Establishing the relationship between subjective perception and neural responses: Insights from correlation analysis and representational similarity analysis.

Exploring the relationship between sensory perception and brain responses holds important theoretical and clinical implications. However, commonly used methodologies like correlation analysis performed either intra- or inter- individually often yield inconsistent results across studies, limiting their generalizability. Representational similarity analysis (RSA), a method that assesses the perception-response relationship by calculating the correlation between behavioral and neural patterns, may offer a fresh perspective to reveal novel findings. Here, we delivered a series of graded sensory stimuli of four modalities (i.e., nociceptive somatosensory, non-nociceptive somatosensory, visual, and auditory) to/near the left or right hand of 107 healthy subjects and collected their single-trial perceptual ratings and electroencephalographic (EEG) responses. We examined the relationship between sensory perception and brain responses using within- and between-subject correlation analysis and RSA, and assessed their stability across different numbers of subjects and trials. We found that within-subject and between-subject correlations yielded distinct results: within-subject correlation revealed strong and reliable correlations between perceptual ratings and most brain responses, while between-subject correlation showed weak correlations that were vulnerable to the change of subject number. In addition to verifying the correlation results, RSA revealed some novel findings, i.e., correlations between behavioral and neural patterns were observed in some additional neural responses, such as "γ-ERS" in the visual modality. RSA results were sensitive to the trial number, but not to the subject number, suggesting that consistent results could be obtained for studies with relatively small sample sizes. In conclusion, our study provides a novel perspective on establishing the relationship between behavior and brain activity, emphasizing that RSA holds promise as a method for exploring this pattern relationship in future research.

Structure-Guided Evolution of Cyclohexanone Monooxygenase Toward Bulky Omeprazole Sulfide: Substrate Migration and Stereoselectivity Inversion.

Structure-guided engineering of a CHMO from Amycolatopsis methanolica (AmCHMO) was performed for asymmetric sulfoxidation activity and stereoselectivity toward omeprazole sulfide. Initially, combinatorial active-site saturation test (CASTing) and iteratively saturation mutagenesis (ISM) were performed on 5 residues at the "bottleneck" of substrate tunnel, and MT3 was successfully obtained with a specific activity of 46.19 U/g and R-stereoselectivity of 99 % toward OPS. Then, 4 key mutations affecting the stereoselectivity were identified through multiple rounds of ISM on residues at the substrate binding pocket region, resulting MT8 with an inversed stereoselectivity from 99 % (R) to 97 % (S). MT8 has a greatly compromised specific activity of 0.08 U/g. By introducing additional beneficial mutations, MT11 was constructed with significantly increased specific activity of 2.29 U/g and stereoselectivity of 97 % (S). Enlarged substrate tunnel is critical to the expanded substrate spectrum of AmCHMO, while reshaping of substrate binding pocket is important for stereoselective inversion. Based on MD simulation, pre-reaction states of MT3-OPSproR, MT8-OPSproS, and MT11-OPSproS were calculated to be 45.56 %, 17.94 %, and 28.65 % respectively, which further confirm the experimental data on activity and stereoselectivity. Our results pave the way for engineering distinct activity and stereoselectivity of BVMOs toward bulky prazole thioethers.

Nanowire Array Breath Acetone Sensor for Diabetes Monitoring.

Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes characterized by the accumulation of ketone bodies in the blood. Breath acetone, a ketone, directly correlates with blood ketones. Therefore, monitoring breath acetone can significantly enhance the safety and efficacy of diabetes care. In this work, the design and fabrication of an InP/Pt/chitosan nanowire array-based chemiresistive acetone sensor is reported. By incorporation of chitosan as a surface-functional layer and a Pt Schottky contact for efficient charge transfer processes and photovoltaic effect, self-powered, highly selective acetone sensing is achieved. The sensor has exhibited an ultra-wide acetone detection range from sub-ppb to >100 000 ppm level at room temperature, covering those in the exhaled breath from healthy individuals (300-800 ppb) to people at high risk of DKA (>75 ppm). The nanowire sensor has also been successfully integrated into a handheld breath testing prototype, the Ketowhistle, which can successfully detect different ranges of acetone concentrations in simulated breath samples. The Ketowhistle demonstrates the immediate potential for non-invasive ketone monitoring for people living with diabetes, in particular for DKA prevention.

