Strain Conditions Research Articles

Assessment and Validation of Predictive Growth Models for Locally Isolated Salmonella enterica and Listeria monocytogenes in Alfalfa Sprouts at Various Temperatures

ABSTRACTSprouts are popular due to their high nutritional content, including vitamins, minerals, antioxidants, and enzymes. However, the conditions favorable for sprouting, such as warm and humid environments, are also ideal for the growth of bacteria, including food‐borne pathogens. Here, we analyzed the growth and developed predictive models of locally isolated and commercial strains of Salmonella enterica and Listeria monocytogenes in alfalfa sprouts under various constant temperatures, ranging from 5°C to 25°C. Our findings indicated that these pathogens could grow at 5°C in sprouts, albeit with a low growth rate. A rapid increase in concentration occurred at temperatures of 10°C and above. The fitted models demonstrated high performance, with R2 values ranging from 0.964 to 0.997 and RMSE values ranging from 0.15 to 0.51, respectively. Based on the fitted values, bias factor (Af) values varied between 1.01 and 1.06, with all accuracy factor (Bf) values at 1.00. Acceptable prediction zone (APZ) values ranged from 81.8% to 100%. Validation of the models under dynamic temperature conditions for specific strains showed acceptable performance. This study enhances our understanding of S. enterica and L. monocytogenes growth in alfalfa sprouts. The findings of this study could be used to improve the risk assessment of these pathogens in alfalfa sprouts.

Effect of alloying element segregation on theoretical strength and structural low-energy transition of Ni grain boundaries: A first-principles computational tensile test study

Enhancing the stability and strength of nanocrystalline metals through the manipulation of grain boundary (GB) chemistry and structure is crucial for their engineering applications. In this study, first-principle computational tensile tests on Ni Σ5 [001] (210) GBs were conducted with considering Poisson's ratio and strengthening effect of alloying elements B, W, Zr, Ta, B-W and Zr-Ta segregation. The results indicate that the Zr-Ta co-segregated GB shows a remarkable increase in theoretical tensile strength by 195 % compared to the clean GB under small strain conditions. As tensile strain increases, both clean and segregated GBs undergo a low-energy structural transition from the Σ5 [001] (210) to the more stable Σ11 [110] (113). This work presents a promising approach for enhancing the stability of Ni nanograined materials through tensile deformation and GB segregation.

3D strain heterogeneity and fracture studied by X-ray tomography and crystal plasticity in an aluminium alloy

Strong correlations between measured strain fields and crystal plasticity finite element (CP-FE) predictions based on the real microstructure are found for a plane strain tensile specimen made of 6016 T4 aluminium alloy. This is achieved using multimodal X-ray lab tomography giving access to both the initial grain structure and the strain evolution. The real microstructure of the central region of interest (ROI) of the undeformed specimen is obtained non destructively using lab-based diffraction contrast tomography (DCT) and meshing. An in situ tensile test, using absorption contrast tomography (ACT) is then performed for twelve loading increments up to fracture. Taking advantage of the plane strain condition, the evolution of the internal strain field is measured by two-dimensional digital image correlation (DIC) in the material bulk using the natural speckle provided by intermetallic particles. Early strain heterogeneities in the form of slanted bands, that are spatially stable over time, are revealed and the fracture path – determined from the post mortem scan – is found to coincide with the bands exhibiting maximum strain. CP-FE simulations are performed on the meshed microstructure of the specimen acquired by DCT and are compared with image correlation measurements. The measured strain fields are well described by 3D CP-FE predictions, whilst it is shown that neither a macroscopic anisotropic plasticity model nor a CP-FE simulation with random grain orientations could reproduce the measurements.

