Continuous Component Research Articles

Mutual Diffusivities of Mixtures of Carbon Dioxide and Hydrogen and Their Solubilities in Brine: Insight from Molecular Simulations.

H2-CO2 mixtures find wide-ranging applications, including their growing significance as synthetic fuels in the transportation industry, relevance in capture technologies for carbon capture and storage, occurrence in subsurface storage of hydrogen, and hydrogenation of carbon dioxide to form hydrocarbons and alcohols. Here, we focus on the thermodynamic properties of H2-CO2 mixtures pertinent to underground hydrogen storage in depleted gas reservoirs. Molecular dynamics simulations are used to compute mutual (Fick) diffusivities for a wide range of pressures (5 to 50 MPa), temperatures (323.15 to 423.15 K), and mixture compositions (hydrogen mole fraction from 0 to 1). At 5 MPa, the computed mutual diffusivities agree within 5% with the kinetic theory of Chapman and Enskog at 423.15 K, albeit exhibiting deviations of up to 25% between 323.15 and 373.15 K. Even at 50 MPa, kinetic theory predictions match computed diffusivities within 15% for mixtures comprising over 80% H2 due to the ideal-gas-like behavior. In mixtures with higher concentrations of CO2, the Moggridge correlation emerges as a dependable substitute for the kinetic theory. Specifically, when the CO2 content reaches 50%, the Moggridge correlation achieves predictions within 10% of the computed Fick diffusivities. Phase equilibria of ternary mixtures involving CO2-H2-NaCl were explored using Gibbs Ensemble (GE) simulations with the Continuous Fractional Component Monte Carlo (CFCMC) technique. The computed solubilities of CO2 and H2 in NaCl brine increased with the fugacity of the respective component but decreased with NaCl concentration (salting out effect). While the solubility of CO2 in NaCl brine decreased in the ternary system compared to the binary CO2-NaCl brine system, the solubility of H2 in NaCl brine increased less in the ternary system compared to the binary H2-NaCl brine system. The cooperative effect of H2-CO2 enhances the H2 solubility while suppressing the CO2 solubility. The water content in the gas phase was found to be intermediate between H2-NaCl brine and CO2-NaCl brine systems. Our findings have implications for hydrogen storage and chemical technologies dealing with CO2-H2 mixtures, particularly where experimental data are lacking, emphasizing the need for reliable thermodynamic data on H2-CO2 mixtures.

Volatility forecasting incorporating intraday positive and negative jumps based on deep learning model

AbstractMost existing studies on volatility forecasting have focused on interday characteristics and ignored intraday characteristics of high‐frequency data, especially the asymmetric impact of positive and negative jumps on volatility. In this paper, 5‐min high‐frequency data are used to construct realized volatility which is decomposed into continuous components and jump components with positive and negative directions. Then, this information is combined with the long short‐term memory model for the realized volatility prediction. The empirical analysis demonstrates that negative jumps resulting from negative news have a more significant impact on market volatility than positive jumps. Additionally, the long short‐term memory model, which incorporates positive and negative jump volatility, outperforms traditional econometric and machine learning models in predicting out‐of‐sample volatility. Furthermore, applying the prediction results to value at risk yields a better measurement effect than the generalized autoregressive conditional heteroskedasticity model.

Use of FOLFOXIRI Plus Bevacizumab and Subsequent Therapies in Metastatic Colorectal Cancer: An Age-Stratified Analysis

