyclic material constitutive models well calibrated to experimental data are critical when predicting the nonlinear dynamic response of structural systems to extreme loads (e.g., earthquakes, high winds, blast). Hence, this study focuses on the inference and uncertainty quantification of material model parameters from an experimental dataset consisting of data from experiments on multiple specimens of the same kind, which is a topic of great interest to the structural modeling and simulation community. Traditionally, Bayesian inference is performed by pooling the data from all the specimens, or by considering the data from a single specimen, disregarding the inherent variability (aleatory uncertainty) among specimens of the same kind. Consequently, traditional approaches fail to capture the population distribution of material model parameters, which represents the aleatory specimen-to-specimen variability that is essential for conducting reliability analysis and uncertainty propagation studies. Moreover, these approaches cannot accurately simulate the response of new specimens. To overcome these limitations, this study introduces a novel application of hierarchical Bayesian inference for calibrating material model parameters. By simultaneously considering experimental data from multiple specimens of the same kind, hierarchical Bayesian modeling quantifies both epistemic uncertainty and aleatory specimen-to-specimen variability. In this study, the parameters of the well-known Giuffré-Menegotto-Pinto (GMP) uniaxial material model for reinforcing steel are calibrated and validated based on a dataset of experimental cyclic tests conducted on thirty-six steel specimens, or coupons, originating from three different manufacturing mills, complying to two different manufacturing standards, and subjected to different strain histories. These strain histories are similar to those experienced during seismic events by reinforcing steel bars within reinforced concrete structures. The material model parameters are calibrated using both the traditional and the hierarchical Bayesian approach and the results are compared. Based on the experimental dataset employed in this study, a joint probability distribution of the GMP material model parameters that quantifies both epistemic (due to finite sample size) and aleatory (coupon-to-coupon) variability or uncertainty is provided which can be used for uncertainty propagation in reliability and risk analyses of nonlinear dynamic systems.

Benefits, implementation and sustainability of innovative paediatric models of care for children with type 1 diabetes: a systematic review

Background and aimThe evidence about the acceptability and effectiveness of innovative paediatric models of care for Type 1 diabetes is limited. To address this gap, we synthesised literature on implemented models of care, model components, outcomes, and determinants of implementation and sustainability.MethodsA systematic review was conducted and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Database searches of Medline, CINAHL, EMBASE and Scopus were conducted. Empirical studies focused on Type 1 diabetes paediatric models of care, published from 2010 to 2022 in English were included.ResultsNineteen extant studies reported on models and their associations with health and psychosocial outcomes, patient engagement with healthcare, and healthcare costs. Thirteen studies described multidisciplinary teamwork, education and capacity building that supported self-care. Four studies involved shared decision making between providers and patients, and two discussed outreach support where technology was an enabler. Fourteen studies reported improvements in health outcomes (e.g. glycaemic control), mostly for models that included multidisciplinary teams, education, and capacity building (11 studies), outreach support or shared care (3 studies). Four studies reported improvements in quality of life, three reported increased satisfaction for patients and carers and, and one reported improved communication. Four of five studies describing shared care and decision-making reported improvements in quality of life, support and motivation. Outreach models reported no negative outcomes, however, accessing some models was limited by technological and cost barriers. Eight studies reported on model sustainability, but only half reported implementation determinants; none reported applying a theoretical framework to guide their research.ConclusionSome health and psychosocial benefits were associated with newer models. To address knowledge gaps about implementation determinants and model sustainability, longitudinal studies are needed to inform future adoption of innovative models of care for children with Type 1 diabetes.

Modeling spatial correlation between earthquake insured losses in New Zealand: A mixed-effects analysis.

Earthquake insurance is a critical risk management strategy that contributes to improving recovery and thus greater resilience of individuals. Insurance companies construct premiums without taking into account spatial correlations between insured assets. This leads to potentially underestimating the risk, and therefore the exceedance probability curve. We here propose a mixed-effects model to estimate losses per ward that is able to account for heteroskedasticity and spatial correlation between insured losses. Given the significant impact of earthquakes in New Zealand due to its particular geographical and demographic characteristics, the government has established a public insurance company that collects information about the insured buildings and any claims lodged. We thus develop a two-level variance component model that is based on earthquake losses observed in New Zealand between 2000 and 2021. The proposed model aims at capturing the variability at both the ward and territorial authority levels and includes independent variables, such as seismic hazard indicators, the number of usual residents, and the average dwelling value in the ward. Our model is able to detect spatial correlation in the losses at the ward level thus increasing its predictive power and making it possible to assess the effect of spatially correlated claims that may be considerable on the tail of lossdistribution.