Shakedown analysis of incompressible materials under cyclic loads: A locking-free CS-FEM-Q5 numerical approach

Volumetric locking may occur in plastic analysis of incompressible materials using low-order finite elements due to incompressibility constraints. This study presents a locking-free smoothed five-node quadrilateral element-based approach for plastic analysis in structural engineering. The proposed Q5-element employing four cell-based smoothing domains effectively alleviates the volumetric locking issues, here in the problems under plane strain conditions. The resulting large-scale optimization problem is formulated in a conic programming form, enabling efficient use of the interior-point optimizer. Numerical investigations demonstrate the method’s effectiveness in alleviating volumetric locking, accurately predicting collapse and shakedown limits, and generating interaction diagrams for load-carrying capacity and structural collapse mechanisms.

A computationally efficient Element Edge point numerical integration scheme in the meshless method framework for solving fracture problems

The fracture problem is modeled using the Radial Point Interpolation Meshless Method (RPIM) to solve for displacements. Further, the stresses and Stress Intensity Factor (SIF) are calculated using obtained displacements. An effective numerical integral quadrature called the Element Edge point(EE) scheme is used as an alternative to conventional Gauss Quadrature to improve computational efficiency. A comparative study based on two numerical integration schemes, the Element Edge point scheme and Gauss Quadrature, is conducted on four benchmark problems of thick, cracked plates owing to plane strain conditions. The study reveals that the proposed Element Edge point (EE) scheme is computationally efficient and works well in the meshless method framework.

Active control of transonic airfoil flutter using synthetic jets through deep reinforcement learning

This paper presents a novel framework for the active control of transonic airfoil flutter using synthetic jets through deep reinforcement learning (DRL). The research, conducted in a wide range of Mach numbers and flutter velocities, involves an elastically mounted airfoil with two degrees of freedom of pitching and plunging oscillations, subjected to transonic flow conditions at varying Mach numbers. Synthetic jets with zero-mass flux are strategically placed on the airfoil's upper and lower surfaces. This fluid–structure interaction (FSI) problem is treated as the learning environment and is addressed by using the arbitrary Lagrangian–Eulerian lattice Boltzmann flux solver (ALE-LBFS) coupled with a structural solver on dynamic meshes. DRL strategies with proximal policy optimization agents are introduced and trained, based on the velocities probed around the airfoil and the dynamic responses of the structure. The results demonstrate that the pitching and plunging motions of the airfoil in the limited cycle oscillation (LCO) can be effectively alleviated across an extended range of Mach numbers and critical flutter velocities beyond the initial training conditions for control onset. Furthermore, the aerodynamic performance of the airfoil is also enhanced, with an increase in lift coefficient and a reduction in drag coefficient. Even in previously unseen environments with higher flutter velocities, the present strategy is achievable satisfactory control results, including an extended flutter boundary and a reduction in the transonic dip phenomenon. This work underscores the potential of DRL in addressing complex flow control challenges and highlights its potential to expedite the application of DRL in transonic flutter control for aeronautical applications.

Accurate evaluation on peak shaving capacity of combined-heat-and-power thermal power units based on physical information neural network

The high proportion of new energy requires the power system to have sufficient flexibility and peak shaving capacity. The combined-heat-and-power thermal power unit is one of the main flexibility resources. Accurately evaluating the peak shaving capability from thermal power units is of great significance for power system scheduling. However, there are some problems in the previous evaluation models. Fully mechanistic models may exhibit poor accuracy due to component degradation and other reasons, while fully data-driven models may exhibit poor generalization performance due to limited training conditions. To address these issues, this paper first uses physical information neural network to fuse thermal power mechanisms and operational data, and constructs a high-precision and strong-generalization power output evaluation model. Then, error indicators and generalization indicators are used to validate the effectiveness and superiority of the model. In the test set, the mean absolute error, root mean square error and Pearson correlation coefficient of the model are1.633 MW, 1.971 MW and 0.9643, respectively. Based on this model, the peak shaving capacity range of the target thermal power plant under different heating demands is calculated. Finally, the experiment analyzed the real-time peak shaving capability and peak shaving margin.

