Exploratory Experiments Research Articles

Ethanol’s Pharmacodynamic Effect on Odorant Detection in Distilled Spirits Models

Aroma perception in distilled spirits is influenced by both the physicochemical and pharmacodynamic effects of ethanol. This study measured these effects by examining the odor detection threshold (ODT) of various odorants. The physicochemical effect influences how odorants partition into the vapor matrix (headspace), while the pharmacodynamic effect affects the functioning of olfactory receptors cells (ORCs). Both factors contribute to changes in odorant ODTs, though it remains unclear which has a greater influence. Across three exploratory experiments, we demonstrated that ethanol in the vapor matrix suppressed the olfactory detection of key odorants in distilled spirits, with some chemical groups being more affected than others. This suppression effect increased as ethanol concentration rose. Notably, our results showed that ethanol’s pharmacodynamic effect plays the primary role in elevating ODTs in ethanol/water solutions, and this effect intensifies as ethanol concentration in the liquid matrix increases. These findings highlight the significant role of ethanol concentration in the vapor matrix and provide scientific support for practices such as diluting spirits or using specifically shaped glassware to lower ethanol headspace concentration during whiskey nosing (odor evaluation).

Overgamified? An Exploratory Study on Gamification and Crowdsourcing for Fake Accounts Detection in Social Networks

In this exploratory research, a gamification approach for crowdsourcing fake account detection in social networks has been proposed and evaluated for the first time. Gamification usually tries to satisfy the users’ psychological needs. However, motivation could also be based on human physiological needs. Among these needs are health, shelter, and clothes. In the gamification world, we can translate them into monetary or cash rewards. We have investigated the effects of both these rewards on users’ motivations in participating and detecting fake accounts by conducting two in-the-wild exploratory experiments and two surveys. The experimental results showed that users prefer physiological rewards over psychological rewards, and an increase in the reward (0.75 euro in this study) resulted in a 365% increase in user participation and a 28.88% decrease in number of accurate reports in the first experiment. Similarly, in the second experiment, we observed that higher monetary rewards resulted in higher user acquisition and higher user engagement, but the quality of the reports was 10% lower than the low monetary rewards. This indicates that physiological rewards can potentially make users over-motivated or, in other words, overgamified. To tackle this problem, we proposed a gamification approach that benefits from both psychological and physiological rewards and gradually increases them. The evaluation results showed a 15% increase in the quality of the reports, a 26% increase in interaction time using the proposed method, and a 19% increase in user acquisition to lower monetary rewards. It also showed a 57% increase in commitment to participating in the survey compared with other groups. Both survey results show that around 40% of the users prefer to receive between 0.50 and 1 euro for their services. Also, women showed more quality responses and commitment in completing the participation than men.

The CNN-LSTM-attention model for short term prediction of the polar motion

Abstract The accuracy of polar motion (PM) prediction significantly impacts the fields of coordinate frame transformation, satellite orbit determination, and deep space exploration. The present study develops two short term forecasting models based on the EOP 14C04 series. One hybrid approach incorporates convolutional neural networks (CNNs) and long short-term memory networks (LSTM), augmented with an attention mechanism; whereas another baseline model comprises CNN and LSTM. The first model, in contrast to the second model, incorporates an attention mechanism module for a more comprehensive integration of temporal information at each time step. In the initial short-term forecasting experiment, we conducted 360 repeated predictions, and the findings revealed that the parameters suitable for PMX forecasting may not necessarily be applicable to PMY forecasting. In the second experiment, the two models generated a total of 500 forecasts, each encompassing short-term predictions ranging from 1 to 30 d. The experimental results demonstrate that the first model exhibits mean absolute error (MAE) range of 0–7.72 mas for PMX and 0–4.73 mas for PMY, while the second model shows MAE range of 0–7.88 mas for PMX and 0–4.78 mas for PMY. After two exploratory experiments, we discovered the following results: the first model exhibits marginally superior predictive accuracy compared to the second model. Furthermore, this study substantiates the robustness of both models in short-term prediction and affirms the significance of assigning distinct weights to past temporal intervals in forecasting, thereby offering a novel perspective for PM prediction research.

Does Momentary Outcome-Based Reflection Shape Bioethical Views? A Pre-Post Intervention Design.