BackgroundTreatment recommendations for metastatic colorectal cancer (mCRC) do not differ by age group; nevertheless, aggressive multiagent chemotherapy comprising FOLFOXIRI+bevacizumab (triplet+bev) is routinely administered in younger patients. This study analyzed real-world data on index triplet+bev use and subsequent systemic therapies. Materials and MethodsThis retrospective, observational cohort study was conducted in patients aged ≥ 18 years with mCRC, who were initiated on triplet+bev. Data were derived from the Optum de-identified electronic health record dataset. ResultsOf 36,056 patients, 14%, 36%, and 50% were aged 18-49, 50-64, and ≥ 65 years, respectively. During the study period (2010-2021), triplet+bev use increased in patients aged 18-49 years (1%-4%) but remained at approximately 3% and 1% in patients aged 50-64 and ≥ 65 years, respectively. Patient demographics and clinical characteristics varied slightly; of patients receiving triplet+bev (n = 921) versus nontriplet+bev (n = 35,132) most were male (57% vs. 52%), resided in the Midwest (54% vs. 49%) and Northeast (18% vs. 14%) US regions, and had secondary malignancies (86% vs. 73%). Following triplet+bev, most patients received subsequent therapies (including continued triplet component therapies; 97%) or subsequent “new” therapies (therapies that did not include any agents comprising triplet+bev; 57%), most frequently EGFR inhibitors (28%) and regorafenib (21%), with a similar trend among all age groups. ConclusionsOverall, this study shows that younger patients with mCRC are more likely to receive first-line triplet+bev. These results also reveal that nonchemotherapy options are often used beyond first-line triplet chemotherapy for patients with mCRC.

Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set

We propose a shrinkage heterogeneous autoregressive (HAR) model to explore the predictability of global stock market volatilities. To this end, we construct a big data environment using international stock market data, which comprises over 200 cross-market predictors, including realized variances (RVs), continuous components, jumps, leverages, overnight returns, and uncertainty indices. Two shrinkage models (LASSO and ENet) are considered for volatility modeling and forecasting. The results demonstrate that these models, notably LASSO, consistently improve predictive performance across global stock markets and daily, weekly, and monthly horizons. Their superiority extends to directional and density forecasting as well as asset allocation. There are several empirical findings of shrinkage: (i) the shrinkage degree varies significantly across forecast horizons, with longer horizons implying more predictors are needed for accurate estimation; (ii) no country/region's predictors show absolute superiority and utilize cross-market information leads to larger predictive gains, particularly for longer horizons; (iii) the predictors except for RVs and continuous components are more powerful, especially over longer horizons; and (iv) the uncertainty indices are the strongest predictors for all horizons.

Finger photopletysmography detects early acute blood loss in compensated blood donors: a pilot study

Objective. Diagnosis of incipient acute hypovolemia is challenging as vital signs are typically normal and patients remain asymptomatic at early stages. The early identification of this entity would affect patients’ outcome if physicians were able to treat it precociously. Thus, the development of a noninvasive, continuous bedside monitoring tool to detect occult hypovolemia before patients become hemodynamically unstable is clinically relevant. We hypothesize that pulse oximeter’s alternant (AC) and continuous (DC) components of the infrared light are sensitive to acute and small changes in patient’s volemia. We aimed to test this hypothesis in a cohort of healthy blood donors as a model of slight hypovolemia. Approach. We planned to prospectively study blood donor volunteers removing 450 ml of blood in supine position. Noninvasive arterial blood pressure, heart rate, and finger pulse oximetry were recorded. Data was analyzed before donation, after donation and during blood auto-transfusion generated by the passive leg-rising (PLR) maneuver. Main results. Sixty-six volunteers (44% women) accomplished the protocol successfully. No clinical symptoms of hypovolemia, arterial hypotension (systolic pressure < 90 mmHg), brady-tachycardia (heart rate <60 and >100 beats-per-minute) or hypoxemia (SpO2 < 90%) were observed during donation. The AC signal before donation (median 0.21 and interquartile range 0.17 a.u.) increased after donation [0.26(0.19) a.u; p < 0.001]. The DC signal before donation [94.05(3.63) a.u] increased after blood extraction [94.65(3.49) a.u; p < 0.001]. When the legs’ blood was auto-transfused during the PLR, the AC [0.21(0.13) a.u.; p = 0.54] and the DC [94.25(3.94) a.u.; p = 0.19] returned to pre-donation levels. Significance. The AC and DC components of finger pulse oximetry changed during blood donation in asymptomatic volunteers. The continuous monitoring of these signals could be helpful in detecting occult acute hypovolemia. New pulse oximeters should be developed combining the AC/DC signals with a functional hemodynamic monitoring of fluid responsiveness to define which patient needs fluid administration.