Recent developments on the removal of zinc from electric arc furnace dust by using microwave heating.

Electric arc furnace dust (EAFD) is a hazardous by-product of steel production. As global steel output increases, substantial amounts of EAFD are produced, which causes significant environmental issues. EAFD contains quantities of Fe and Zn, which could be reused as raw materials in the steelmaking process. However, zinc oxides can be reduced and vaporized during this process, forming zinc vapor that contaminates equipment surfaces and causes damage. Consequently, various pyrometallurgical methods have been proposed for zinc removal from EAFD. Due to the extensive usage of carbonaceous materials, these methods contribute to significant CO2, raising concerns about greenhouse gas emissions. Microwave heating offers an efficient, energy-saving, and environmentally friendly alternative to pyrometallurgical approaches. EAFD can generate heat under microwave irradiation without carbon addition, which means the CO2 emissions can be reduced by replacing the reductant in the microwave heating process. Furthermore, microwaves enhance zinc removal reactions to a certain extent, resulting in higher efficiency. Thus, employing microwave heating for EAFD processing has significant potential for future development. This paper reviews recent research on using microwave heating for zinc removal from EAFD, focusing on the heating behavior of EAFD in microwaves and the mechanisms of zinc removal. This review will be crucial for researchers working on processing EAFD using microwave heating and could help guide the development of more sustainable and efficient methods.

Response of soil CO2 emissions and water-carbon use efficiency of winter wheat to different straw returning methods and irrigation scenarios.

BACKGROUND: The shortage of water resources and the increase of greenhouse gas emissions from soil seriously restrict the sustainable development of agriculture. Under the premise of ensuring a stable yield of winter wheat through a reasonable irrigation scenario, identifying a suitable straw returning method will have a positive effect on agricultural carbon sequestration and emission reduction in North China Plain. RESULTS: Straw burying (SR) and straw mulching (SM) were adopted based on traditional tillage under in the winter wheat growing season of 2020-2021 and 2021-2022. Three irrigation scenarios were used for each straw returning method: no irrigation (I0), irrigation 60 mm at jointing stage (I1), and irrigation of 60 mm each at the jointing and heading stages (I2). Soil moisture, soil respiration rate, cumulative soil CO2 emissions, yield, water use efficiency (WUE) and soil CO2 emission efficiency (CEE) were mainly studied. The results showed that, compared to SM, SR improved the utilization of soil water and enhanced soil carbon sequestration. SR reduced soil respiration rate and cumulative soil CO2 emissions in two winter wheat growing seasons, and increased yield by increasing spike numbers. In addition, with an increase in the amount of irrigation, soil CO2 emissions and yield increased. Under SR-I1 treatment, WUE and CEE were the highest. SR-I1 increases crop yields at the same time as reducing soil CO2 emissions. CONCLUSION: The combination of SR and irrigation 60 mm at jointing stage is a suitable straw returning irrigation scenario, which can improve water use and reduce soil CO2 emission in NCP. © 2023 Society of Chemical Industry.

Application of adaptive laboratory evolution to improve the tolerance of Rhodotorula strain to methanol in crude glycerol and development of an effective method for cell lysis.