Many bioliberals endorse broadly consequentialist frameworks in normative ethics, implying that a progressive stance on matters of bioethical controversy could stem from outcome-based reasoning. This raises an intriguing empirical prediction: encouraging outcome-based reflection could yield a shift toward bioliberal views among nonexperts as well. To evaluate this hypothesis, we identified empirical premises that underlie moral disagreements on seven divisive issues (e.g., vaccines, abortion, or genetically modified organisms). In exploratory and confirmatory experiments, we assessed whether people spontaneously engage in outcome-based reasoning by asking how their moral views change after momentarily reflecting on the underlying empirical questions. Our findings indicate that momentary reflection had no overall treatment effect on the central tendency or the dispersion in moral attitudes when compared to prereflection measures collected 1 week prior. Autoregressive models provided evidence that participants engaged in consequentialist moral reasoning, but this self-guided reflection produced neither moral "progress" (shifts in the distributions' central tendency) nor moral "consensus" (reductions in their dispersion). These results imply that flexibility in people's search for empirical answers may limit the potential for outcome-based reflection to foster moral consensus.

Rastermap: a discovery method for neural population recordings.

Neurophysiology has long progressed through exploratory experiments and chance discoveries. Anecdotes abound of researchers listening to spikes in real time and noticing patterns of activity related to ongoing stimuli or behaviors. With the advent of large-scale recordings, such close observation of data has become difficult. To find patterns in large-scale neural data, we developed 'Rastermap', a visualization method that displays neurons as a raster plot after sorting them along a one-dimensional axis based on their activity patterns. We benchmarked Rastermap on realistic simulations and then used it to explore recordings of tens of thousands of neurons from mouse cortex during spontaneous, stimulus-evoked and task-evoked epochs. We also applied Rastermap to whole-brain zebrafish recordings; to wide-field imaging data; to electrophysiological recordings in rat hippocampus, monkey frontal cortex and various cortical and subcortical regions in mice; and to artificial neural networks. Finally, we illustrate high-dimensional scenarios where Rastermap and similar algorithms cannot be used effectively.

Feasibility of a 1,3-propanediol biorefinery from glycerol using a Clostridium butyricum wild-type strain and its in-silico knockout mutants: A genome-scale metabolic model integration

Advances in computational tools have enabled the development of genome-scale metabolic (GSM) models. Integrating GSM models with downstream processes through multi-scale models allows predicting biorefinery feasibility. This study utilizes the GSM model iCbu641 to predict the use of the wild-type strain Clostridium butyricum IBUN 158B for producing 1,3-propanediol (PDO) from Colombian biodiesel-derived glycerol. Different bioreactor and evaporation trains were evaluated, with the selected biorefinery comprising a fed-batch bioreactor and double-effect evaporation trains. Economic evaluation indicates the selected biorefinery has a payout period of 7.4 years and a production cost of around 1 US$/kg, indicating feasibility. Five additional biorefineries were assessed using in-silico knockout mutants blocking competing co-products. Simulations revealed that blocking hydrogen production could reduce unit costs and payout periods by up to 15 %, suggesting its potential in a PDO biorefinery. Concluding, the novelty of this study is the holistic integration of biological and economic assessments, reducing resources in exploratory experiments.

Investigating Internal Heat Exchanger Performance in a VCR System with a CO2 and LPG Refrigerant Mixture

In this study, an attempt was made to develop a cooling system with an internal heat exchanger using a mixture of carbon dioxide (CO2) and liquefied petroleum gas (LPG) as refrigerants to help eliminate the global warming potential and other harmful environmental effects caused by conventional refrigerants'. The CO2 and LPG refrigeration experimental setup was constructed with varying sizes of capillary tubes, a pressure controller, an evaporator, and a gas hob. The working ranges were initially confirmed through exploratory experiments with low-pressure and high-pressure flow circuits, using and without an internal heat exchanger (IHE). The evaporator temperature helped to determine the proportional changes in the coefficient of performance (COP). The REFPROP software design was used to conduct experiments and determine the important process parameters. A confirmation test was performed to validate the expected results of the REFPROP software technique. The results showed that the experiments conducted using IHE had a COP with greater performance levels as follows: mean of 1.398 and SD of 0.367 which is greater than the value of the experiments undertaken without IHE which had a COP performance levels as follows: mean of 0.67 and SD of 0.19. The Paired Samples T-test found these differences to be significant, at p-value < 0.033. The null hypothesis was rejected, hence there is evidence to suggest that the COP of the experiment with IHE is statistically greater than the COP of the experiment without IHE, with a 95% confidence interval of -1.357 and -0.099