IMPROVING THE MANAGEMENT DECISION-MAKING PROCESS AT INTERNATIONAL ENTERPRISES

The article is devoted to topical issues of determining the technology of management decision-making at international enterprises. Since management decisions are made continuously, international enterprises need knowledge and practical use of technologies to increase their efficiency. Solving the raised issues requires the development of practical recommendations for making effective management decisions. Decision-making is an integral part of modern management. Essentially, rational or reasoned acceptance decisions are considered the main function of management. The decision-making process is a continuous and indispensable component of the management of any international enterprise or business. Managers must regularly make decisions about long-term and short-term plans. In the short term, managers have to solve everyday activities with the involvement of other employees. On the other hand, long-term decision-making involves policies and strategies that promote business development. The management matrix of the distribution of powers when making managerial decisions at international enterprises is considered, which will lead to an increase in the quality of organizational decision-making and a reduction in time loss. The stages of management decision-making at international enterprises are analyzed and systematized. The world experience of using this technology at international enterprises was studied. It has been proven that if international enterprises use an improved management decision-making process, they achieve the best results faster than others. In addition, the outcome of most decisions depends on both the quality of the decision-making process and the combination of realization and chance. Even with excellent implementation, an exemplary method can only sometimes guarantee a good result. However, it is logical to conclude that the chances of a positive outcome increase with an exemplary decision-making process and quality implementation.

Total CO2 budget estimate and degassing dynamics for an active stratovolcano: Turrialba Volcano, Costa Rica

Distributions and concentrations of carbon dioxide being emitted from active volcanoes elucidate the subsurface controls on gas ascent from the source and provide important information regarding the extent and state of the magmatic system. The main goal of this study was to determine if degassing followed open- or closed-system dynamics, and to define a baseline for eruption monitoring of degassing across the volcanic edifice through the CO2 budget estimate from the combined results of two CO2 gas emission surveys from 2021 and 2022 on Turrialba volcano, Costa Rica. This was accomplished by utilizing a new method for estimating total carbon flux on and around this persistently degassing and intermittently erupting volcano by integrating fine and coarse spatial scales of measurements; including an analysis of carbon isotopes to determine the source contributions to the gas emissions. Approximately 99% (2287 ± 1719 t CO2 day−1) of magma-derived degassing activity is advective and concentrated at the summit crater, with a smaller, continuous component of ∼1% (23.73 ± 6.65 tonnes CO2 day−1) flank diffuse soil degassing. As the majority of the gas emissions from Turrialba are concentrated in the summit plume, the system is likely experiencing open-system degassing dynamics through one dominant degassing pathway. Though at relatively low levels, the locations and distributions of diffuse degassing on the volcanic flanks allow us to delineate subsurface features that likely reveal the extent of the magmatic system of the volcano. Volcanic CO2 outputs at Turrialba primarily concentrate along faults and fractures near the summit and across the flanks where permeable zones allow gas ascent, and with limited emissions elsewhere. The results of this study provide a baseline for monitoring future changes in the Turrialba magmatic system and demonstrate the potential for applying this method to other volcanic complexes, particularly those that are poorly monitored or where there is a greater prevalence of diffuse and distal degassing.