A new theoretical model for high-order harmonics of SH0 mode ultrasonic guided waves based on magnetostrictive mechanism

In recent years, it was found that magnetostrictive ultrasonic guided wave transducers experimentally excited nonlinear harmonic components under a certain combination of dynamic and static magnetic fields. However, a satisfactory model for the relevant excitation mechanisms is not available. In this study, a new magnetostrictive guided wave excitation model was established and the causes for harmonics generation were analyzed. In addition, the calculation results of the model were obtained under different magnetic field parameters. We firstly changed the calculation conditions of magnetostrictive strain in the model and then theoretically calculated the odd and even harmonics of SH0 mode ultrasonic guided waves for the first time. Furthermore, the accuracy of the model was experimentally verified. By changing the strength ratio of the dynamic magnetic field to the static magnetic field (HD/HS), the excitation amplitudes of odd and even harmonics could be regulated with a magnetostrictive sensor. As the ratio of HD/HS increased, the normalized amplitude of the second harmonic firstly increased and then decreased, whereas the normalized amplitude of the third harmonic showed an exponential growth with different curvatures. This study enriched the theory of magnetostrictive guided wave excitation and provided a theoretical basis for the applications of magnetostrictive sensors.

Peer learning and peer assessment in institutions of higher education

The article examines the types of control and the most important principles of evaluating the knowledge of higher education students; the advantages of the modular rating system for the organization of training and training in "peer-to-peer" or peering training conditions are shown; the basis of peer learning is considered and various definitions of peer assessment are proposed. The basis of peering interaction is Web 3.0 technologies, the Internet, a large number of open educational resources (OER), and mass digitization of various materials. Peer 2 Peer University (P2PU) is an example of peering interaction and its successful functioning system. The system of peering interaction using ICT is revealed and the possibilities for peering assessment, which are provided in the applications of research learning spaces, are shown. The features of peer evaluation and consideration of these features when developing evaluation criteria are described. Based on the results of the ascertainment experiment and the conclusions regarding the renewal and improvement of the educational sector, in general, and the evaluation of higher education applicants, in particular, a model of digital tools and methods of introducing peer evaluation into the educational process of higher education institutions was introduced into the educational process of higher education institutions.

A self-powered and self-sensing hybrid energy harvester for freight trains

Freight trains, being crucial for economic development, often face challenges due to the lack of electrical infrastructure. In this study, a self-powered and self-sensing hybrid energy harvester system (SS-HEH) is proposed, it consists of an electromagnetic generator (EMG), a piezoelectric energy harvester (PEH), and an energy input module. The proposed EMG utilizes a rolling magnet to intersect the square coil, thereby better adapting to the operational conditions of freight trains and producing higher electrical energy output. Additionally, the PEH converts bogie vibration signals into electrical signals to detect bogie operations. The EMG acts on the PEH, inducing bending and generating electrical signals. Conversely, the PEH acts on the EMG to maintain it horizontally, enhancing its ability to absorb the vibration energy of the bogie and forming a bistable system. Furthermore, at a speed of 40 km/h, the EMG voltage with PEH increased by 43.75 % compared to the scenario without PEH. The electrical performance of the SS-HEH was assessed through shake table experiments, yielding an RMS voltage of 11.5 V and output power of 74.1 mW. In addition, combined with deep learning, SS-HEH has an accuracy of 97.41 % in detecting the operating status of bogie.

Parent Training for Disruptive Behaviors in Referred Children with Autism Spectrum Disorder: A Randomized Controlled Trial.

The purpose of this study was to investigate whether face-to-face and therapist-assisted online (i.e., blended) behavioral parent training are effective on reducing disruptive behaviors in children with autism spectrum disorder (ASD) in routine mental health care. Ninety-seven children with ASD (4-13years; 76 boys) were randomized to face-to-face parent training, blended parent training, or a waitlist control condition. We assessed treatment effects on parent-rated child noncompliance (primary outcome) and irritability (secondary outcome). This involved comparing both formats separately to the control condition using linear regression models. Child behaviors at 6months follow-up were also examined. Children in the face-to-face parent training condition improved significantly more on noncompliance and irritability than children in the waitlist condition and improvements sustained to 6months follow-up. Children in the blended condition did not improve more than children in the waitlist condition and attrition was high. Our results extend findings from efficacy studies to routine mental health care and advocate the use of face-to-face parent training for disruptive behaviors in children with ASD. More research into blended parent training programs for children with ASD and disruptive behaviors in routine mental health care should be conducted to draw more definite conclusions about the value of blended parent training for these children. Trial registration number NL4712; date of registration 22-10-2014.