Study on Enhancement of Acid Production by Combination Fermentation of Caproic Acid-producing Bacteria and Lactic Acid-producing Bacteria

A new caproic acid bacteria 20-5 (Caproicibacterium sp.) was newly screened in the laboratory, and several high-quality lactic acid bacteria A2-3 ( Sporolactobacillus fermentans ), GCB-3 ( Pediococcus acidilactici ), KR-4 ( Lactiplantibacillus plantarum ), LY-5 ( Levilactobacillus brevis ), B2-1 ( Lactiplantibacillus plantarum ) were used for exploratory compound fermentation experiments. The compound fermentation was a caproic acid bacteria (20-5) alone plus four lactic acid bacteria ( A2-3, GCB-3, KR-4, LY-5, B2-1 ), the experimental ratio was set up four groups of compound ratio of 1 : 2,1 : 1,5 : 1,10 : 1. The optimum ratio of 20-5 to B2-1 was 10 : 1, and the total acid yield reached 26.75 g / L. The best caproic acid production capacity after compounding was the 10: 1 group of 20-5 and B2-1, and the caproic acid yield was 7.22 g / L. The average lactic acid content in the fermentation broth was 4.52 g / L after compounding. After compounding, the acid production of the 1 : 1 and 5 : 1 groups of 20-5 : A2-3 and the 10 : 1 group of 20-5 : B2-1 increased compared with that of single bacteria. In the other compound groups, the acid production capacity decreased after the compound operation, and the lactic acid production generally decreased, but the caproic acid production increased, indicating that caproic acid bacteria can use lactic acid as a carbon source for fermentation and acid production activities, so that caproic acid bacteria can produce caproic acid.

Tungsten sulfide highly boosted Fe(III)/peroxymonosulfate system for rapid degradation of cyclohexanecarboxylic acid: Performance, mechanisms, and applications

In this study, the Fe(III)/WS2/peroxymonosulfate (PMS) system was found to remove up to 97% of cyclohexanecarboxylic acid (CHA) within 10 min. CHA is a model compound for naphthenic acids (NAs), which are prevalent in petroleum industrial wastewater. The addition of WS2 effectively activated the Fe(III)/PMS system, significantly enhancing its ability to produce reactive oxidative species (ROS) for the oxidation of CHA. Further experimental results and characterization analyses demonstrated that the metallic element W(IV) in WS2 could provide electrons for the direct reduction of Fe(III) to Fe(II), thus rapidly activating PMS and initiating a chain redox process to produce ROS (SO4•−, •OH, and 1O2). Repeated tests and practical exploratory experiments indicated that WS2 exhibited excellent catalytic performance, reusability and anti-interference capacity, achieving efficient degradation of commercial NAs mixtures. Therefore, applying WS2 to catalyze the Fe(III)/PMS system can overcome speed limitations and facilitate simple, economical engineering applications.

Laboratory simulations of ice growth in space: An expected nonuniform ice mantle composition

Context. In dense, cold molecular regions, gas-phase chemical species freeze out onto grain surfaces. These icy condensates become an important reservoir of volatile elements and feedstock for molecular diversity. Aims. While there is a fairly general agreement on the chemical composition of icy mantles, there are differences in how the various molecular components are perceived to be present. Should the materials composing the ice be mixed or are they segregated into distinct chemical zones? Methods. To answer such a question, we performed a few exploratory experiments that allowed the adsorbing surface (mimic dust grains) to slowly relax to very low temperatures while gas-phase mixtures of H2O, NH3, and CO embed onto it. Results. We find that mantles are far from being uniform, and they could evolve into completely mixed ices only if the ambient temperature undergoes a catastrophic collapse. Conclusions. Under the typical conditions of an interstellar dense cloud, ices present a high degree of molecular segregation, with possible consequences on the ice chemistry and the desorption mechanisms.

