Optimization and analysis of battery thermal management system structure based on flat heat pipes and biomimetic fins.

As one of the key components of electric vehicles, the enhancement of the performance of the power battery is closely intertwined with an efficient Battery Thermal Management System (BTMS). In the realm of BTMS, Flat Heat Pipes (FHP) have garnered considerable attention due to their lightweight structure and excellent thermal conductivity. Thus, a BTMS configuration scheme based on FHP is proposed in this study. Utilizing orthogonal design and fuzzy grey relational analysis as the evaluation methods, coupled with numerical simulations, an investigation into the influence of four structural parameters of the novel biomimetic fins (namely, the diameter, height, spacing of protrusions, and height of cooling fins) on the temperature distribution of the battery pack is conducted. The research findings indicate that to maintain the battery within an optimal operational temperature range, the optimal dimensional parameters should be controlled at 17.5 mm, 4 mm, 13 mm, and 90 mm, respectively. Subsequent sensitivity analysis reveals that the height of the protrusions exhibits the most significant influence on the maximum temperature of the module, whereas the height of the cooling fins exerts a considerable impact on the consistency of the module temperature. The optimized maximum temperature is determined to be 36.52 °C, with a temperature difference of 2.65 °C.

First attempt to measure macroplastic fragmentation in rivers.

Direct field measurements of macroplastic fragmentation during its transport in rivers are currently unavailable, and there is no established method to perform them. Previous studies have showed that macroplastic fragmentation results in the production of harmful microplastics, and river channels can be hotspots for this process. Therefore, obtaining information about this process is crucial for quantifying the production of secondary microplastics in rivers and assessing the related risks for riverine biota and human health. Here, we propose a simple low-cost methodology for quantifying riverine macroplastic fragmentation by conducting repeated measurements of the mass of tagged macroplastic items before and after their transport in the river. As a proof-of-concept for this method, we conducted a 52-65 day experiment that allowed us to measure a median fragmentation rate of 0.044 ± 0.012 g for 1-liter PET bottles during their transport at low to medium flow in the middle mountain Skawa River in the Polish Carpathians. Using the obtained data (n = 42), we extrapolated that during low to medium flows, the median yearly mass loss of PET bottles in the study section is 0.26 ± 0.012 g/year (0.78 ± 0.036 % of bottle mass), and the median rate of bottle surface degradation is 3.13 ± 0.14 µm/year. These estimates suggest a relatively high fragmentation rate for a PET bottle in a mountain river even under low to medium flow conditions without high-energy transport. We discuss how our simple and relatively low-cost methodology can be flexibly adapted and future optimized to quantify macroplastic fragmentation in various types of rivers and their compartments, informing future mitigation efforts about the rates of formation and dispersion of secondary microplastics.

Creating a resilient pedagogy: Character strengths intervention for aspiring educators.

Teachers play a crucial role in guiding learners through life's challenges. They face educational and socio-economic shifts while striving to teach for a better future. Our study focuses on equipping future teachers, called pre-service teachers, with resilience-building resources during their teacher training program. A potential antecedent to resilience, which facilitates cognitive strategies and attentional processes, is cognitive flexibility. We first tested whether cognitive flexibility predicts resilience. Next, relying on the tenets of positive psychology, which studies resilience, we developed and tested the effectiveness of character strengths intervention in enhancing pre-service teachers' resilience and cognitive flexibility. An individual's belief in their ability to change personal resources could influence how an intervention manifests. Hence, we studied how mindset impacts the intervention's effect on cognitive flexibility and, thus, resilience. We adopted a multi-method approach, guided by Polk's theory of resilience, to test out objectives. Using a cross-sectional design, study one (n = 273) found that cognitive flexibility significantly predicted resilience. Study two (N = 193; nexp = 133, ncont = 60) was a multi-site field experiment. We found that intervention significantly enhanced resilience (experimental group M = 29.62, control group M = 28.33) and cognitive flexibility (experimental group M = 54.42, control group M = 52.01). Further, a growth mindset, was found to moderate the indirect effect of character strengths intervention on resilience via cognitive flexibility. The study contributes to theoretical and practical advancements in resilience. Taken together, the findings highlight the cognitive-affective-behavioural makeup of resilience and, importantly, the role of cognitive flexibility. The intervention can be seamlessly integrated into teacher training curricula for a resilient future.