Black-box modeling of PMSG-based wind energy conversion systems based on neural ODEs

Abstract Integrating renewable energy sources like wind power into the power grid enhances the dynamic interactions among renewable energy-producing equipment, leading to new technological issues for the power grid. Modeling and simulation are essential to ensure the stability of the emerging power grid, but they require precise dynamic component modeling, which is often unavailable due to technical confidentiality and other factors. Conventional hardware-in-the-loop (HIL) simulation can accurately simulate the dynamics of a single renewable energy device, but not the complex dynamics of multiple devices. This research introduces a method that combines classical mechanism modeling and differential neural network modeling to create accurate wind turbine models utilizing equipment measurement data or HIL simulation data. A realistic wind turbine electromagnetic transient simulation model of a specific type is developed and validated by connecting it to the IEEE-39 node system, confirming the model’s accuracy.

Examining the Mediating Effect of the Rural Economic Dynamization between the Socio-Environmental Heritage and Sustainability of Protected Areas

This study examines the mediating effect of rural economic dynamization between socio-environmental heritage and the sustainability of protected areas in the buffer zone of the Serranía de las Quinchas Regional Natural Park, located in the municipality of Otanche, Boyacá Department, Colombia. The study population includes families that are part of the productive units in this area. The methodological approach of this study is based on partial least squares structural equation modeling. The working unit was established in the regional protected areas of Colombia, specifically in the Serranía de las Quinchas Regional Natural Park. A sample of 172 participants was selected using a non-probabilistic intentional sampling method, covering academics, company representatives, social leaders, local authorities, and representatives of non-governmental organizations. The study variables were measured using a scale with satisfactory psychometric properties, which included 12 items for socio-environmental heritage, 17 items for rural economic dynamization, and 11 items for the sustainability of protected areas. These were structured into subcategories based on the ecosystem services approach (factors that demonstrate social and economic dynamics). Responses were collected using a five-point Likert scale. The sample was analyzed using SmartPLS 3.3.3 software, applying a reflective–reflective hierarchical component model to evaluate the first- and second-order relationships among the variables. The results demonstrate the importance of socio-environmental heritage for local communities as a strategic component that facilitates the rural economic dynamization of protected areas based on sustainability. This research contributes to understanding the relationship between socio-environmental heritage and the sustainability of protected areas, mediated by rural economic dynamization, highlighting the relevance of in situ conservation strategies and prospective planning of these territories to implement sustainability dynamics. It is concluded that rural economic dynamization acts as a significant mediator in the relationship between socio-environmental heritage and the sustainability of protected areas, emphasizing the need to integrate these dynamics into the management of natural resources and the promotion of sustainable development in rural communities.

A Component Method for Full-Range Behaviour of Embedded Steel Column Bases

This paper introduces a component model for analysing embedded column bases to predict rotational stiffness, moment resistance, and the full-range moment–rotation response. The key components identified include the embedded column, concrete in compression on the column side, concrete in compression beneath the base plate, concrete in punching shear above the base plate, and anchor bolts. The embedded column is modelled as a Timoshenko beam, considering both shear and flexural deformations, while other components are represented by springs. Methods are provided for determining their uniaxial constitutive behaviour. A simplified iterative solution method is proposed, where the embedded column is further simplified into three rigid segments to specifically address shear and bending deformations. A corresponding simplified finite element model is developed for accurate numerical solutions. The validity of the component model is confirmed through comparisons with the results of existing tests and refined solid finite element analysis for H-steel column bases. The simplified iterative solution method effectively predicts strength but underestimates the stiffness of deeply embedded column bases. This is due to the trilinear deformation pattern simplification, which concentrates flexural deformation at the upper bearing stress resultant force point, leading to an overestimation of steel column rotation on the foundation surface.

Study on Seismic Behavior and Component Vulnerability of Corroded RC Shear Walls Subjected to Flexural Shear Failure

ABSTRACT The impact of corrosion degree, axial compression ratio, reinforcement ratio of longitudinal bar and horizontal distribution rebar, and stirrup of boundary column on seismic performance of RC shear walls were investigated. The corrosion forms (rust expansion cracks and corroded steel bars), failure process, hysteretic characteristics, bearing capacity, and deformability were compared. Subsequently, a numerical model of corroded RC shear walls was established adopting shell elements. Finally, according to the numerical simulation method, considering the uncertainty of corrosion degree and material parameters, the vulnerability models of RC shear wall components with different corrosion degrees were built. The results show that the mechanical properties of the shear wall were seriously deteriorated due to the corrosion of steel bars, and the ultimate displacement and ductility coefficient of severely corroded specimens were reduced by 28.5% and 12.27% respectively, compared to non-corroded specimens. A proposed numerical modeling method for corroded RC shear walls based on shell element is accurate, and the bearing capacity error and energy dissipation error of the simulation and test results were less than 20%. As the degree of corrosion grew, the probability of shear wall components experiencing more severe failure added significantly. When the displacement angle was 1/120 (This is the limit value of elastic-plastic displacement angle specified in the code), the probability of DS3 and DS4 occurring in the shear wall with a corrosion degree of 0% were 56% and 39.44%, and the probability of DS4 and DS5 occurring in the shear wall with a corrosion degree of 10% were 41.1% and 38.44%.