Rhodotorula toruloides can utilize crude glycerol as the low-cost carbon source for lipid production, but its growth is subjected to inhibition by methanol in crude glycerol. Here, transcriptome profiling demonstrated that 1004 genes were significantly regulated in the strain R. toruloides TO2 under methanol stress. Methanol impaired the function of membrane transport and subsequently weakened the utilization of glycerol, activities of the primary metabolism and functions of nucleus and ribosome. Afterwards the tolerance of TO2 to methanol was improved by using two-round adaptive laboratory evolution (ALE). The final strain M2-ale had tolerance up to 3.5% of methanol. 1 H NMR-based metabolome analysis indicated that ALE not only improved the tolerance of M2-ale to methanol but also tuned the carbon flux towards the biosynthesis of glycerolipid-related metabolites. The biomass and lipid titer of M2-ale reached 14.63 ± 0.45 g L-1 and 7.06 ± 0.44 g L-1 at 96 h in the crude glycerol medium, which increased up to 17.69% and 31.39%, respectively, comparing with TO2. Afterwards, an effective method for cell lysis was developed by combining sonication and enzymatic hydrolysis (So-EnH). The lytic effect of So-EnH was validated by using confocal imaging and flow cytometry. At last, lipid recovery rate reached 95.4 ± 2.7% at the optimized condition.

High performance of membrane capacitive deionization with ZnS/g-C3N4 composite electrodes.

Capacitive deionization (CDI) is considered a promising technology for desalination of sea or brackish water. In this study, a ZnS/g-C3N4 composite was synthesized through a one-step high-temperature method and used as the main material to fabricate CDI electrodes. The results of SEM and TEM showed that spherical-like nanoparticles of ZnS were uniformly distributed on the g-C3N4 sheet. The g-C3N4 phase facilitates the ZnS particles precipitate and restrain their agglomeration, which contributes to a high specific surface area of ZnS. Furthermore, the electrochemical test results indicated that ZnS/g-C3N4 composite had a good capacitance characteristic, low resistance, and high electrochemical stability. Finally, the desalinization performance of the ZnS/g-C3N4 composite electrodes was tested in traditional mode and membrane capacitive deionization (MCDI) mode. The results showed that ZnS/g-C3N4//ZnS/g-C3N4 (MCDI) exhibited an optimal desalination capacity. The adsorption amount was 27.65, 50.26, and 65.34 mg/g for NaCl initial concentration of 200, 400, and 600 mg/L, respectively, with the voltage of 1.2 V and flow rate of 5 mL/min. Increasing initial concentration enhanced the conductivity and ion migration rate so as to increase the NaCl adsorption amount. ZnS/g-C3N4 composite can be used as potential electrode material for high performance of MCDI.

Enhancing pain modulation: the efficacy of synchronous combination of virtual reality and transcutaneous electrical nerve stimulation.

Introduction: Virtual reality (VR) and transcutaneous electrical nerve stimulation (TENS) have emerged as effective interventions for pain reduction. However, their standalone applications often yield limited analgesic effects, particularly in certain painful conditions. Aims: Our hypothesis was that the combination of VR with TENS in a synchronous manner could produce the best analgesic effect among the four experimental conditions. Methods: To address this challenge, we proposed a novel pain modulation strategy that synchronously combines VR and TENS, aiming to capitalise on both techniques' complementary pain modulation mechanisms. Thirty-two healthy subjects participated in the study and underwent three types of interventions: VR alone, a combination of VR with conventional TENS, and a combination of VR with synchronous TENS. Additionally, a control condition with no intervention was included. Perceived pain intensity, pain unpleasantness, positive and negative affect scores, and electroencephalographic (EEG) data were collected before and after the interventions. To delve into the potential moderating role of pain intensity on the analgesic efficacy of VR combined with synchronous TENS, we incorporated two distinct levels of painful stimuli: one representing mild to moderate pain (ie, low pain) and the other representing moderate to severe pain (ie, high pain). Results: Our findings revealed that both combination interventions exhibited superior analgesic effects compared with the VR-alone intervention when exposed to low and high pain stimuli. Notably, the combination of VR with synchronous TENS demonstrated greater analgesic efficacy than the combination of VR with conventional TENS. EEG data further supported these results, indicating that both combination interventions elicited a greater reduction in event-related potential magnitude compared with the VR-alone intervention during exposure to low and high pain stimuli. Moreover, the synchronous combination intervention induced a more significant reduction in N2 amplitude than the VR-alone intervention during exposure to low pain stimuli. No significant differences in EEG response changes were detected between the two combination interventions. Both combination interventions resulted in a greater reduction in negative affect compared with the VR-alone intervention. Conclusions: Altogether, our study highlights the effectiveness of the synchronous combination of VR and TENS in enhancing pain modulation. These findings offer valuable insights for developing innovative pain treatments, emphasising the importance of tailored and multifaceted therapeutic approaches for various painful conditions.