Differences in acute responses and chronic adaptations according to the exercise intensity reference method in previously inactive individuals

During prolonged continuous exercise, the relationship between external load (e.g., running speed) and internal load [e.g., heart rate (HR)] shifts. This means, for example, that at a given running speed, the HR will continuously increase, whereas if the goal of the exercise is to maintain a constant HR, the running speed will decrease over time. The time dependence of the internal/external load relationship could lead to different acute responses and chronic adaptations depending on the exercise intensity reference method. This hypothesis was tested in the present study. Forty-three previously inactive individuals were randomized into two groups: one group (SPEED-C) trained at a speed midway between the first and second lactate threshold (v ∆ 50LT), whereas the other group (HR-C) trained at a HR midway between the thresholds (HR ∆ 50LT). Both groups performed 30 min of continuous endurance exercise 3 times per week for 8 weeks. Maximal oxygen consumption (V̇O2max) and peak treadmill speed (Vpeak) were determined by an incremental treadmill test followed by a verification test before (PRE) and after (POST) the 8 weeks of training. V̇O2, HR, speed, and rate of perceived exertion (RPE; measured with the Borg CR10) were recorded during the first and last treadmill training sessions performed in the lab. After POST, an additional simulated session was performed with the intensity adjusted to the new training level. Thirty-four participants (9 women and 7 men in SPEED-C; 11 women and 7 men in HR-C) completed the study and were included in the analysis. v ∆ 50LT/HR ∆ 50LT occurred at 74 ± 5% of HRmax, 63 ± 4% of V̇O2max, and 60 ± 4% of V̇peak in SPEED-C and at 74 ± 5 % of HRmax, 63 ± 5% of V̇O2max, and 60 ± 6 % of V̇peak in HR-C. SPEED-C showed higher speed (+1.5 km/h, p < 0.001), V̇O2 (+6.3 mL/kg/min, p < 0.001), HR (+23 bpm, p < 0.001) and RPE (+1.9 points, p = 0.002) than HR-C during the first training session. These initial differences between groups were reduced after 8 weeks of training (speed: by -0.5 km/h, p = 0.006; V̇O2: by -2.6 mL/kg/min, p < 0.001; HR: by -14 bpm, p < 0.001; RPE: (-1.7 points, p = 0.002). However, statistically significant reductions were no longer observed when the intensity was adjusted to the new training level. V̇O2max (+1.0 mL/kg/min, p = 0.021) and Vpeak (+0.8 km/h, p < 0.001) improved more in SPEED-C than in HR-C. Among the secondary physiological characteristics investigated in this study, speed at the second lactate threshold (+1.1 km/h, p < 0.001) and v ∆ 50LT (+0.5 km/h, p = 0.008) improved more in SPEED-C than in HR-C, whereas HR at the second lactate threshold improved more in HR-C than in SPEED-C (-7 bpm, p = 0.008). The exercise intensity reference method (speed vs. HR) affects acute responses and chronic adaptations in previously inactive individuals. However, training conditioning may mitigate these differences if the intensity is not constantly adjusted to the new training level.

