Solvent-free catalytic oxidation of benzyl alcohol over Au-Pd bimetal deposited on TiO2: comparison of Rutile, Brookite, and Anatase

TiO2 (P25)-supported Au-Pd bimetal nanoparticles displayed excellent performance in the solvent-free benzyl alcohol catalytic oxidation. However, little research attention has been paid to investigate the effects of TiO2 form on the catalytic activity of Au-Pd/TiO2. In the present research, rutile, brookite, and anatase TiO2 were successfully synthesized and subsequently applied as the carrier to load Au-Pd nanoparticles by the deposition-precipitation method. The experimental results indicated that the benzyl alcohol conversion employing the rutile TiO2-supported Au-Pd catalyst is higher than the conversion of anatase and brookite TiO2-loaded Au-Pd catalysts. However, the Au-Pd/TiO2-rutile displayed the lowest and highest selectivity toward benzaldehyde and toluene, respectively. ICP-AES, XRD, XPS, and TEM were conducted to characterize these catalysts. The corresponding experimental results revealed that the excellent performance of Au-Pd/TiO2-rutile catalyst was attributed to both the smaller Au-Pd nanoparticle size distribution and the higher concentrations of Oα and Pd2+ species on the catalyst surface. In the recycle experiments, the Au-Pd/TiO2-rutile catalyst displayed lower reaction stability compared with the Au-Pd/TiO2-anatase and Au-Pd/TiO2-brookite, which might be due to the coverage of larger amount of aldehyde products on the surface

Interpretable Machine Learning for Weather and Climate Prediction: A Survey

Advanced machine learning models have recently achieved high predictive accuracy for weather and climate prediction. However, these complex models often lack inherent transparency and interpretability, acting as "black boxes" that impede user trust and hinder further model improvements. As such, interpretable machine learning techniques have become crucial in enhancing the credibility and utility of weather and climate modeling. In this survey, we review current interpretable machine learning approaches applied to meteorological predictions. We categorize methods into two major paradigms: 1) Post-hoc interpretability techniques that explain pre-trained models, such as perturbation-based, game theory based, and gradient-based attribution methods. 2) Designing inherently interpretable models from scratch using architectures like tree ensembles and explainable neural networks. We summarize how each technique provides insights into the predictions, uncovering novel meteorological relationships captured by machine learning. Lastly, we discuss research challenges around achieving deeper mechanistic interpretations aligned with physical principles, developing standardized evaluation benchmarks, integrating interpretability into iterative model development workflows, and providing explainability for large foundation models.Comment: 26 pages, 5 figure

Assessment of the economic impacts of heat waves: A case study of Nanjing, China

The southeast region of China is frequently affected by summer heat waves. Nanjing, a metropolitan city in Jiangsu Province, China, experienced an extreme 14-day heat wave in 2013. Extreme heat can not only induce health outcomes in terms of excess mortality and morbidity (hospital admissions) but can also cause productivity losses for self-paced indoor workers and capacity losses for outdoor workers due to occupational safety requirements. All of these effects can be translated into productive working time losses, thus creating a need to investigate the macroeconomic implications of heat waves on production supply chains. Indeed, industrial interdependencies are important for capturing the cascading effects of initial changes in factor inputs in a single sector on the remaining sectors and the economy. To consider these effects, this paper develops an interdisciplinary approach by combining meteorological, epidemiological and economic analyses to investigate the macroeconomic impacts of heat waves on the economy of Nanjing in 2013. By adopting a supply-driven input-output (IO) model, labour is perceived to be a key factor input, and any heat effect on human beings can be viewed as a degradation of productive time and human capital. Using this interdisciplinary tool, our study shows a total economic loss of 27.49 billion Yuan for Nanjing in 2013 due to the heat wave, which is equivalent to 3.43% of the city's gross value of production in 2013. The manufacturing sector sustained 63.1% of the total economic loss at 17.34 billion Yuan. Indeed, based on the ability of the IO model to capture indirect economic loss, our results further suggest that although the productive time losses in the manufacturing and service sectors have lower magnitudes than those in the agricultural and mining sectors, they can entail substantial indirect losses because of industrial interdependencies. This important conclusion highlights the importance of incorporating industrial interdependencies and indirect economic assessments in disaster risk studies

Investigations of supported Au-Pd nanoparticles on synthesized CeO2 with different morphologies and application in solvent-free benzyl alcohol oxidation