Microstructure evolution of medium carbon steel during heat-assisted 3D ultrasonic vibration-assisted turning.

Medium carbon steel is an excellent carbon structural steel, and is one of the most common materials for metal cutting. Little research has been done on the microstructural changes induced by thermal-force coupling. In this paper, a finite element simulation method based on the improved J-C model is used to predict the grain size, microstructure change depth and surface hardness of medium carbon steel surface induced by heat-assisted 3D-UVAT are studied. The numerical simulation results are compared with the experimental results, and the significant influence of turning conditions on them is analyzed. The results show that heat-assisted 3D-UVAT lowered the grain size of machined induced deformation zone. Numerical model foresees this case with a mean error of 9.4%. Microstructure and hardness measurements under different turning conditions show that the turning speed and feed rate contribute significantly to grain size and grain refinement layer depth in the area being machined.

Greed personality trait links to negative psychopathology and underlying neural substrates.

Greed personality trait (GPT), characterized by the desire to acquire more and the dissatisfaction of never having enough, has been hypothesized to link with negative emotion/affect characteristics and aggressive behaviors. To describe its emotion-related features, we utilized a series of scales to measure corresponding emotion/affect and aggression (n = 411) and collected their neuroimaging data (n = 330) to explore underlying morphological substrates. Correlational analyses revealed that greedy individuals show more negative symptoms (e.g. depression, loss of interest, negative affect), lower psychological well-being and more aggression. Mediation analyses further demonstrated that negative symptoms and psychological well-being mediated greedy individuals' aggression. Moreover, exploratory factor analysis extracted factor scores across three factors (negative psychopathology, happiness, and motivation) from the measures scales. Negative psychopathology and happiness remained robust mediators. Importantly, these findings were replicated in an independent sample (n = 68). Voxel-based morphometry analysis also revealed that gray matter volumes (GMVs) in the prefrontal-parietal-occipital system were associated with negative psychopathology and happiness, and GMVs in the frontal pole and middle frontal cortex mediated the relationships between GPT and aggressions. These findings provide novel insights into the negative characteristics of dispositional greed, and suggest their mediating roles on greedy individuals' aggression and underlying neuroanatomical substrates.

A Self-Powered Portable Nanowire Array Gas Sensor for Dynamic NO2 Monitoring at Room Temperature.

The fast development of the Internet of Things (IoT) has driven an increasing consumer demand for self-powered gas sensors for real-time data collection and autonomous responses in industries such as environmental monitoring, workplace safety, smart cities, and personal healthcare. Despite intensive research and rapid progress in the field, most reported self-powered devices, specifically NO2 sensors for air pollution monitoring, have limited sensitivity, selectivity, and scalability. Here, a novel photovoltaic self-powered NO2 sensor is demonstrated based on axial p-i-n homojunction InP nanowire (NW) arrays, that overcome these limitations. The optimized innovative InP NW array device is designed by numerical simulation for insights into sensing mechanisms and performance enhancement. Without a power source, this InP NW sensor achieves an 84% sensing response to 1 ppm NO2 and records a limit of detection down to the sub-ppb level, with little dependence on the incident light intensity, even under <5% of 1 sun illumination. Based on this great environmental fidelity, the sensor is integrated into a commercial microchip interface to evaluate its performance in the context of dynamic environmental monitoring of motor vehicle exhaust. The results show that compound semiconductor nanowires can form promising self-powered sensing platforms suitable for future mega-scale IoT systems.

Neurobiological substrates of the dread of future losses.