A photothermal colorimetric dual-signal sensor for Staphylococcus aureus in food based on CuS nanoparticles

Staphylococcus aureus (S. aureus) is a common foodborne pathogenic organism, and rapid detection with high sensitivity and targeted killing are essential for controlling its spread. Therefore, a sandwich structure of magnetic bead-target bacteria-copper sulfide was constructed in this paper. The photothermal conversion function and peroxidase (POD) activity of CuS NPs were utilized to establish a dual sensing platform for temperature and color rendering, that is, after capturing target bacteria, light was converted to heat signal by infrared irradiation. Moreover, the specific detection of S. aureus was realized by detecting the temperature change of the complex and the oxidation of TMB by nano-enzymes of residual CuS in the supernatant to form oxTMB blue product, which formed the change of UV (ultraviolet) − Visible spectroscopy. Based on the high specificity binding and strong signal amplification of the method, the linear range of the photothermal specific probe combined with MBs-S. aureus-CuS was 10–106 CFU/mL, and the detection limit was 1.407 CFU/mL. The linear range of the color specific probe was 10–106 CFU/mL, R2 = 0.9853, and the detection limit was 1.15 CFU/mL. The photothermal efficiency of MBs-S. aureus-CuS system can reach 62.84 %, which has excellent photothermal conversion effect, and the temperature rises to about 70 °C within 7 min, which can directly kill bacteria in the detection. In addition, the portable infrared thermal imager is applied to realize the real-time field detection of S. aureus. The study was significant, because exploratory experiments were conducted to conceive a proof-of-concept based on multiple bacterial sensors that could easily be adapted to a variety of fields where bacteria pose a threat.

ТЕОРЕТИЧЕСКОЕ ОБОСНОВАНИЕ ЧАСТОТЫ ВРАЩЕНИЯ ЛОПАСТНОГО ПОГРУЗЧИКА В ЦИРКУЛЯЦИОННОМ СМЕСИТЕЛЕ

The purpose of the research is to substantiate the critical rotation speed of the working body based on force analysis and modeling of the movement of particles of a bulk product in a horizontal loader with radial blades located in a circulation mixer. The research methodology involved substantiating the maximum rotation speed of the loader working body based on an analysis of the forces acting on particles as they move by the loader blades and fall into the tray during flight. Based on the obtained expressions, the values of the indicators were modeled to analyze and substantiate rational values. The implementation of a numerical analysis of the obtained expressions based on force analysis and process modeling with the Mathcad mathematical package made it possible to identify the critical values of the rotation speed of the working body of a paddle loader based on the condition for the possibility of material coming off the blade and the condition for the possibility of particles flying from the blade into the receiving tray. Due to the need for material to flow off the blades and the rotation speed reduction factor of 0.9, the rotation speed of a blade loader with an outer diameter of blades of 0.24 m and an inner diameter of 0.17 m should not exceed 77 min-1 . The highest rotation speed of the working body shaft at which particles of material will enter the receiving tray area from the outer end of the blade is 43 min-1 , and from the inner end - 73 min-1 . In the process of manufacturing a circulating mixer with a radial blade loader for experimental studies, it should be possible to change the rotation speed up to 43 min-1 . To test theoretical principles in exploratory experiments, it is necessary to provide for the possibility of changing the rotation speed of the blade loader shaft to 70 min-1 .

Tribological Performance Study of Low-Friction PEEK Composites under Different Lubrication Conditions

This study introduces a low-friction composite based on PEEK to improve its friction and wear properties. The composite incorporates PTFE as a solid lubricant and utilizes PPTA as a reinforcing material within the PEEK matrix. These components were prepared utilizing a compression molding method, followed by a series of exploratory experiments to identify the optimal preparation conditions for PEEK. This research assesses how the PTFE/PPTA/PEEK composites perform in terms of friction and wear under dry and oil-lubricated conditions. By examining wear tracks using scanning electron microscopy and white light interference microscopy, this study aims to uncover the wear mechanisms of PEEK and its composites under different lubrication scenarios. Results show that the main wear mechanisms for the PTFE/PPTA/PEEK composites and bearing steel are ploughing and adhesive wear. The presence of PPTA helps reduce wear by leveraging its strong fibers and thermal stability, while the coefficient of friction decreases as PTFE creates a smooth, solid lubricating film on the surface. Notably, PEEK composites containing 25 wt% PTFE and 6 wt% PPTA demonstrate the lowest wear rates and reduced coefficient of friction in both dry and oil-lubricated conditions.