Title evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Trends and cycles during the COVID-19 pandemic period

We perform several trend-cycle decompositions through the lens of two unobserved components models, herein estimated for Portugal and the euro area. Our procedure copes with the COVID-19’s consequences by explicitly considering potentially larger second moments during that period. This is achieved through a set of pandemic-specific shocks affecting only the 2020–21 period and embedded into estimation through a piecewise linear Kalman filter. Our methodology generates negligible historical revisions in key smoothed variables when the sample period is expanded until 2021:4, since pandemic shocks absorb a great deal of data volatility with minimal impacts on filtered data revisions or estimated parameters. Furthermore, non-pandemic shock volatility remains largely unaffected by the pandemic period. Innovations affecting the cycle in our preferred model are the key propellers of GDP developments during the COVID-19 pandemic period.

Pemodelan Komponen Sistem Enterprise Resource Planning pada Industri Produksi Minyak

The digitalization of technology in the current era of globalization has brought many changes to the industry. The emergence of Enterprise Resource Planning (ERP) functions to integrate all departments and industrial business functions, especially in the oil production sector. ERP systems simplify business processes by integrating key functions from various departments. The business processes in the oil production industry are currently not yet running, which has given rise to problems with errors in purchasing goods from suppliers, inaccurate calculations of raw material usage, raw material stocks not being updated quickly, and purchasing reports not being generated automatically. Based on the background of these problems, the industry requires a component modeling that helps the ERP implementation process. Component modeling allows users in industry to understand ERP systems better without being overwhelmed by product or technical details. This research aims to define the ERP system components that are taken into consideration in its implementation. The research stages are divided into five, namely pre-implementation, analysis, design, construction and implementation. The results of the research are component model designs in terms of software, process flow, user mindset, and change management that will be used in implementing the ERP system

CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval

The first-stage retrieval aims to retrieve a subset of candidate documents from a huge collection both effectively and efficiently. Since various matching patterns can exist between queries and relevant documents, previous work tries to combine multiple retrieval models to find as many relevant results as possible. The constructed ensembles, whether learned independently or jointly, do not care which component model is more suitable to an instance during training. Thus, they cannot fully exploit the capabilities of different types of retrieval models in identifying diverse relevance patterns. Motivated by this observation, in this paper, we propose a Mixture-of-Experts (MoE) model consisting of representative matching experts and a novel competitive learning mechanism to let the experts develop and enhance their expertise during training. Specifically, our MoE model shares the bottom layers to learn common semantic representations and uses differently structured upper layers to represent various types of retrieval experts. Our competitive learning mechanism has two stages: (1) a standardized learning stage to train the experts equally to develop their capabilities to conduct relevance matching; (2) a specialized learning stage where the experts compete with each other on every training instance and get rewards and updates according to their performance to enhance their expertise on certain types of samples. Experimental results on retrieval benchmark datasets show that our method significantly outperforms the state-of-the-art baselines in the in-domain and out-of-domain settings.

Development of Hardware-in-the-Loop Simulation Test Bed to Verify and Validate Power Management System for LNG Carriers

Liquefied natural gas carrier (LNGC) orders are increasing owing to marine environment regulations. The complexity of the integrated system applied to shipbuilding and software errors have increased with the high degree of automation. Direct on-site inspection methods are associated with high costs and safety risks, whereas software-based simulations rely heavily on the accuracy of the models of power system components. Hardware-in-the-loop simulation (HILS) can be utilized for designing and testing intricate real-time embedded systems. Specifically, HILS offers a reliable means of evaluating power management system (PMS) performance for LNGCs, which are high-value vessels commonly used in offshore plants. This study proposes a PMS–HIL test bed comprising a power supply unit, consumer, simulation control console, and main switchboard. The proposed HILS test bed utilizes the real equipment data of the shipbuilding industry to replicate the conditions associated with actual LNGCs. The proposed system is verified and validated through a software acceptance test procedure. Additionally, load-sharing, load-dependent start, blackout prevention, and preferential tests are performed for the PMS function evaluation. Test results indicate that the proposed system has great potential for conventional PMS commissioning. Therefore, it exhibits the potential to replace traditional factory acceptance tests. Additional development of the system will be conducted for ship automation, utilizing PMS control and an energy management system.

