Catalysts design for higher alcohols synthesis by CO2 hydrogenation: Trends and future perspectives

Global warming due to the accumulation of atmospheric CO2 has received great attention in recent years. Hence, it is urgent to reduce CO2 emissions into the atmosphere and develop sustainable technologies for a circular carbon economy. In this regard, CO2 capture coupled with the conversion into chemicals and fuels provides a promising solution to reduce CO2 emissions as well as to store and utilize renewable energy. Among the many possible CO2 conversion pathways, CO2 hydrogenation to higher alcohols is considered an important strategy for the synthesis of carbon-based fuels and feedstock and holds great promise for the chemical industry. Thus, this review provides an overview of advances in CO2 hydrogenation to higher alcohols that have been achieved recently in terms of catalyst design, catalytic performance, and insight into the reaction mechanism under different experimental conditions. First, the limitations provided by reaction thermodynamics and the indispensability of catalysts for CO2 hydrogenation to higher alcohols are discussed. Then, four main categories of catalysts will be introduced and discussed (i.e. Rh-, Cu-, Mo-, and Co-based catalysts). Moreover, important factors significantly influencing the efficiency of the catalytic transformation such as alkali/alkaline earth metal promoters, transition metal promoters, catalyst supports, catalyst precursors, and reaction conditions, as well as the reaction mechanism are explained. Finally, the review discusses emerging methodologies yet to be explored and future directions to achieve a high efficiency for the hydrogenation of CO2 to higher alcohols

Exploring Memorization in Fine-tuned Language Models

LLMs have shown great capabilities in various tasks but also exhibited memorization of training data, thus raising tremendous privacy and copyright concerns. While prior work has studied memorization during pre-training, the exploration of memorization during fine-tuning is rather limited. Compared with pre-training, fine-tuning typically involves sensitive data and diverse objectives, thus may bring unique memorization behaviors and distinct privacy risks. In this work, we conduct the first comprehensive analysis to explore LMs' memorization during fine-tuning across tasks. Our studies with open-sourced and our own fine-tuned LMs across various tasks indicate that fine-tuned memorization presents a strong disparity among tasks. We provide an understanding of this task disparity via sparse coding theory and unveil a strong correlation between memorization and attention score distribution. By investigating its memorization behavior, multi-task fine-tuning paves a potential strategy to mitigate fine-tuned memorization

Recent advances in PEG–PLA block copolymer nanoparticles

Due to their small particle size and large and modifiable surface, nanoparticles have unique advantages compared with other drug carriers. As a research focus in recent years, polyethylene glycol–polylactic acid (PEG–PLA) block copolymer and its end-group derivative nanoparticles can enhance the drug loading of hydrophobic drugs, reduce the burst effect, avoid being engulfed by phagocytes, increase the circulation time of drugs in blood, and improve bioavailability. Additionally, due to their smaller particle size and modified surface, these nanoparticles can accumulate in inflammation or target locations to enhance drug efficacy and reduce toxicity. Recent advances in PEG–PLA block copolymer nanoparticles, including the synthesis of PEG–PLA and the preparation of PEG–PLA nanoparticles, were introduced in this study, in particular the drug release and modifiable characteristics of PEG–PLA nanoparticles and their application in pharmaceutical preparations

detrex: Benchmarking Detection Transformers

The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and other perception tasks. However, the current field lacks a unified and comprehensive benchmark specifically tailored for DETR-based models. To address this issue, we develop a unified, highly modular, and lightweight codebase called detrex, which supports a majority of the mainstream DETR-based instance recognition algorithms, covering various fundamental tasks, including object detection, segmentation, and pose estimation. We conduct extensive experiments under detrex and perform a comprehensive benchmark for DETR-based models. Moreover, we enhance the performance of detection transformers through the refinement of training hyper-parameters, providing strong baselines for supported algorithms.We hope that detrex could offer research communities a standardized and unified platform to evaluate and compare different DETR-based models while fostering a deeper understanding and driving advancements in DETR-based instance recognition. Our code is available at https://github.com/IDEA-Research/detrex. The project is currently being actively developed. We encourage the community to use detrex codebase for further development and contributions.Comment: project link: https://github.com/IDEA-Research/detre