Improving the Classification of Unexposed Potsherd Cavities by Means of Preprocessing

The preparation of raw images for subsequent analysis, known as image preprocessing, is a crucial step that can boost the performance of an image classification model. Although deep learning has succeeded in image classification without handcrafted features, certain studies underscore the continued significance of image preprocessing for enhanced performance during the training process. Nonetheless, this task is often demanding and requires high-quality images to effectively train a classification model. The quality of training images, along with other factors, impacts the classification model’s performance and insufficient image quality can lead to suboptimal classification performance. On the other hand, achieving high-quality training images requires effective image preprocessing techniques. In this study, we perform exploratory experiments aimed at improving a classification model of unexposed potsherd cavities images via image preprocessing pipelines. These pipelines are evaluated on two distinct image sets: a laboratory-made, experimental image set that contains archaeological images with controlled lighting and background conditions, and a Jōmon–Yayoi image set that contains images of real-world potteries from the Jōmon period through the Yayoi period with varying conditions. The best accuracy performances obtained on the experimental images and the more challenging Jōmon–Yayoi images are 90.48% and 78.13%, respectively. The comprehensive analysis and experimentation conducted in this study demonstrate a noteworthy enhancement in performance metrics compared to the established baseline benchmark.

Prototyping of compliant grippers using FFF and TPU

PurposeThe purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.Design/methodology/approachAfter reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.FindingsThe research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.Research limitations/implicationsThe cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.Originality/valueThis paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.

On the reproducibility of electron-beam lithographic fabrication of photonic nanostructures.

Photonic nanostructures such as gratings and ring resonators have become ubiquitous building blocks in Photonics. For example, they are used in filters, they resonantly enhance signals and act as grating couplers. Much research effort is invested in using such structures to create novel functionalities, which often employs electron-beam lithography. An intrinsic issue in this field is the ability to accurately achieve a specific operating wavelength, especially for resonant systems, because nanometer-scale variations in feature size may easily detune the device. Here, we examine some of the key fabrication steps and show how to improve the reproducibility of fabricating wavelength scale photonic nanostructures. We use guided mode resonance grating sensors as our exemplar and find that the exposure condition and the development process significantly affect the consistency of the resonance wavelength, amplitude, and sensitivity of the sensor. By having careful control over these factors, we can achieve consistent performance for all the sensors studied, with less than 10% variation in their resonance behaviors. These investigations provide useful guidelines for fabricating nanostructures more reliably and to achieve a higher success rate in exploratory experiments.

Theoretical Study and Virtual Screening of Nitrogen‐Containing Corrosion Inhibitors Based on Quantitative Structure–Activity Relationship

AbstractNitrogen‐containing corrosion inhibitors have a wide range of promising applications, and current conventional corrosion design and evaluation methods are largely based on empirical speculation and extensive exploratory experiments. Unfortunately, these efforts are often associated with high costs, long lead times, and a lot of “blind work.” In this work, we have computationally screened the quantum chemical parameters of five nitrogen‐containing corrosion inhibitor molecules and their corrosion inhibition properties by a molecular simulation method based on density functional theory calculations. The ultimate relationship between the corrosion inhibition efficiency (IE) of an adsorbent and its quantum chemical parameters was analyzed using linear regression by comparing the various quantum mechanical parameters of each inhibitor molecule, as well as the fraction of electrons (ΔN) that are transferred to the metal surface from the chemisorbed inhibitor molecule. Five different nitrogen‐containing corrosion inhibitor molecules were screened based on structural similarity. Meanwhile, their corrosion inhibition performance was evaluated using the most relevant structure–activity equations. The results showed that the synergistic effect between the corrosion inhibition performance and the orbital energies of highest occupied molecular orbital and lowest unoccupied molecular orbital was optimal under the HF/6‐31G(d) method, and the corresponding structure–activity relationship was established. Based on these results, a specific inhibitor molecule was found to have excellent corrosion inhibition performance with a predicted corrosion IE of up to 94.12 %.