Study and development of a logical model for an ORC based district heating renewable energy system considering discrete analysis

Renewable energy sources may help build energy-efficient, ecologically friendly communities. District heating systems are crucial for distributed renewable energy. The objective of this study is to establish a theoretical framework for a district heating distribution system capable of accommodating bi-directional flow and effectively serving a large number of consumers. Distinction and continuity are present in District Heating System fuel selection and energy demand determination. Scholarly literature suggests many modeling methods for discrete and continuous consumer decision-making. This method has been used to solve transportation, housing, and water problems. The overall demand for consumer choices can be separated into two components: a discrete component with several possibilities and a continuous component. Energy includes social, economic, security, climate, and environmental factors. This study analyzed previous energy logical modeling methods and examines energy consumption trends and climate change. This study supports its claims on modern conflicts using expert interviews, research expertise, and a thorough literature assessment. The model was used to assess control system architectural improvements and low-cost device integration. This study shows the versatility of using real data and model output under varied boundary conditions by using validation. The research suggests that adding waste heat input may make pressure equilibrium in nearby consumer substations harder. Despite assumptions and simplifications, the results show waste heat source features, benefits, and limitations.

Computing solubility and thermodynamic properties of H2O2 in water

Hydrogen peroxide plays a key role in many environmental and industrial chemical processes. We performed classical Molecular Dynamics and Continuous Fractional Component Monte Carlo simulations to calculate thermodynamic properties of H2O2 in aqueous solutions. The quality of the available force fields for H2O2 developed by Orabi and English (2018) [67], and by Cordeiro (2014) [69] was systematically evaluated. To assess which water force field is suitable for predicting properties of H2O2 in aqueous solutions, four widely used water force fields were used, namely the TIP3P, TIP4P/2005, TIP5P-E, and a modified TIP3P force field. While the computed densities of pure H2O2 in the temperature range of 253 - 353 K using the force field by Orabi & English are in excellent agreement with experimental results, the densities using the force field by Cordeiro are underestimated by 3%. The TIP4P/2005 force field in combination with the H2O2 force field developed by Orabi & English can predict the densities of H2O2 aqueous solution for the whole range of H2O2 mole fractions in very good agreement with experimental results. The TIP4P/2005 force field in combination with either of the H2O2 force fields can predict the viscosities of H2O2 aqueous solutions for the whole range of H2O2 mole fractions in reasonably good agreement with experimental results. The computed diffusion coefficients for H2O2 and water molecules using the TIP4P/2005 force field with either of the H2O2 force fields are almost constant for the whole range of H2O2 mole fractions. Hydrogen bond analysis showed a steady increase in the number of hydrogen bonds with the solute concentrations in H2O2 aqueous solutions for all combinations except for the Cordeiro-TIP5P-E and Orabi-TIP5P-E systems, which showed a minimum at intermediate concentrations. The Cordeiro force field for H2O2 in combination with either of the water force fields can predict the Henry coefficients of H2O2 in water in better agreement with experimental values than the force field by Orabi & English.

A new approach to the multiple obnoxious facility location problem based on combinatorial and continuous tools

In this paper we address the multiple obnoxious facility location problem. In this problem p facilities need to be spread within the unit square in such a way that they are far enough from each other and that their minimal distance from n communities, with known positions within the unit square, is maximized. The problem has a combinatorial component, related to the key observation made in Drezner (Omega 87:105–116, 2019) about the role played by Voronoi points. We propose a new approach, which exploits both the combinatorial component of the problem and, through continuous local optimizations, also its continuous component. We also propose techniques to limit the impact on computation times of the number n of communities. The approach turns out to be quite competitive and is able to return 24 new best known solutions with respect to the best results reported in Kalczynski (Optim Lett 16:1153–1166, 2022).

What are the key stability challenges in high-bandwidth, non-minimum phase systems with time-varying, and non-smooth delays?