Fractional-Order Boosted Hybrid Young's Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization.

Inspired by classical experiments that uncovered the inherent properties of light waves, Young's Double-Slit Experiment (YDSE) optimization algorithm represents a physics-driven meta-heuristic method. Its unique search mechanism and scalability have attracted much attention. However, when facing complex or high-dimensional problems, the YDSE optimizer, although striking a good balance between global and local searches, does not converge as fast as it should and is prone to fall into local optimums, thus limiting its application scope. A fractional-order boosted hybrid YDSE, called FYDSE, is proposed in this article. FYDSE employs a multi-strategy mechanism to jointly address the YDSE problems and enhance its ability to solve complex problems. First, a fractional-order strategy is introduced into the dark edge position update of FYDSE to ensure more efficient use of the search potential of a single neighborhood space while reducing the possibility of trapping in a local best. Second, piecewise chaotic mapping is constructed at the initial stage of the population to obtain better-distributed initial solutions and increase the convergence rate to the optimal position. Moreover, the low exploration space is extended by using a dynamic opposition strategy, which improves the probability of acquisition of a globally optimal solution. Finally, by introducing the vertical operator, FYDSE can better balance global exploration and local exploitation and explore new unknown areas. The numerical results show that FYDSE outperforms YDSE in 11 (91.6%) of cec2022 sets. In addition, FYDSE performs best in 8 (66.6%) among all algorithms. Compared with the 11 methods, FYDSE obtains the optimal best and average weights for the 20-bar, 24-bar, and 72-bar truss problems, which proves its efficient optimization capability for difficult optimization cases.

The Mechanisms of Cadmium Stress Mitigation by Fungal Endophytes from Maize Grains.

Maize is a crucial staple crop that ensures global food security by supplying essential nutrients. However, heavy metal (HM) contamination inhibits maize growth, reduces output, and affects food security. Some endophytic fungi (EFs) in maize seeds have the potential to enhance growth and increase dry biomass, offering a solution to mitigate the negative effect of HM contamination. Using these functional EFs could help maintain crop production and ensure food safety in HM-contaminated areas. In the present study, the diversity of EFs in corn grains from various HM-contaminated areas in China was studied through culture-dependent and culture-independent methods. We tested the plant growth-promoting (PGP) traits of several dominant culturable isolates and evaluated the growth-promoting effects of these twenty-one isolates through pot experiments. Both studies showed that HM contamination increased the diversity and richness of corn grain EFs and affected the most dominant endophytes. Nigrospora and Fusarium were the most prevalent culturable endophytes in HM-contaminated areas. Conversely, Cladosporium spp. were the most isolated endophytes in non-contaminated areas. Different from this, Saccharomycopsis and Fusarium were the dominant EFs in HM-contaminated sites, while Neofusicoccum and Sarocladium were dominant in non-contaminated sites, according to a culture-independent analysis. PGP trait tests indicated that 70% of the tested isolates (forty-two) exhibited phosphorus solubilization, IAA production, or siderophore production activity. Specifically, 90% of the tested isolates from HM-contaminated sites showed better PGP results than 45% of the isolates from non-contaminated sites. The benefit of the twenty-one isolates on host plant growth was further studied through pot experiments, which showed that all the isolates could improve host plant growth. Among them, strains derived from HM-contaminated sites, including AK18 (Nigrospora), AK32 (Beauveria), SD93 (Gibberellia), and SD64 (Fusarium), had notable effects on enhancing the dry biomass of shoots and roots of maize under Cd stress. We speculate that the higher ratio of PGP EFs in corn grains from HM-contaminated areas may explain their competitiveness in such extreme environments. Fusarium and Cladosporium isolates show high PGP properties, but they can also be phytopathogenic. Therefore, it is essential to evaluate their pathogenic properties and safety for crops before considering their practical use in agriculture.

Seed Priming with Rhizospheric Bacillus subtilis: A Smart Strategy for Reducing Fumonisin Contamination in Pre-Harvest Maize.