OsOLP1 contributes to drought tolerance in rice by regulating ABA biosynthesis and lignin accumulation

Rice, as a major staple crop, employs multiple strategies to enhance drought tolerance and subsequently increase yield. Osmotin-like proteins have been shown to promote plant resistance to biotic and abiotic stress. However, the drought resistance mechanism of osmotin-like proteins in rice remains unclear. This study identified a novel osmotin-like protein, OsOLP1, that conforms to the structure and characteristics of the osmotin family and is induced by drought and NaCl stress. CRISPR/Cas9-mediated gene editing and overexpression lines were used to investigate the impact of OsOLP1 on drought tolerance in rice. Compared to wild-type plants, transgenic rice plants overexpressing OsOLP1 showed high drought tolerance with leaf water content of up to 65%, and a survival rate of 53.1% by regulating 96% stomatal closure and more than 2.5-fold proline content promotion through the accumulation of 1.5-fold endogenous ABA, and enhancing about 50% lignin synthesis. However, OsOLP1 knockout lines showed severely reduced ABA content, decreased lignin deposition, and weakened drought tolerance. In conclusion, the finding confirmed that OsOLP1 drought-stress modulation relies on ABA accumulation, stomatal regulation, proline, and lignin accumulation. These results provide new insights into our perspective on rice drought tolerance

Compatibility research of laser additive repairing (LAR) TA15 forgings with Ti6Al4V-xTA15 alloy

The application of mixed powders with different mass fraction on laser additive repairing (LAR) can be an effective way to guarantee the performance and functionality of repaired part in time. A convenient and feasible approach is presented to repair TA15 forgings by employing Ti6Al4V-xTA15 mixed powders in this paper. The performance compatibility of Ti6Al4V-xTA15 powders from the aspects of microhardness, tensile property, heat capacity, thermal expansion coefficient and corrosion resistance with the TA15 forgings was fully investigated. The primary α laths were refined and the volume fraction of the secondary α phase was increased by increasing the mass fraction of TA15 in the mixed Ti6Al4V-xTA15 powders, leading to varied performances. In conclusion, the mixed Ti6Al4V-70%TA15 (x=70%) powders is the most suitable candidate and is recommended as the raw material for LAR of TA15 forgings based on overall consideration of the compatibility calculations of the laser repaired zone with the wrought substrate zone

Achieving high power factor and output power density in p-type half-Heuslers Nb

Improvements in thermoelectric material performance over the past two decades have largely been based on decreasing the phonon thermal conductivity. Enhancing the power factor has been less successful in comparison. In this work, a peak power factor of ∼106 μW⋅cm⁻¹⋅K⁻² is achieved by increasing the hot pressing temperature up to 1,373 K in the p-type half-Heusler Nb[subscript 0.95]Ti[subscript 0.05]FeSb. The high power factor subsequently yields a record output power density of ∼22 W⋅cm⁻² based on a single-leg device operating at between 293 K and 868 K. Such a high-output power density can be beneficial for large-scale power generation applications.United States. Department of Energy (DE-SC0001299

The Antitumor Activities of Marsdenia tenacissima

Marsdenia tenacissima (MT), a traditional Chinese herbal medicine, has long been used for thousands of years to treat asthma, tracheitis, rheumatism, etc. An increasing number of recent studies have focused on the antitumor effects of MT. The effects of MT on cancer are the result of various activated signaling pathways and inhibiting factors and the high expression levels of regulatory proteins. MT can inhibit different cancer types including non-small cell lung cancer (NSCLC), malignant tumors, hepatic carcinoma, and so on. This article mainly focuses on the activities and mechanisms of MT. In addition, the efficacy and toxicity of MT are also discussed. Further studies of MT are required for improved medicinal utilization