The analysis and control of stability in high-bandwidth systems characterized by non-minimum phase delays represent a formidable challenge within the realm of control theory and engineering. This research aims to address the pivotal question of whether it is feasible to enhance the stability of such intricate systems. These systems inherently possess uncertain and swiftly changing delay characteristics, rendering them exceptionally demanding to control effectively. In the course of this investigation, we embark on a comprehensive exploration of the theoretical underpinnings of the stability of high-bandwidth, non-minimum phase delay systems. This encompassing inquiry encompasses a meticulous consideration of both derivative-delay and piecewise continuous delay components. To underpin our analysis, we judiciously incorporate feedback mechanisms, drawing upon mathematical tools such as the Jensen inequality and Lyapunov-based methodologies to rigorously establish stability conditions. Furthermore, our exploration extends to encompass the concept of input-output stability and complements it with the notion of asymptotic stability, thereby ensuring that the systems in question exhibit uniform stability across diverse temporal domains. The outcomes of our investigation furnish compelling evidence that by harnessing the power of discrete-time Lyapunov-Krasovskii functionals, it becomes conceivable to circumscribe the maximum delay within predefined thresholds. This achievement holds the promise of enhancing stability in non-minimum phase delay systems characterized by high bandwidth. These findings have far-reaching implications, profoundly influencing the design and control paradigms across a spectrum of engineering applications. Notably, this impact extends to areas such as communication networks, real-time control systems, and robotics, where the mitigation of instability due to non-minimum phase delays has been an enduring challenge.

Al-Quran Recitation Therapy with Surah Ar-Rahman on Students' Sleep Quality: A Randomized Controlled Trial

Sleep quality is the level of sleep satisfaction experienced by a person which includes the components of sleep quantity, sleep continuity, and fresh and fit when waking up. Poor sleep quality is associated with psychiatric disorders, such as depression and anxiety. Recitation (Murottal) Al- Quran Surah Ar-Rahman Therapy is the chanting of the holy verses of Al-Quran Surah Ar-Rahman which is given to someone to have a relaxing effect. The research was conducted on students using the randomized control trial experimental research method with pre and post approaches with the control group. The study was conducted on 36 respondents (18 respondents in the intervention group and 18 respondents in the control group). The results showed that there was an increase in sleep quality by 13.2% in the intervention group after therapy. The mean difference in sleep quality which showed an increase in sleep quality was 0.11 greater in the intervention group than the control group, but not significant (p=0.908, α=0.05). There was an increase in sleep quality for students after being given Murottal Al Quran Surah Ar-Rahman therapy. Further research is needed with a longer treatment time and it is necessary to study the factors that most influence the sleep quality of master students.&#x0D;

Melting and heat generating influences on radiative flow of two-phase magneto-Williamson nanofluid via stretchable surface with slippage velocity and activation energy

Melting heat and solutal transference in a magnetohydrodynamic flowing of Williamson nanofluid have been described, with the mathematical model guided by Arrhenius activation energy, chemically reactive species, and convective boundary restrictions. By implementing suitable similarity conversions, the regulating equations of partial differential equations (PDEs) (formed by continuity, impetus, energy, and concentricity components) are condensed to an arrangement of ordinary differential equations (ODEs). These commonalities are in nonlinear form, which includes the fluid’s velocity, heat, and concentration changes. Finally, the standard Keller box approach is used to solve this ODEs system computationally (KBM). Under the influence of regulating parameters, the computational results are tallied and displayed in suitable diagrams. The friction force factor, local Nusselt, and Sherwood values are tabulated. Furthermore, the velocity, energy, and concentration contours are plotted versus fluid thickness. The attributes of Williamson nanofluid flowing, melting heat transfer, and mass transference are debated in depth toward the end of this study. Among the most important outcomes that have been reached is that the rate of heat and solutal transport heightened between 52.5 and 55.2% by detraction of the magnetic field, Weissenberg number, and Brownian motion. We also found that there is an inverse relationship between the mass transmission and heat generating factor.