Maize, one of the most important cereal crops in Bangladesh, is severely contaminated by fumonisin, a carcinogenic secondary metabolite produced by Fusarium including Fusarium proliferatum. Biocontrol with Bacillus strains is an effective approach to controlling this F. proliferatum as Bacillus has proven antagonistic properties against this fungus. Therefore, the present study aimed to determine how native Bacillus strains can reduce fumonisin in maize cultivated in Bangladesh, where BDISO76MR (Bacillus subtilis) strains showed the highest efficacy both in vitro in detached cob and in planta under field conditions. The BDISO76MR strain could reduce the fumonisin concentration in detached cob at 98.52% over untreated control, by inhibiting the conidia germination and spore formation of F. proliferatum at 61.56% and 77.01%, respectively in vitro. On the other hand, seed treatment with formulated BDISO76MR showed higher efficacy with a reduction of 97.27% fumonisin contamination compared to the in planta cob inoculation (95.45%) over untreated control. This implies that Bacillus-based formulation might be a potential approach in mitigating fumonisin contamination in maize to ensure safe food and feed.

Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer.

OBJECTIVE: Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs). METHODS: In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR). RESULTS: Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m6A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated. CONCLUSION: Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.

Treatment Preferences of Adult Patients with Attention-Deficit/Hyperactivity Disorder - A Discrete Choice Experiment.

Background: Understanding patient preferences for treatments may facilitate shared decision-making. This study assessed adult patient preferences for attention-deficit/hyperactivity disorder (ADHD) treatments in a sample of 600 patients in the United States (US). Methods: A web-based discrete choice experiment (DCE) survey was conducted among treated adults with ADHD. Participants were recruited from Dynata's US panel (06/22/2023-07/06/2023). Attributes and levels, identified based on clinical inputs and published data, included efficacy and safety. Participants' preferences were estimated using conditional logistic regression. Willingness to trade-off and attributes' relative importance were calculated. Overall preferences for treatment profiles approximating centanafadine, lisdexamfetamine, atomoxetine, and viloxazine were estimated using adjusted total utilities. Results were stratified by current treatment status. Sensitivity analyses including participants who passed validity tests were conducted. Results: Among the 600 participants (mean age 37.9 years; 66.2% female; 50.8% treated), all attributes had a statistically significant impact on preferences for ADHD treatments (p < 0.001); the most important attribute was improvement in ADHD symptoms (36%), followed by risks of nausea (25%), insomnia (20%), anxiety (8%), dry mouth (6%), and feeling jittery (5%). Together, safety attributes accounted for >60% of relative importance in decision-making. Participants were willing to forgo 0.59, 0.57, 0.49, 0.32, and 0.17 percentage points of symptom improvement to achieve one-percentage-point reduced risk of insomnia, nausea, anxiety, feeling jittery, and dry mouth, respectively. Centanafadine profile had consistently higher adjusted total utilities than its comparators. Similar results were obtained in the subgroup and sensitivity analyses. Conclusion: Efficacy was the most important attribute for patients when making treatment decision, but taken together, AEs had greater relative importance than efficacy alone. Accordingly, a profile resembling that of centanafadine would be preferred by an average patient compared to key competitors due to its favorable safety profile. These findings may help improve treatment decision-making, enhance treatment satisfaction, and foster adherence.

Optimization of headspace high-capacity tool coupled to two-dimensional gas chromatography-mass spectrometry for mapping the volatile organic compounds of raw pistachios. A proof-of-concept on the classification ability by geographic origin.

An optimized procedure for extracting and analyzing raw pistachio volatiles was developed through headspace sampling with high-capacity tools and subsequent analysis using comprehensive two-dimensional gas chromatography coupled with mass spectrometry. The examination of 18 pistachio samples belonging to different geographic areas led to the identification of a set of 99 volatile organic compounds (VOCs). Molecules were putatively identified using linear retention index, mass spectra similarity, and two-dimensional plot location. The impact of preprocessing and processing techniques on the aligned data matrix from a set of samples of different geographical origins, after removing contaminants, was evaluated. The combination of scaling with log-transformation, normalization with z-score, and data reduction with random forest machine learning algorithm generated a panel of 16 discriminatory VOC molecules. As a proof of concept, raw pistachios' VOC profile was employed for the first time to tentatively classify them based on their geographical origin.

Does a palliative medicine service reduce hospital length of stay and costs in adults with a life-limiting illness?-a difference-in-differences evaluation of service expansion in Ireland.