Population genomics of emerging multidrug-resistant Salmonella derby from pork and human in Guangdong, China

Salmonella is a foodborne pathogen that poses a severe public health threat. Salmonella enterica serovar Derby (S. Derby) is one of the top five serovars isolated from humans and animals, and it carries the potential risk of transmission to humans through consumption of pork and related products. This study isolated 98 S. Derby, mainly from pork, and clinical samples in Guangdong to investigate and compare their molecular characteristics, phylogenetic relationships, transmission routes, antimicrobial resistance phenotypes, genotypes, and virulence profiles. Whole-genome sequencing (WGS) revealed that all S. Derby isolates belonged to ST40 and displayed a relatively large core genome. Phylogenomic analysis indicated the possibility of clonal transmission of S. Derby not only between pork and humans but also across geographic areas in Guangdong over an extended period of time. Discriminant analysis of principal components (DAPC) model showed that a significant proportion of S. Derby isolates retrieved from multiple hosts originated from pork. Furthermore, similar antimicrobial resistance phenotypes and genotypes were found in S. Derby strains recovered from animal products and humans. All S. Derby isolates were found to contain numerous virulence genes, primarily related to fimbrial adherence determinants and secretion system components. This study offers valuable insights into the transmission routes of S. Derby between pork and humans and provides essential data for public health management.

Modeling the dynamic interaction between machine tools and their foundations

The performance of a machine tool is directly influenced by the characteristics of the floor, subsoil, and their interaction with the installed machine. Installing a machine tool in its operational environment poses a distinct challenge that bridges mechanical and civil engineering disciplines. This interdisciplinary issue is often overlooked within the individual separate disciplines. However, effectively addressing this challenge requires a comprehensive understanding of mechanical and civil engineering principles. To address this problem, the present study proposes a method for improved modeling of the dynamic properties of the machine tool by considering the foundation and the subsoil on which it is installed. The method is based on finite element modeling. Linear models of the system components and the connections between them were used. These, supplemented with damping expressed by complex stiffness, made it possible to determine the natural frequencies, mode shapes, and frequency response functions (based on which the transmissibilities were obtained). Based on the experimentally verified models of vertical and horizontal lathes, the sensitivity analysis aimed at estimating the impact of changes in system parameters on vibration transmissibility for a floor-type and a block-type foundation was conducted. Thus, it was possible to identify those machine tool-support-foundation-subsoil system parameters that had the most significant impacts on the vibration's transmissibility. After analyzing the cases discussed, it became evident that the transmissibility of vibrations is primarily influenced by two key factors. First and foremost, the properties of the structural loop of the machine tool played a significant role. Additionally, the characteristics of the subsoil on which the foundation was situated emerged as a crucial determinant in the observed vibration transmissibility.

Simulation Analysis of Non-concentric Squeeze Film Damper

Squeeze film dampers are components that provide additional damping for rotating motors. In general, in order to achieve the best results of the squeeze film damper, it is necessary to appropriately increase the damping value, reduce the stiffness and set a reasonable eccentricity. In the process of designing the squeeze film damper, we can apply the rotor dynamics module of COMSOL software to model and simulate it, so as to achieve better simulation results and lay a foundation for the subsequent development and design of the product. In COMSOL software, in order to simplify the modeling of rotor components, we usually model squeeze film dampers based on the damping coefficient. The model calculates the damping coefficient for a short squeeze film damper and compares the results with the analytically calculated values. In addition, the damping coefficient depends on the position of the journal in the damper, i.e., the magnitude of the eccentricity. In this paper, by analyzing the dimensionless damping coefficient, bearing stiffness, journal displacement, and fluid load at different eccentricity, and plotting the fluid pressure distribution and the average oil film flow rate of the squeeze film damper, we can find the most suitable range of eccentricity and the damage-prone part of the damper, which can provide an important reference for the actual design of the squeeze film damper.

Architecture Tune is a Time Symphony

Statement of the problem. We investigate the concept of «an architecture tune is a time symphony» that combines a conceptual, artistic and aesthetic, compositional and functional unity of an idea of architectu-ral piece of work and its implementation essential for a viable architectural piece of work. Results. The ideas of mutual integral connection between architecture and music in temporary, spatial, temporary and spatial, content, artistic and symbolic aspects are examined. The model «Fundamental Components of Musical and Architectural Literacy» is proposed. Conclusions. A mutual connection between architecture and music at the level of content organization for developing the concept of space in motion and in time is elaborated for the method of architectural designing at the design stage. The model of the general components of the artistic development of a musical as well as an architectural piece is set forth.