Au-Pd bimetallic nanoparticles immobilized on series of CeO2 supports with different morphologies, e.g., rod, cube, and polyhedrons were prepared through the deposition-precipitation method with a consequent investigation on their catalytic performances for benzyl alcohol oxidation in the absence of solvent. The experimental results exhibited that the morphology of CeO2 has a markedly impact on the catalytic performance of Au-Pd/CeO2. In which Au-Pd supported on CeO2 rod could achieve higher benzyl alcohol conversion than that supported on CeO2 polyhedrons and CeO2 cube, however, CeO2 cube supported Au-Pd showed the highest selectivity towards the production of benzaldehyde. ICP-AES, XRD, Raman, N2-BET, TEM, HAADF-STEM, and XPS were conducted to characterize the catalysts. The results revealed that the excellent behavior of Au-Pd/CeO2-rod in benzyl alcohol oxidation was closely related with the smaller size of CeO2 particle, the higher concentration of oxygen defects in support and the higher number of Ce3+ and Pd2+ species on the catalyst surface. The present study on the morphologies of CeO2 support in solvent-free benzyl alcohol oxidation would offer a notable approach for the future catalyst design

The role of macrophages in gastric cancer

As one of the deadliest cancers of the gastrointestinal tract, there has been limited improvement in long-term survival rates for gastric cancer (GC) in recent decades. The poor prognosis is attributed to difficulties in early detection, minimal opportunity for radical resection and resistance to chemotherapy and radiation. Macrophages are among the most abundant infiltrating immune cells in the GC stroma. These cells engage in crosstalk with cancer cells, adipocytes and other stromal cells to regulate metabolic, inflammatory and immune status, generating an immunosuppressive tumour microenvironment (TME) and ultimately promoting tumour initiation and progression. In this review, we summarise recent advances in our understanding of the origin of macrophages and their types and polarisation in cancer and provide an overview of the role of macrophages in GC carcinogenesis and development and their interaction with the GC immune microenvironment and flora. In addition, we explore the role of macrophages in preclinical and clinical trials on drug resistance and in treatment of GC to assess their potential therapeutic value in this disease

Au-Pd nanoparticles immobilized on TiO2 nanosheet as an active and durable catalyst for solvent-free selective oxidation of benzyl alcohol

TiO2 nanocrystals with controlled facets have been extensively investigated due to their excellent photocatalytic performance in sustainable and green energy field. However, the applications in thermal catalysis without applying UV irradiation are comparably less and the identification of their intrinsic roles, especially the different catalytic behaviors of each crystal facet, remains not fully recognized. In this study, bimetallic AuPd nanoparticles supported on anatase TiO2 nanosheets exposing {0 0 1} facets or TiO2 nanospindles exposing {1 0 1} as a catalyst were prepared by sol-immobilization method and used for solvent-free benzyl alcohol oxidation. The experimental results indicated that the exposed facet of the support has a significant effect on the catalytic performance. AuPd/TiO2-001 catalyst exhibited a higher benzyl alcohol conversion than that of the AuPd/TiO2-101. Meanwhile, all the prepared AuPd/TiO2 catalysts were characterized by XRD, ICP-AES, XPS, BET, TEM, and HRTEM. The results revealed that the higher number of oxygen vacancies in TiO2-sheets with the exposed {0 0 1} facets of higher surface energy could be responsible for the observed enhancement in the catalytic performance of benzyl alcohol oxidation. The present study displays that it is plausible to enhance the catalytic performance for the benzyl alcohol oxidation by tailoring the exposed facet of the TiO2 as a catalyst support

Polyethyleneimine-coated MXene quantum dots improve cotton tolerance to Verticillium dahliae by maintaining ROS homeostasis

Verticillium dahliae is a soil-borne hemibiotrophic fungal pathogen that threatens cotton production worldwide. In this study, we assemble the genomes of two V. dahliae isolates: the more virulence and defoliating isolate V991 and nondefoliating isolate 1cd3-2. Transcriptome and comparative genomics analyses show that genes associated with pathogen virulence are mostly induced at the late stage of infection (Stage II), accompanied by a burst of reactive oxygen species (ROS), with upregulation of more genes involved in defense response in cotton. We identify the V991-specific virulence gene SP3 that is highly expressed during the infection Stage II. V. dahliae SP3 knock-out strain shows attenuated virulence and triggers less ROS production in cotton plants. To control the disease, we employ polyethyleneimine-coated MXene quantum dots (PEI-MQDs) that possess the ability to remove ROS. Cotton seedlings treated with PEI-MQDs are capable of maintaining ROS homeostasis with enhanced peroxidase, catalase, and glutathione peroxidase activities and exhibit improved tolerance to V. dahliae. These results suggest that V. dahliae trigger ROS production to promote infection and scavenging ROS is an effective way to manage this disease. This study reveals a virulence mechanism of V. dahliae and provides a means for V. dahliae resistance that benefits cotton production

Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016

May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961–2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Ni ̃no years have been found to be correlatedwith extreme rainfall in the Yangtze River region in previous studies—the strong El Ni ̃no of 2015–2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south