Understanding a new wrinkling behavior of annular grooved panel during flexible free incremental sheet forming

Wrinkling behavior of sheet metal by inappropriate process parameters and the resultant variation of thickness and microstructure during incremental sheet forming (ISF) have significant impact on forming stability and geometric profile. The wrinkling-related mechanism is yet to be well understood, which make it difficult to effectively control wrinkling defects during ISF. In the present work, the wrinkling behavior and related mechanism of a typical annular grooved panel are investigated during a novel flexible free ISF process. Experiments demonstrate that during this ISF process, the sheet material sequentially undergoes 4 deformation modes: contacting state under plane strain condition, contracting state with only elastic deflection, thickening state under uniaxial compression condition, and wrinkling state where the circumferential compressive stress exceeds the critical wrinkling stress. The evolution of these deformation modes is dominantly caused by the increasing of edge contraction and circumferential stress, which are induced by the bending moment from the forming tool and auxiliary sheets. Based on the mechanism, an analytical model is developed to predict the wrinkling behavior, by which the corresponded sheet thickness, bending moment, circumferential compressive stress and critical wrinkling stress during the wrinkling process could be comprehensively calculated. Experimental results validate that the analytical model can accurately predict the wrinkling behavior under different process parameters, material properties and auxiliary sheet materials. Through microstructural characterization, numerical simulation and analytical modeling, the influence of process parameter and material property on wrinkling behavior is systematically investigated, along with the variation of sheet thickness and microstructure under different wrinkling modes. This work enhance a deep understanding of wrinkling behavior during ISF process, thereby providing effective methods for process optimization and quality improvement.

The Impact of Pressure Training on the Performance of Semi-Professional Female Rugby League Players.

The aim of this study was to examine the effect of pressure training on the performance of semi-professional female rugby league athletes. Using a within-subjects design, 16 female athletes (19.9 ± 3.4 years) performed a passing accuracy task under three conditions; (1) a control condition; (2) a physiological fatigue condition; and (3) a threat of consequence condition. Passing performance, perceived pressure, rate of perceived exertion (RPE), and self-confidence were assessed. A significant main effect of conditions was found for rate of perceived exertion (p < 0.001), self-confidence (p < 0.028), and perceived pressure (p = 0.011). There was no main effect of condition on passing performance. Post hoc comparisons revealed that RPE was significantly higher in the physiological fatigue condition when compared to the control (p = 0.009) and threat of consequence conditions (p < 0.001). Perceived pressure was significantly higher in the threat of consequence condition compared to the control condition (p = 0.037). The main findings of this study are that (1) passing performance was not impacted by pressure training conditions, and (2) threats of consequences are an effective manipulation to generate pressure in female semi-professional rugby league players. These results offer nuanced insights into the impact of pressure generation in training environments for female semi-professional rugby league athletes.

Electroactive differential growth and delayed instability in accelerated healing tissues

Guided by experiments contrasting electrically accelerated recovery with natural healing, this study formulates a model to investigate the importance of electroactive differential growth and morphological changes in tissue repair. It underscores the clinical potential of leveraging electroactive differential growth for improved healing outcomes. The study reveals that voltage stimulation significantly enhances the healing and growth of biological tissues, accelerating the regeneration process across various growth modalities and steering towards isotropic growth conditions that do not favor any specific growth pathways. Enhancing the electroelastic coupling parameters improves the efficacy of bioelectric devices, initiating contraction and fortification of biological tissues in alignment with the electric field. This process facilitates swift cell migration and proliferation, as well as oriented growth of tissue. In instances of strain stiffening at elevated strains, the extreme critical growth ratio aligns with the predictions of neo-Hookean models. Conversely, for tissues experiencing strain stiffening under moderate to very low strain conditions, the strain stiffening effect substantially delays the onset of electroelastic growth instability, ultimately producing a smooth, hyperelastic surface devoid of any unstable morphologies. Our investigation, grounded in nonlinear electroelastic field and perturbation theories, explores how electric fields influence differential growth and instability in biological tissues. We examine the interactions among dimensionless voltage, internal pressure, electroelastic coupling, radius ratio, and strain stiffening, revealing their effects on promoting growth and delaying instability. This framework offers insights into the mechanisms behind electroactive growth and its instabilities, contributing valuable knowledge to the tissue healing.