BACKGROUND: People approaching end of life account disproportionately for health care costs, and the majority of these costs accrue in hospitals. The economic evidence base to improve value of care to this population is thin. Natural experiment methods may be helpful in bridging evidence gaps with credible causal estimates from routine data, but these methods have seldom been applied in this field. This study aimed to evaluate the association between timely palliative care consultation and length of stay for adults with serious illness admitted to acute hospital in Ireland. METHODS: In primary analysis we evaluated if timely palliative care receipt following emergency hospital inpatient admission impacted length of stay (LOS); in secondary analysis we verified if palliative medicine service (PMS) implementation co-occurred with any changes in in-hospital mortality, and we estimated cost differences associated with any change in LOS. This was a secondary analysis on routinely collected data for acute admissions to public hospitals in Ireland. We used difference-in-differences analysis to exploit the staggered implementation of PMS teams at acute public hospitals in Ireland between 2010 and 2015. We identified palliative care receipt following PMS implementation using ICD-10 codes, and we matched admissions involving a palliative care interaction to admissions in years prior to PMS implementation using propensity score weights. RESULTS: Our primary analytic sample included 4,314 observations, of whom 608 (14%) received timely palliative care. We estimated that the intervention reduced LOS by nearly two days, with an estimated associated saving per admission of €1,820. These analyses were robust to multiple sensitivity analyses on regression specification, weighting strategy and site selection. Proportion of admissions ending in death did not change following PMS implementation. CONCLUSIONS: Prompt interaction between suitable patients and palliative care can improve the quality and efficiency of care to this population. Many patients receive palliative care later in the hospital stay, which does not yield cost-savings. Future studies can extend and strengthen our approach with better data, as well as using different methods to understand how to trigger palliative care early in a hospital admission and realise available gains.

Deep Learning and Histogram-Based Grain Size Analysis of Images.

Grain size analysis is used to study grain size and distribution. It is a critical indicator in sedimentary simulation experiments (SSEs), which aids in understanding hydrodynamic conditions and identifying the features of sedimentary environments. Existing methods for grain size analysis based on images primarily focus on scenarios where grain edges are distinct or grain arrangements are regular. However, these methods are not suitable for images from SSEs. We proposed a deep learning model incorporating histogram layers for the analysis of SSE images with fuzzy grain edges and irregular arrangements. Firstly, ResNet18 was used to extract features from SSE images. These features were then input into the histogram layer to obtain local histogram features, which were concatenated to form comprehensive histogram features for the entire image. Finally, the histogram features were connected to a fully connected layer to estimate the grain size corresponding to the cumulative volume percentage. In addition, an applied workflow was developed. The results demonstrate that the proposed method achieved higher accuracy than the eight other models and was highly consistent with manual results in practice. The proposed method enhances the efficiency and accuracy of grain size analysis for images with irregular grain distribution and improves the quantification and automation of grain size analysis in SSEs. It can also be applied for grain size analysis in fields such as soil and geotechnical engineering.

Testing a policy intervention in the lab: differences between students and non-students in switching bank accounts.

The reliance on student samples has long been a subject of debate in experimental approaches to studying behaviour. We contribute to this discussion by looking at differences in financial behaviour between a student and a non-student sample in three sets of lab experiments conducted in Spain, Germany and Poland (n=857). Participants from both samples switched more often and made better financial decisions after they received a message encouraging them to switch financial service providers. While the size of the effect on switching frequency was comparable between the two samples, the effect on switching quality was significantly stronger on non-students. Further analysis suggests this is due to a better performance of students before the prompt leaving less room for improvement by the reminder. Results suggest that experimental evidence derived from students should be generalized with caution.

Large-scale culturing of the subpolar foraminifera Globigerina bulloides reveals tolerance to a large range of environmental parameters associated to different life-strategies and an extended lifespan.

The subtropical to subpolar planktic foraminifera Globigerina bulloides is a calcifying marine protist, and one of the dominant foraminiferal species of the Nordic Seas. Previously, the relative abundance and shell geochemistry of fossil G. bulloides have been studied for palaeoceanographic reconstructions. There is however a lack of biological observations on the species and a poor understanding of its ecological tolerances, especially for high latitude genotypes. Here, we present observations from the first extensive culturing of G. bulloides under subpolar conditions, including the first low temperature (6-13°C) and variable salinity (30-38) experiments. Carbonate chemistry (pH and [CO3 2-]) was also manipulated. Experimental conditions were chosen to reflect a range of plausible past and future scenarios for the Nordic Seas. We found G. bulloides to be tolerant of environmental conditions well outside their optimal range (<10°C, salinity <33, pH <8). Observed life span was up to three months, which was attributed to a microalgal diet. Two alternative life strategies were employed, whereby individuals either experienced rapid growth and death, or a prolonged lifespan with minimal growth and death via slow decay. We posit this could help explain differences in geochemical signals recorded from different size fractions of fossil specimens used for palaeoceanographic reconstructions.