Comparison of Generalized Linear Model between Gamma and Tweedie Compound Response for Rainfall Prediction in Lampung Province

Rainfall plays a pivotal role in influencing agricultural production in Lampung province. The precision of rainfall predictions holds significant importance for enhancing agricultural yields in the region. One effective approach for modeling rainfall is Statistical Downscaling (SD), which employs statistical models to examine the correlation between large-scale (global) climatological data and small-scale (local) data. SD addresses the limitation of global scale data, such as the General Circulation Model (GCM), which lacks the resolution to directly forecast localized climate conditions like rainfall. Rainfall can be broadly categorized into continuous and discrete components. The continuous component delineates the intensity of rainfall, while the discrete component describes the occurrence of rain. Both components are integral to accurate rainfall predictions. The mixed Tweedie distribution, combining Gamma and Poisson distributions, is proficient in handling both continuous and discrete components of rainfall. GCMs commonly encounter multicollinearity issues in SD modeling, which can be mitigated through Principal Component Analysis. This study seeks to compare two regression models: the generalized linear model with a gamma response and the Tweedie compound response. Rainfall data from three distinct regions in Lampung province, representing high, medium, and lowlands, is utilized. The research findings indicate that, for high and lowlands, the Tweedie compound exhibits a smaller Root Mean Square Error of Prediction (RMSEP) compared to gamma. Conversely, in medium lands, gamma-GLM demonstrates a smaller RMSEP value than the Tweedie compound. Thus, the distribution of the Tweedie compound is better suited for use than Gamma-GLM, especially for high and lowland areas.

Linear-inverse associations of serum Klotho protein with prevalence of frailty among adults in the United States.

To investigate the potential linear relationship between serum concentrations of klotho and frailty. A retrospective analysis was conducted on the data of 9,597 middle-aged and older adults (aged 40-79 years) from the five cycles of the National Health and Nutrition Examination Survey (NHANES). Frailty was assessed using the Frailty Index, calculated as a percentage of accumulated deficits across 53 health items. Restricted cubic spline curves, subgroup analyses and logistic regression models were employed to evaluate the specific linear trend connection between circulating klotho protein concentration and frailty. When taking Klotho into account as a continuous component in Models 1 and 2, there was a substantial association between the increasing Klotho level and the reduced risk of frailty. Model 3 revealed a strong negative correlation between the Klotho and Frailty, suggesting that high levels of Klotho protein decreases the frailty prevalence [Odd ratio (OR): 0.25; 95% confidence interval (CI): 0.15-0.43]. Furthermore, according to the quartile analyses, after fully adjusting for the covariates, it was observed that, comparing to the lowest quartile of Klotho, the highest quartile of Klotho demonstrated lowest risk of frailty (OR 0.69; 95% CI 0.58-0.81, Ptrend < 0.001). The restricted cubic spline curves showed a linear relationship and an inverse association between frailty and the Klotho levels (Plinearity < 0.001; Pnon-linearity = 0.736). Klotho is inversely and linearly associated with physical frailty in the general population (aged 40-79 years), specifically in the population with an age < 65 and body mass index (BMI) ≥ 25 kg/m2. More necessary prospective studies should be done to further investigate the mechanisms underlying frailty and aging and to elucidate individual frailty causes.

Deep Neural Networks, Cellular Automata and Petri Nets: Useful Hybrids for Smart Manufacturing

In the era of Industry 4.0 and beyond, intelligent and reliable models are vital for processes and assets. Models in smart manufacturing involve combining knowledge-based and data-driven methods with discrete and continuous modelling components. Formalism choice determines models' strengths and weaknesses in accuracy, efficiency, robustness, and explainability. Hybrid models seem to be the only way to address the complexity of modern industrial systems with respect to different and conflicting quality criteria. This study focuses on three paradigms: Petri nets, cellular automata, and neural network driven deep learning. We create four hybrids: Petri nets controlling deep neural networks, and vice versa; cellular automata controlling deep neural networks, and vice versa. These hybrids combine explainable discrete models with continuous black-box models, enhancing either explainability with robustness or elevating accuracy with efficiency. The flexibility of these and similar hybrids enable enhancement of the scope and quality of modeling and simulation in smart manufacturing.