Multimodal training on L2 Japanese pitch accent: learning outcomes, neural correlates and subjective assessments

Abstract Japanese pitch accent is phonemic, making it crucial for second-language learners to acquire. Building on theories of multimodal learning, the present study explored how auditory, visual and gestural training of Japanese pitch accent affected behavioral, neural and meta-cognitive aspects of pitch perception across two experiments. Experiment 1 used a between-subjects pre/posttest design to train native English speakers to perceive Japanese pitch accents in one of the following three conditions: (1) baseline (audio + flat notation), (2) pitch height notation (audio + notation mimicking pitch height) and (3) pitch height notation + a left-hand gesture (L-gesture) (to engage the contralateral right hemisphere specialized for suprasegmental pitch processing). Our results indicated that (2) pitch height notation training was most robust in its benefits, as participants in this condition improved on trained and novel words alike. Experiment 2 used a within-subjects design to extend Experiment 1 in three ways: adding a right-hand gesture (R-gesture) condition (to engage more segmental language areas in the left hemisphere), introducing a neural correlate of cognitive load (measured by EEG alpha and theta power) and performing a metacognitive subjective assessment of learning (e.g., ‘Which training did you find the most helpful?’). The results showed that although there were no differences among our four training conditions on learning outcomes or EEG power, participants made the most positive subjective evaluations about pitch height notation and R-gesture training. Together, the results suggest that there may be a ‘just right’ amount of multimodal instruction to boost learning and increase engagement during foreign language pitch instruction.

A novel method for predicting carburizing and quenching deformation of the gear with the mandrel based on carburizing expansion strain and dynamic thermal boundary conditions of quenching

During the carburizing quenching process, the interaction of multiple physical fields leads to significant nonlinearity in the mechanical properties and physical characteristics of the material, making prediction of carburizing quenching deformation particularly challenging. Based on the phase transformation thermo-elastic-plastic constitutive equation, this paper innovatively incorporated the deformation of interstitial solid solution induced by carburization, and integrated experimental data on material properties for 8620RH, a multi-field model for carburizing quenching was constructed. The accuracy of the proposed deformation prediction model was validated through experiments on cylindrical samples and the calculation results from specialized heat treatment software Dante. Based on the deformation prediction model, considering the flow effect of quenching medium in gear quenching process, and introducing dynamic heat boundary conditions during quenching, a finite element model for predicting carburizing and quenching deformation of the gear with the mandrel was constructed to study the deformation distribution of the gear. The accuracy of the deformation prediction model was verified through the carburizing quenching experiment of the gear with the mandrel. The results show that compared with the classical model which does not consider the carburizing expansion strain and the dynamic thermal boundary conditions, the proposed model demonstrates higher predictive accuracy in torsional deformation and expansion deformation. The research work provides a novel model and method for improving the accuracy of predicting carburizing and quenching deformation in gears.

INVESTIGATION OF THE INFLUENCE OF CHOOSING THE TYPE OF FACADE SYSTEM USING ABC ANALYSIS ON THE COST OF THE LIFE CYCLE OF THE BUILDING OBJECT

The article is devoted to a comprehensive study of the influence of the choice of the type of facade systems on the total cost of the life cycle of the construction object, with a special emphasis on the application of ABC-analysis as a tool for determining the optimal option for arranging the facade, taking into account economic and quality aspects. The main purpose of the article is to justify the feasibility of using ABC analysis to select the type of facade systems and assess its impact on the costs associated with the life cycle of the building. The article provides a detailed analysis of various types of facade systems from the point of view of their fastening, materials, design and method implementation. Such systems as ventilated and non-ventilated facades, hinged ventilated facade systems, facades with cladding made of natural stone, composite materials and other modern materials are considered. Special attention is paid to the study of technological characteristics, durability and maintenance costs of various types of facade systems. The application of ABC analysis allows classifying facade systems according to their impact on the cost and quality of construction. In this context, facade systems are divided into three categories: A - the most important and expensive, B - medium importance and expensive, C - less important and with minimal expenses. This approach allows builders and designers to focus their attention on the most critical elements that affect the overall cost and efficiency of construction.As a result of the study, it becomes possible to make an informed decision regarding the choice of the optimal facade system, which best meets the specific needs of the project and contributes to the optimization of the cost of the life cycle of the building. In particular, the selection of appropriate materials and technologies allows to reduce construction costs, ensure durability and reduce maintenance and repair costs in the future. In addition, the results of the study can become the basis for the development of practical recommendations for professionals in the construction industry, including builders, designers and architects. This makes it possible to create more efficient, economical and ecologically sustainable construction objects. Also, the article emphasizes the importance of creating specialist training schools and conditions for the successful implementation of life cycle assessment technologies in the construction industry.