Mechanism and application of gas phase trapping by spontaneous imbibition.

For fractured gas reservoirs with strong water drive, gas phase trapping affects the gas recovery significantly. The recovery may be less than 50% for some reservoirs while it is only 12% for Beaver River gas field. The gas phase trapping mechanism has been revealed by the results of depletion experimental test. The residual pressure of the trapped gas is as high as 11.75 MPa with a 12.8 cm imbibition layer resulting in gas recovery deceased 49.5% compared with that without imbibition layer. A mathematical model is built to calculate the imbibition thickness based on capillary pressure and relative permeability of the matrix. The gas phase trapping are analyzed by two representative wells in Weiyuan gas field, the intermittent production reinforces the imbibition thickness and result in gas trapped in the matrix block with high residual pressure for the low performace gas wells, the extremely low gas recovery can be explained more rationally. That lays a foundation of improving the gas recovery for fractured reservoirs.

Public Heterogeneous Preferences for Low-Dose Computed Tomography Lung Cancer Screening Service Delivery in Western China: A Discrete Choice Experiment.

BACKGROUND: Lung cancer screening (LCS) with low-dose computed tomography (LDCT) is an efficient method that can reduce lung cancer mortality in high-risk individuals. However, few studies have attempted to measure the preferences for LDCT LCS service delivery. This study aimed to generate quantitative information on the Chinese population's preferences for LDCT LCS service delivery. METHODS: The general population aged 40 to 74 in the Sichuan province of China was invited to complete an online discrete choice experiment (DCE). The DCE required participants to answer 14 discrete choice questions comprising five attributes: facility levels, facility ownership, travel mode, travel time, and out-of-pocket cost. Choice data were analyzed using mixed logit and latent class logit (LCL) models. RESULTS: The study included 2529 respondents, with 746 (29.5%) identified as being at risk for lung cancer. Mixed logit model (MLM) analysis revealed that all five attributes significantly influenced respondents' choices. Facility levels had the highest relative importance (44.4%), followed by facility ownership (28.1%), while out-of-pocket cost had the lowest importance (6.4%). The at-risk group placed relatively more importance on price and facility ownership compared to the non-risk group. LCL model identified five distinct classes with varying preferences. CONCLUSION: This study revealed significant heterogeneity in preferences for LCS service attributes among the Chinese population, with facility level and facility ownership being the most important factors. The findings underscore the need for tailored strategies targeting different subgroup preferences to increase screening participation rates and improve early detection outcomes.

Behavioral nudges in social media ads show limited ability to encourage COVID-19 vaccination across countries.

Behavioral nudges in Facebook ads reached nearly 15 million people across six diverse countries and, consequently, many thousands took the step of navigating to governments' vaccine signup sites. However, none of the treatment ads caused significantly more vaccine signup intent than placebo uniformly across all countries. Critically, reporting the descriptive norm that 87% of people worldwide had either been vaccinated or planned vaccination-social proof-did not meaningfully increase vaccine signup intent in any country and significantly backfired in Taiwan. This result contradicts prominent prior findings. A charge to "protect lives in your family" significantly outperformed placebo in Taiwan and Turkey but saw null effects elsewhere. A message noting that vaccination significantly reduces hospitalization risk decreased signup intent in Brazil and had no significant effects in any other country. Such heterogeneity was the hallmark of the study: some messages saw significant treatment effects in some countries but failed in others. No nudge outperformed the placebo in Russia, a location of high vaccine skepticism. In all, widely touted behavioral nudges often failed to promote vaccine signup intent and appear to be moderated by cultural context.

Enhanced photocatalytic property of Cu doped Ce2Zr2O7 toward photodegradation of methylene blue under visible light.