Thermodynamic analysis of waste heat in a combined super-critical CO2 Brayton cycle for power and hydrogen production

The current investigation aims to propose a novel cycle to generate power and hydrogen using waste heat. For this purpose, super-critical carbon dioxide Brayton cycle, Organic Rankine Cycle (ORC) and proton exchange membrane (PEM) electrolyser systems are consideredin the cycle. Energy, exergy analyses along with parametric study are performed in the research. The best organic working fluid is selected for ORC based on the obtained results. Zero-dimensional modeling for components is performed and results are presented. Results show that the net power generation is 245.5 MW, thermal efficiency is 40.97 %, exergy efficiency is 56.73 %, and hydrogen and oxygen production is 9.04 kg/h and 74.2 kg/h, respectively. The optimum working pressure ratio and evaporator temperature are calculated. The effect of different working parameters on the system performance is obtained. It is shown that increasing the isentropic efficiency of the main and recompression compressors increases power generation, hydrogen production and system efficiency. Furthermore, increasing the turbine’s inlet temperature increases the power generation of the system.

Effects of a physical therapist-driven individualized hybrid model of the exercise component of cardiac rehabilitation on patient outcomes: a prospective single group, time-series design

Purpose The aim of this prospective single group, time-series study was to determine the feasibility, adherence, and effectiveness of an individualized physical therapist (PT)-driven hybrid model of the exercise component of cardiac rehabilitation (CR) that uses a novel intensity-recovery progression protocol (IRPP) and cardiac testing template (CTT) to assess achieved heart rate (HR) intensity, HR recovery, and intensity-recovery total to guide treatment. Methods Assessment of a questionnaire, treadmill 6-min walk (6MW), 1-min sit-to-stand (1STS), 1-min step, and 1-min agility square tests were assessed on 100 participants. Compared to traditional CR the 36-visit 1:1 hybrid model was individualized using the IRPP program and CTT. Results Adherence was 35% (timely) and 44% (overall) completion. The per-protocol analysis (PPA) and intent-to-treat (ITT) analysis suggest significant improvement in objective assessments baseline to visit 15 (PPA = 11 of 14) (ITT = 13 of 14), baseline to visit 30 (PPA = 12 of 14) (ITT = 12 of 14) and visit 15 to visit 30 (PPA = 9 of 14) (ITT = 10 of 14). Improvement beyond the minimal clinically important difference (MCID) was 94.3% in the 6MW and 91.4% in the 1STS. Conclusions The PT-driven IRPP program was feasible in terms of adherence and safety, showing significant improvement in a majority of assessments. Analysis of HR using the CTT may help clinical decision making for progression in CR. Implications for rehabilitation Cardiac rehabilitation (CR) is an underutilized means of improving health for people recovering from cardiac surgery. People recovering from cardiac surgery have complex reasons for why they choose to enroll in, drop out from, or complete a CR program. Reporting of outcomes in CR and progression in intensity is not often individualized. An individualized physical therapist driven CR program using both subjective and objective assessments may be successful at improving adherence and effectiveness in this cohort.

Seismic behavior of high-rise modular buildings with simplified models of inter-module connections

Inter-module connections serve as crucial components, horizontally and vertically connecting individual modules to form modular buildings. This paper presents a component-based model that divides inter-module connections into vertical and horizontal connection components, facilitating the simplification of shear and axial behaviors for input into the global numerical model. Initially, experimental studies and numerical simulations were conducted to investigate the shear and axial behavior of these connection components, following which simplified connection component models were derived. Subsequently, a component-based model of inter-module connections was established, in which the shear and axial properties of the vertical and horizontal components were represented by nonlinear connector elements. Finally, the proposed component-based model was incorporated directly into the global frame models of high-rise steel modular buildings, and the seismic behavior was evaluated. The accuracy of the proposed component-based model was investigated by comparing the natural vibration characteristics and global building responses of high-rise steel modular buildings with traditional empirical models established based on assumptions of rigid or pinned fixities. The results reveal that traditional empirical models fail to accurately represent the discontinuous properties of inter-module connections, resulting in an overestimation of structural lateral stiffness. In contrast, the component-based model accounts for the actual load-transfer mechanisms of vertical and horizontal components, providing a more accurate understanding of the natural vibration characteristics and seismic response of high-rise steel modular buildings. The proposed component-based model establishes a critical link between isolated connection behavior and structural response assessment for high-rise steel modular buildings, making it well-suited for accurately predicting global building responses.