High Strength and Tough Ionogels with Bicontinuous Phase Network Structure Induced by Electrostatic Adsorption Triggered Microphase Separation

AbstractA simple one‐step approach is presented to fabricate high strength and tough ionogels by copolymerizing zwitterionic monomers and monomers rich in functional groups capable of forming hydrogen bonds within an ionic liquid. The electrostatic adsorption of ionic liquid by the polyzwitterionic segment induces the formation of a bicontinuous phase network structure consisting of a polymer‐rich phase and a solvent‐rich phase. Within this structure, a polymer‐rich phase with hydrogen bonds dissipates energy and enhances the toughness of the ionogel, while an elastic solvent‐rich phase facilitates significant strain. The prepared ionogels exhibit high fracture strength (8.89 MPa), toughness (41.12 MJ m−3), and Young's modulus (58.9 MPa). The critical point for triggering the formation of a bicontinuous phase network can be precisely controlled by the maximum adsorption capacity of the zwitterionic monomers for the ionic liquid. Ionogels at the critical point of bicontinuous phase network formation demonstrate excellent fatigue resistance, with residual strain of only ≈25% under 50% to 250% strain conditions, recovering to their original state within 5 s. Due to the widespread presence of electrostatic interactions, this strategy for constructing a bicontinuous phase network structure exhibits excellent adaptability across different ionic liquid systems.

B - 115 How Training Conditions Impact Performance on a Theoretically-Derived Learning Instrument

Abstract Objective Few neuropsychological measures were developed using an explicit theory that accounts for individual performance. We developed a novel associative learning measure to address this limitation and investigated whether training conditions could influence accuracy and response time. Methods Fifty young, community-dwelling adult participants completed the novel relational learning task, which explicitly trained two stimulus pairs (A- &amp;gt; B, A- &amp;gt; C) and involved a single common stimulus. Participants identify six unique relationships between stimuli: trained relations (A- &amp;gt; B, A- &amp;gt; C), mutually entailed relations (B- &amp;gt; A, C- &amp;gt; A), and combinatorial relations (B- &amp;gt; C, C- &amp;gt; B). Participants were randomly assigned to a congruent (A is opposite B, A is opposite C) or incongruent (A is opposite B, B is the same as C) training condition and completed the procedure when stimuli were observably (e.g., color-coded shapes) or arbitrarily related (e.g., letters). Results Comparisons of accuracy between training conditions using Bayesian independent samples t-tests found moderate evidence of no reliable difference between training groups when stimuli were observably related (BF01 = 3.4, δ = 0.06) and arbitrarily related (BF01 = 3.5, δ = 0.03). Comparisons of response time found strong evidence that participants took longer to identify relations when receiving incongruent training when the stimuli were visually related (BF10 = 38.8, δ = 0.9) but inconclusive evidence when the stimuli were arbitrarily related (BF10 = 1.5, δ = 0.49) (See Table 1). Conclusion These findings suggest that manipulating training conditions does not appreciably impact the ability to identify relationships between stimuli accurately. However, training appears to increase the response time needed to identify visibly related stimuli accurately. While this is a promising theoretically-derived learning paradigm, further research is required for validation in clinical practice.