Widespread ecosystem degradation from noxious substances like industrial waste, toxic dyes, pesticides, and herbicides poses serious environmental risks. For remediation of these hazardous problems, present study introduces an innovative Cu-doped Ce2Zr2O7 nano-photocatalyst, fabricated via a simple, eco-friendly hydrothermal method, designed to degrade toxic textile dye methylene blue. Harnessing Cu doping for pyrochlore Ce2Zr2O7, structure engineering carried out through a hydrothermal synthesis method to achieve superior photocatalytic performance, addressing limitations of rapid charge carrier recombination in existing photocatalysts. Photoluminescence analysis showed that doped pyrochlore slows charge carrier recombination, boosting dye degradation efficiency. UV-Visible analysis demonstrated an impressive 96 % degradation of methylene blue by Cu-doped Ce2Zr2O7 within 50 min, far exceeding the performance of pristine materials. Trapping experiments clarified the charge transfer mechanism, deepening our understanding of the photocatalytic process. These findings highlight the potential for developing innovative, highly efficient photocatalysts for environmental remediation, offering sustainable solutions to combat pollution. This study not only addresses the limitations of existing photocatalysts but also opens new avenues for enhancing photocatalytic performance through strategic material design.

Application of quality by design in optimization of nanoformulations: Principle, perspectives and practices.

Nanoparticulate drug delivery systems (NDDS) based nanoformulations have emerged as promising drug delivery systems. Various NDDS-based formulations have been reported such as polymeric nanoparticles (NPs), nanoliposomes, solid lipid NPs, nanocapsules, liposomes, self-nano emulsifying drug delivery systems, pro liposomes, nanospheres, microemulsion, nanoemulsion, gold NPs, silver NPs and nanostructured lipid carrier. They have shown numerous advantages such as enhanced bioavailability, aqueous solubility, permeability, controlled release profile, and blood-brain barrier (BBB) permeability. This advantage of NDDS can help to deliver pure drugs to the target site. However, the formulation of nanoparticles is a complex process that requires optimization to ensure product quality and efficacy. Quality by Design (QbD) is a systemic approach that has been implemented in the pharmaceutical industry to improve the quality and reliability of drug products. QbD involves the optimization of different parameters like zeta potential (ZP), particle size (PS), entrapment efficiency (EE), polydispersity index (PDI), and drug release using statistical experimental design. The present article discussed the detailed role of QbD in optimizing nanoformulations and their advantages, advancement, and applications from the industrial perspective. Various case studies of QbD in the optimization of nanoformulations are also discussed.

In situ DRIFTs-based comprehensive reaction mechanism of photo-thermal synergetic catalysis for dry reforming of methane over Ru-CeO2 catalyst.

Solar-driven photo-thermal dry reforming of methane (DRM) is an environmentally friendly production route for high-value-added chemicals. However, the lack of thorough understanding of the mechanism for photo-thermal reaction has limited its further development. Here, we systematically investigated the mechanism of photo-thermal DRM reaction with the representative of Ru/CeO2 catalyst. Through in situ DRIFTs and transient experiments, comprehensive investigation into the reaction steps and their reactive sites in the process of DRM reaction were conducted. Besides, the excitation and migration direction of photo-electron was determined by ISI-XPS experiments, and the change of surface defect structure induced by light was characterized by ISI-EPR experiments. Based on the above results, the photo-enhancement effect on each micro-reaction step was determined. This study provides a theoretical basis for the industrialization of photo-thermal DRM reaction and its development of catalysts.

Nonlinear adaptive robust control of tank bidirectional stabilizers with dead zone compensation based on extended state observer.

In this paper, the problem of highly performance motion control of tank bidirectional stabilizer with dead zone nonlinearity and uncertain nonlinearity is addressed. First, the electromechanical coupling dynamics model of bidirectional stabilizer is developed finely. Second, the dead zone nonlinearity in bidirectional stabilizer is characterized as the combination of an uncertain time-varying gain and a bounded disturbance term. Meanwhile, an adaptive robust controller with dead zone compensation is proposed by organically combining adaptive technique and extended state observer (ESO) through backstepping method. The adaptive technique is employed to reduce the impact of unknown system parameter and dead zone parameter. Furthermore, the ESO is constructed to compensate the lumped uncertainties including unmodeled dynamics and dead zone residual, and integrated together via a feedforward cancellation technique. Moreover, the adaptive robust control law is derived to ensure final global stability. In stability analysis, the asymptotic tracking performance of the proposed controller can be guaranteed as the uncertainty nonlinearities in tank bidirectional stabilizer are constant. It is also guaranteed to achieve bounded tracking performance when time-varying uncertainties exist. Extensive co-simulation and experimental results verify the superiority of the proposed strategy.