In this research, the effect of external fields (solvent, temperature, solution concentration, and external force) on dynamic evolution from chain disorder to order of poly[[4,8-bis[(2-ethylhexyl)oxy]benzo[1,2- b:4,5- b']dithiophene-2,6-diyl][3-fluoro-2-[(2-ethylhexyl)carbonyl]thieno[3,4- b]thiophenediyl]] (PTB7) condensed state structures was explored by UV-vis absorption spectra, atomic force microscope, and transmission electron microscopy (TEM). It was found that PTB7 main chains presented amorphous conformations induced by the poor solvent 1,2-dichloroethane. However, the local ordered aggregation appeared in amorphous conformations when the solubility of the poor solvent was again lowered by reducing temperature. It is worth noting that the size of ordered aggregation was further increased with the decrease of solution concentration or increase of external force. It was found that there were two main PTB7 absorption peaks in the UV-vis absorption spectra; we denoted A for the intensity of the lower energy absorption peak and A for the intensity of the higher energy absorption peak. The ratio R = A/ A was used to characterize the dynamic evolution from disorder to order of the PTB7 condensed state structures in absorption spectra. It increased from 0.94 for PTB7 amorphous state to 1.25 for PTB7 large-size ordered aggregation. The dynamic evolution from chain disorder to order could also be distinctly observed by TEM. It was inferred that PTB7 condensed state structures (amorphous state, local ordered aggregation, and large-scale ordered aggregation) might exist simultaneously because of the complexity of copolymer conformations. This research is meaningful to establish physical basis for the molecule design and the synthesis of materials to enhance photoelectronic device efficiency based on condensed matter physics of conjugated polymer.
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http://dx.doi.org/10.1021/acsami.8b08938 | DOI Listing |
Nat Commun
January 2025
The Faculty of Data and Decisions Sciences, Technion - Israel Institute of Technology, Haifa, Israel.
Large Language Models (LLMs) have shown success in predicting neural signals associated with narrative processing, but their approach to integrating context over large timescales differs fundamentally from that of the human brain. In this study, we show how the brain, unlike LLMs that process large text windows in parallel, integrates short-term and long-term contextual information through an incremental mechanism. Using fMRI data from 219 participants listening to spoken narratives, we first demonstrate that LLMs predict brain activity effectively only when using short contextual windows of up to a few dozen words.
View Article and Find Full Text PDFWater Res
December 2024
Eawag: Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600, Dübendorf, Switzerland. Electronic address:
Aerobic granular sludge (AGS) is usually considered to be a biofilm system consisting of granules only, although practical experience suggests that flocs and granules of various sizes co-exist. This study thus focused on understanding the contribution of flocs and granules of various sizes to nitrification in a full-scale AGS-based wastewater treatment plant (WWTP) operated as a sequencing batch reactor (SBR). The size distribution in terms of total suspended solids (TSS) and the distribution of the nitrifying communities and activities were monitored over 14 months.
View Article and Find Full Text PDFDrugs R D
January 2025
Quality Evaluation Team, Samsung Bioepis Co., Ltd, Incheon, South Korea.
Background: SB17 is being developed as a biosimilar to ustekinumab reference product (RP), a human monoclonal antibody (IgG1 kappa immunoglobulin) that binds to the common p40 subunit of cytokines interleukin (IL)-23 and IL-12. Binding to this subunit prevents interaction with their receptor, resulting in modulation in the immune system responses that play a key role in inflammatory disease.
Objective: The objective of this study was to demonstrate structural, physicochemical, and biological similarity between ustekinumab RP and SB17 using various state-of-the-art analytical methods.
Neural Netw
December 2024
Department of Earth Science and Engineering, Imperial College London, Prince Consort Road, London SW7 2BP, UK; Centre for AI-Physics Modelling, Imperial-X, White City Campus, Imperial College London, W12 7SL, UK.
Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this development via implementing conventional partial differential equation (PDE) solvers with machine learning packages, most of which rely on structured spatial discretisation and fast convolution algorithms. However, unstructured meshes are favoured in problems with complex geometries.
View Article and Find Full Text PDFR Soc Open Sci
January 2025
School of Computing and Information Systems, The University of Melbourne, Parkville, Victoria, Australia.
During the COVID-19 pandemic, both government-mandated lockdowns and discretionary changes in behaviour combined to produce dramatic and abrupt changes to human mobility patterns. To understand the socioeconomic determinants of intervention compliance and discretionary behavioural responses to epidemic threats, we investigate whether changes in human mobility showed a systematic variation by socioeconomic status during two distinct periods of the COVID-19 pandemic in Australia. We analyse mobility data from two major urban centres and compare the trends during mandated stay-at-home policies and after the full relaxation of nonpharmaceutical interventions, which coincided with a large surge of COVID-19 cases.
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