Redundancy allocation problem with a mix of components for a multi-state system and continuous performance level components

Redundancy allocation problem with a mix of components for a multi-state system and continuous performance level components

Using Structural Equation Modeling to Investigate the Neural Basis of Altered Pain Processing in Fibromyalgia with Functional Magnetic Resonance Imaging

Participants with fibromyalgia (FM) and healthy controls (HC) experienced an identical ‘threat/safety’ experimental pain paradigm while undergoing functional magnetic resonance imaging (fMRI) to investigate the differences in pain processing between the two groups. In the ‘threat’ (Pain) imaging runs, participants were told that they would receive noxious heat stimuli to their right hands, calibrated to elicit subjectively moderate levels of pain. In the ‘safety’ (No-Pain) imaging runs, no stimulus was given. This design enabled the study of both continuous and reactive components of pain processing, as well as brain activity associated with anticipation and reward. The fMRI data were analyzed with a data-driven structural equation modeling approach, and significant group-level connectivity differences were identified in both study conditions, in both time periods of interest (Expectation, Stimulation). Group-level connectivity differences in the No-Pain condition occurred mainly during the expectation of pain, and involved regions associated with emotion and reward, suggesting FM may involve altered affective/reward processing. Group-level connectivity differences in the Pain condition occurred mainly during stimulation, with the FM group having decreased connectivity between the anterior cingulate cortex (ACC) and the amygdala, and increased connectivity between the posterior cingulate cortex (PCC) and the thalamus. The decreased ACC→Amygdala connectivity supports previous findings, suggesting FM likely involves altered responses in motivational-affective aspects of pain processing. The increased PCC→Thalamus connectivity may suggest the FM group experienced heightened saliency toward the noxious stimuli, which may contribute toward the mechanism which causes hyperalgesia in FM.

Synaesthetic metaphors in the description of fragrance properties in perfumery discourse (on the material of the modern Spanish language)

The article deals with the use of synaesthetic metaphors with an olfactory component of meaning in the perfumery discourse of the Spanish language. Synaesthetic metaphors are considered as emotional-evaluative units of linguistic coding of interrelations of polysensory perception of smells, sounds, colours, tastes, temperatures through different organs of human perception and are the result of cognitive-symbolic integration of human sensory experience. The synaesthetic metaphor is viewed as a result of synaesthesia which at the level of perception influences the inventory of the linguistic means involved by the speaker. The source of the investigated empirical material studied is the fragrance descriptions presented on the website of the El Corte Ingles online store. The metaphors studied are classified according to the establishing the synaesthetic interaction of perceptual images, considering their general and particular characteristics, which are analyzed on the basis of the cognitive mechanisms underlying them, as well as from the point of view of their pragmatic potential. By applying the method of continuous sampling, component analysis, descriptive and quantitative research methods, synaesthetic metaphors have been identified, models of synaesthetic transfers have been revealed and their productivity has been established. The most productive models of synaesthetic metaphors used in the description of fragrance in perfumery discourse are models of transfer from tactile to olfactory and from visual to olfactory modalities, transfers from gustatory and auditory modalities are less represented. Also well sufficiently represented are the models of metaphorical transfer of two or more modalities to the olfactory modality.

Mechanical Characterisation of Bond Formation during Overprinting of PEEK Laminates.

The latest generation of high-temperature 3D printers enables the production of complex structural components from aerospace-grade thermoplastics such as PEEK (polyether ether ketone). However, adding long or continuous fibres is currently limited, and thermal stresses introduced during the process restrict the maximum part dimensions. Combining 3D-printed components with continuous fibre-reinforced components into one hybrid structure has the potential to overcome such limitations. This work aims to determine whether in situ bonding between PEEK laminates and PEEK 3D printing during overprinting is feasible and which process parameters are significantly responsible for the bonding quality. To this end, the bonding is analysed experimentally in two steps. Firstly, the influence of the process parameters on the thermal history and the strength of the bond is investigated. In the second step, a detailed investigation of the most critical parameters is carried out. The investigation showed the feasibility of overprinting with bonding strengths of up to 15 MPa. It was shown that the bonding strength depends primarily on the temperature in the interface. Additionally, the critical parameters to control the process were identified. The process influences that were displayed form the basis for future hybrid component and process designs.