How to Arrange Texts and Pictures for Online Visitors — Comparing Basic Ceramic Display Forms with Eye Tracking

In the context of online text–picture relic exhibitions, two exploratory experiments were conducted to investigate the role of integrated/separate display, background information, and annotation type in learning tangible heritage. Using ceramics as an example, we tracked the eye movement of subjects under different display forms and tested whether they obtained the relevant information. Experiment 1 (N = 48) adopted a 2 (integrated/separate display) × 2 (with/without background information) design and Experiment 2 (N = 93) investigated distinct types of annotation (no annotation, indicative/direct/picture/contour shape annotation). We found that the following. (1) In the segmented relic display, the usage time, fixation count, and total fixation duration of relic names were lower than those in the integrated case. The probability that subjects would learn comparatively was also lower in the separate display. However, the performance on retention or transfer tests did not differ depending on the integrated/separate display. After reading the background information, subjects paid less attention to relic names but had better knowledge transfer performance. (2) The viewers’ attention allocation to the materials was not significantly influenced by the annotations. Mere visual annotations did not provide an advantage for information acquisition. By contrast, indicative verbal annotation required relatively more time for better target information memory, and the direct verbal cue consumed the least time. Based on the results, we discussed the application scenario of multimedia learning principles and potential recommendations for designing online relic displays.

Towards Continual Knowledge Graph Embedding via Incremental Distillation

Traditional knowledge graph embedding (KGE) methods typically require preserving the entire knowledge graph (KG) with significant training costs when new knowledge emerges. To address this issue, the continual knowledge graph embedding (CKGE) task has been proposed to train the KGE model by learning emerging knowledge efficiently while simultaneously preserving decent old knowledge. However, the explicit graph structure in KGs, which is critical for the above goal, has been heavily ignored by existing CKGE methods. On the one hand, existing methods usually learn new triples in a random order, destroying the inner structure of new KGs. On the other hand, old triples are preserved with equal priority, failing to alleviate catastrophic forgetting effectively. In this paper, we propose a competitive method for CKGE based on incremental distillation (IncDE), which considers the full use of the explicit graph structure in KGs. First, to optimize the learning order, we introduce a hierarchical strategy, ranking new triples for layer-by-layer learning. By employing the inter- and intra-hierarchical orders together, new triples are grouped into layers based on the graph structure features. Secondly, to preserve the old knowledge effectively, we devise a novel incremental distillation mechanism, which facilitates the seamless transfer of entity representations from the previous layer to the next one, promoting old knowledge preservation. Finally, we adopt a two-stage training paradigm to avoid the over-corruption of old knowledge influenced by under-trained new knowledge. Experimental results demonstrate the superiority of IncDE over state-of-the-art baselines. Notably, the incremental distillation mechanism contributes to improvements of 0.2%-6.5% in the mean reciprocal rank (MRR) score. More exploratory experiments validate the effectiveness of IncDE in proficiently learning new knowledge while preserving old knowledge across all time steps.

Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective

Graph contrastive learning is a general learning paradigm excelling at capturing invariant information from diverse perturbations in graphs. Recent works focus on exploring the structural rationale from graphs, thereby increasing the discriminability of the invariant information. However, such methods may incur in the mis-learning of graph models towards the interpretability of graphs, and thus the learned noisy and task-agnostic information interferes with the prediction of graphs. To this end, with the purpose of exploring the intrinsic rationale of graphs, we accordingly propose to capture the dimensional rationale from graphs, which has not received sufficient attention in the literature. The conducted exploratory experiments attest to the feasibility of the aforementioned roadmap. To elucidate the innate mechanism behind the performance improvement arising from the dimensional rationale, we rethink the dimensional rationale in graph contrastive learning from a causal perspective and further formalize the causality among the variables in the pre-training stage to build the corresponding structural causal model. On the basis of the understanding of the structural causal model, we propose the dimensional rationale-aware graph contrastive learning approach, which introduces a learnable dimensional rationale acquiring network and a redundancy reduction constraint. The learnable dimensional rationale acquiring network is updated by leveraging a bi-level meta-learning technique, and the redundancy reduction constraint disentangles the redundant features through a decorrelation process during learning. Empirically, compared with state-of-the-art methods, our method can yield significant performance boosts on various benchmarks with respect to discriminability and transferability. The code implementation of our method is available at https://github.com/ByronJi/DRGCL.