When anticipating future losses, people respond by exhibiting 1 of 2 starkly distinct behavioral decision patterns: the dread of future losses (DFL) and the preference of future losses (vs. immediate losses). Yet, how to accurately discriminate between those who exhibit dread vs. preference and uncover the potential neurobiological substrates underlying these 2 groups remain understudied. To address this, we designed a novel experimental task in which the DFL group was defined as selecting immediate-loss options >50% in the trials with approximate subjective value in immediate and delayed options (n = 16), otherwise coding as the preference of future losses (PFL). At the behavioral level, DFL exhibited higher weight for delayed losses than immediate losses via the logistic regression model. At the neural level, DFL manifested hypoactivations on subjective valuations of delayed losses, atypical brain pattern when choosing immediate-loss options, and decreased functional coupling between the valuation and choice-systems when making decisions related to immediate-loss alternatives compared with PFL. Moreover, both these brain activations subserving distinct decision processes and their interactions predicted individual decisions and behavioral preferences. Furthermore, morphological analysis also revealed decreased right precuneus volume in DFL compared with PFL, and brain activations related to valuation and choice process mediated the associations between this region volume and behavioral performances. Taken together, these findings help to clarify potential cognitive and neural mechanisms underlying the DFL and provide a clear discrimination strategy.

Engineering of a Baeyer-Villiger monooxygenase reveals key residues for the asymmetric oxidation of omeprazole sulfide.

The structure-guided engineering of a BVMO from Rhodococcus aetherivorans (RaBVMO) was performed for its asymmetric sulfoxidation activity toward omeprazole sulfide. Based on the structural model of RaBVMO, key residues that line the substrate entrance tunnel and the binding pocket were identified, and variants were interrogated with sulfides of varied sizes. The best mutant MT2 (F442A/R337P) was obtained with a specific activity of 2.54 U g-1 and excellent enantioselectivity (≥99%, S) toward omeprazole sulfide, while wild-type RaBVMO exhibited no activity. Further structural analysis reveals that both mutations, F442A and R337P, could render an expanded substrate tunnel and an enlarged substrate binding pocket to enable easier access to the catalytic center for omeprazole sulfide. This work provides valuable guidance for engineering-related BVMOs for improved activity and enantio-preference toward bulky substrates.

The medial temporal lobe structure and function support positive affect.

Positive affect (PA) is not only associated with individuals' psychological and physical health, but also their cognitive processes. However, whether medial temporal lobe (MTL) and its subfields' volume/functional connectivity can explain individual variability in PA remains understudied. We investigated the morphological (i.e., grey matter volume; GMV) and functional characteristics (i.e., resting-state functional connectivity; rsFC) of PA with a combination of univariate and multivariate pattern analyses (MVPA) using a large sample of participants (n = 321). We simultaneously collected the T1-weighted (n = 321), high-resolution MTL T2-weighted, and resting-state functional imaging data (n = 209). The MTL and its subfields' volumes, including the CA1, CA2+3, DG, and subiculum (SUB), perirhinal cortex (PRC), and parahippocampus (PHC), were extracted using an automatic segmentation of hippocampal subfields (ASHS) software. The morphological results revealed that GMVs in the prefrontal-occipital and limbic (i.e., hippocampus, amygdala, and PHC) systems were associated with variability in PA at the whole-brain level using MVPA but not univariate analysis. Linear regression results further revealed a positive association between the MTL subfields' GMV, especially for the right PRC, and PA after controlling for several covariates. PRC-seed-based rsFC analyses further revealed that its couplings with the fronto-parietal-occipital system predicted PA in both univariate and MVPA. These findings provide novel insights into the neuroanatomical and functional substrates underlying human PA trait. Findings also suggest critical contributions of the MTL and its subfield of the perirhinal cortex, but not hippocampal subfields, as well as its functional coupling with the fronto-parietal control-system on the formation of PA.

A Novel Method of Si and Si3N4 Powder Resources Recycling: Cold Bonding Briquettes.

Silicon nitride (Si3N4) and silicon powder (Si) are two kinds of harmful solid waste in industrial production. As an environmental and low-consumption method, the cold-bonding technique is a novel method to utilize the problem of powder resource cycling. In this experiment, mechanical and high-temperature properties of Si and Si3N4 briquettes were studied after cold bonding. The results are as follows: (1) The compressive strength of the Si and Si3N4 briquettes increased with the improvement of molding pressure. With the same binder (1 wt.%) and water (10 wt.%) addition, the compressive strength of the Si3N4 briquette arrived at 12,023.53 N under 40 Mpa molding pressure, which is much higher than that of the Si briquette (942.40 N). The Si particles are uneven and irregular, which leads to an intense arch bridge effect in the Si briquette and the compressive strength decrease. Compared with Si powder, the particle size and shape of Si3N4 is small, uniform, and regular. The influence of the arch bridge effect is smaller than that in the Si briquette. (2) After being treated at 1473 K for 1 h, the compressive strength of the Si briquette increased to 5049.83 N, and the compressive strength of the Si3N4 briquette had a slight change. The surface of the briquettes was contacted with oxygen and reacted to form an outer shell which mainly contains SiO2 in the high-temperature treatment. FT-IR results have shown there were no extra impurities in cold-bonded briquettes when using the organic binder. (3) The microstructure of the cross section of the Si and Si3N4 briquettes after high-temperature treatment presented that oxygen entered the briquette through the pores and continued to react with the Si and Si3N4. The outer shell of the Si briquette grew and thickened continuously with the oxygen spreading in the Si briquette. However, because of the smaller particle size and regular shape, little oxygen diffused in the Si3N4 briquette. The outer shell of the Si3N4 briquette is fairly thin, so the compressive strength did not change too much.

Neuroanatomical substrates of maximizing tendency in decision-making: a voxel-based morphometric study.

Maximizing tendency is a central decision-making concept that has increasingly drawn attention from the scientific community. It refers to individuals' predisposition to look for the best option instead of settling for something that merely passes an internal threshold of acceptability. Although this maximizing strategy intuitively increases individual benefits, it also has been linked to various negative outcomes, including decreased well-being and low life satisfaction, and it varies considerably across populations. However, the neuroanatomical characteristics underlying this heterogeneity remain poorly understood. To address this knowledge gap, a 13-item Maximization Scale and magnetic resonance imaging technique were respectively used in this study to estimate individual maximizing tendency and structural morphological information on a sample of healthy adults (n = 69). Furthermore, voxel-based morphometry (VBM) analysis was conducted to investigate the associations between gray matter volume (GMV) and maximizing tendency through univariate and multivariate pattern analysis (MVPA). Univariate analysis did not determine an association between maximizing tendency and whole-brain GMV; by contrast, MVPA revealed that maximizing tendency could be successfully predicted by the GMVs of the right inferior frontal gyrus (IFG), right insula, and right cerebellum. These findings suggest the critical role of the morphological characteristics of the cortical-subcortical circuitry in individuals' maximizing tendency.

Numerical Analysis of the Relationship between Friction Coefficient and Repose Angle of Blast Furnace Raw Materials by Discrete Element Method.

In recent years, the discrete element method (DEM) has been widely used to study the factors affecting the repose angle and calibrate particle parameters for simulations. In this paper, DEM is used to study the effects of the coefficient of rolling and static friction of pellet, sinter and coke particles on the repose angle. By comparison of the results of simulations and physical experiments, the coefficients of rolling and static friction suitable for simulation work are determined. The results demonstrate that repose angle increases with the coefficient of rolling and static friction, but the rate of increase gradually decays, when the coefficient of rolling friction exceeds 0.4 or the coefficient of static friction exceeds 0.35. The coefficient of static friction has a greater impact on the repose angle than the coefficient of rolling friction. The rougher of the base surface, the larger the repose angle of the formed particle piled. It can be concluded that appropriate coefficient of rolling and static friction for simulations can be obtained by the outlined procedure.

Sex-specific static and dynamic functional networks of sub-divisions of striatum linking to the greed personality trait.

The study of greed has been broadly investigated and discussed in the field of social sciences, including economics, political science, and psychology. However, the neural mechanisms underlying greed personality trait (GPT) have received little attention from the cognitive neuroscience field and still remain unclear. In this study, we explored the associations between GPT and static/dynamic reward circuit-specifically its sub-regions' functional networks including caudate, nucleus accumbens (NAcc), and putamen. Behavioral analyses revealed significant associations of GPT with Past-Negative and Present-Fatalistic time attitude as well as attention impulsivity. Imaging analyses revealed a significant interaction effect between sex and GPT on the static reward functional networks. In particular, GPT was positively correlated with static caudate-NAcc, caudate-cerebellum, and NAcc-parahippocampus/medial orbitofrontal cortex (PHG/mOFC) for males but negatively correlated for females. GPT was also marginally and negatively correlated with static putamen-occipital pole functional connectivities among males. Interestingly, sex difference interaction patterns were further observed in the dynamic reward functional networks. Further, dynamic reward functional networks also exhibited some specific characteristics, manifesting in more brain regions involved for greedy behaviors. These findings suggest sex-specific static and dynamic functional networks underlying human dispositional greed, and also implicate the critical contributions of reward circuit, especially for sub-circuits of reward, on greed.

Interfacial Area Transport Equation for Bubble Coalescence and Breakup: Developments and Comparisons.

Bubble coalescence and breakup play important roles in physical-chemical processes and bubbles are treated in two groups in the interfacial area transport equation (IATE). This paper presents a review of IATE for bubble coalescence and breakup to model five bubble interaction mechanisms: bubble coalescence due to random collision, bubble coalescence due to wake entrainment, bubble breakup due to turbulent impact, bubble breakup due to shearing-off, and bubble breakup due to surface instability. In bubble coalescence, bubble size, velocity and collision frequency are dominant. In bubble breakup, the influence of viscous shear, shearing-off, and surface instability are neglected, and their corresponding theory and modelling are rare in the literature. Furthermore, combining turbulent kinetic energy and inertial force together is the best choice for the bubble breakup criterion. The reviewed one-group constitutive models include the one developed by Wu et al., Ishii and Kim, Hibiki and Ishii, Yao and Morel, and Nguyen et al. To extend the IATE prediction capability beyond bubbly flow, two-group IATE is needed and its performance is strongly dependent on the channel size and geometry. Therefore, constitutive models for two-group IATE in a three-type channel (i.e., narrow confined channel, round pipe and relatively larger pipe) are summarized. Although great progress in extending the IATE beyond churn-turbulent flow to churn-annual flow was made, there are still some issues in their modelling and experiments due to the highly distorted interface measurement. Regarded as the challenges to be addressed in the further study, some limitations of IATE general applicability and the directions for future development are highlighted.

Neural representations of the amount and the delay time of reward in intertemporal decision making.

Numerous studies have examined the neural substrates of intertemporal decision-making, but few have systematically investigated separate neural representations of the two attributes of future rewards (i.e., the amount of the reward and the delay time). More importantly, no study has used the novel analytical method of representational connectivity analysis (RCA) to map the two dimensions' functional brain networks at the level of multivariate neural representations. This study independently manipulated the amount and delay time of rewards during an intertemporal decision task. Both univariate and multivariate pattern analyses showed that brain activity in the dorsomedial prefrontal cortex (DMPFC) and lateral frontal pole cortex (LFPC) was modulated by the amount of rewards, whereas brain activity in the DMPFC and dorsolateral prefrontal cortex (DLPFC) was modulated by the length of delay. Moreover, representational similarity analysis (RSA) revealed that even for the regions of the DMPFC that overlapped between the two dimensions, they manifested distinct neural activity patterns. In terms of individual differences, those with large delay discounting rates (k) showed greater DMPFC and LFPC activity as the amount of rewards increased but showed lower DMPFC and DLPFC activity as the delay time increased. Lastly, RCA suggested that the topological metrics (i.e., global and local efficiency) of the functional connectome subserving the delay time dimension inversely predicted individual discounting rate. These findings provide novel insights into neural representations of the two attributes in intertemporal decisions, and offer a new approach to construct task-based functional brain networks whose topological properties are related to impulsivity.