99 research outputs found
Complete gradient expanding Ricci solitons with finite asymptotic scalar curvature ratio
Let , , be a complete gradient expanding Ricci soliton
with nonnegative Ricci curvature . In this paper, we show that if the
asymptotic scalar curvature ratio of is finite (i.e., ), then the Riemann curvature tensor must
have at least sub-quadratic decay, namely, for any .Comment: 20 pages. Lemma 3.1 statement simplified; the proof of Lemma 3.2 &
Lemma 3.3 streamlined. arXiv admin note: text overlap with arXiv:2111.0984
DDRF: Denoising Diffusion Model for Remote Sensing Image Fusion
Denosing diffusion model, as a generative model, has received a lot of
attention in the field of image generation recently, thanks to its powerful
generation capability. However, diffusion models have not yet received
sufficient research in the field of image fusion. In this article, we introduce
diffusion model to the image fusion field, treating the image fusion task as
image-to-image translation and designing two different conditional injection
modulation modules (i.e., style transfer modulation and wavelet modulation) to
inject coarse-grained style information and fine-grained high-frequency and
low-frequency information into the diffusion UNet, thereby generating fused
images. In addition, we also discussed the residual learning and the selection
of training objectives of the diffusion model in the image fusion task.
Extensive experimental results based on quantitative and qualitative
assessments compared with benchmarks demonstrates state-of-the-art results and
good generalization performance in image fusion tasks. Finally, it is hoped
that our method can inspire other works and gain insight into this field to
better apply the diffusion model to image fusion tasks. Code shall be released
for better reproducibility
CoAIcoder: Examining the Effectiveness of AI-assisted Collaborative Qualitative Analysis
While the domain of individual-level AI-assisted analysis has been
extensively explored in previous studies, the field of AI-assisted
collaborative qualitative analysis remains relatively unexplored. After
identifying CQA practices and design opportunities through formative
interviews, we introduce our collaborative qualitative coding tool, CoAIcoder,
and designed the four different collaboration methods. We subsequently
implemented a between-subject design involving 32 pairs of users who have
undergone training in CQA across three commonly utilized phases under four
methods. Our results suggest that CoAIcoder, which employs AI and a Shared
Model, could potentially improve the efficiency of the coding process in CQA by
fostering a quicker shared understanding and promoting early-stage discussions.
However, this may come with the potential downside of reduced code diversity.
We also underscored the existence of a trade-off between the level of
independence and the coding outcome when humans collaborate during the early
coding stages. Lastly, we identify design implications that could inspire and
inform the future design of CQA systems
Impact of Human-AI Interaction on User Trust and Reliance in AI-Assisted Qualitative Coding
While AI shows promise for enhancing the efficiency of qualitative analysis,
the unique human-AI interaction resulting from varied coding strategies makes
it challenging to develop a trustworthy AI-assisted qualitative coding system
(AIQCs) that supports coding tasks effectively. We bridge this gap by exploring
the impact of varying coding strategies on user trust and reliance on AI. We
conducted a mixed-methods split-plot 3x3 study, involving 30 participants, and
a follow-up study with 6 participants, exploring varying text selection and
code length in the use of our AIQCs system for qualitative analysis. Our
results indicate that qualitative open coding should be conceptualized as a
series of distinct subtasks, each with differing levels of complexity, and
therefore, should be given tailored design considerations. We further observed
a discrepancy between perceived and behavioral measures, and emphasized the
potential challenges of under- and over-reliance on AIQCs systems. Additional
design implications were also proposed for consideration.Comment: 27 pages with references, 9 figures, 5 table
Just add sugar for carbohydrate induced self-assembly of curcumin
In nature, self-assembly processes based on amphiphilic molecules play an integral part in
the design of structures of higher order such as cells. Among them, amphiphilic glycoproteins
or glycolipids take on a pivotal role due to their bioactivity. Here we show that sugars, in
particular, fructose, are capable of directing the self-assembly of highly insoluble curcumin
resulting in the formation of well-defined capsules based on non-covalent forces. Simply
by mixing an aqueous solution of fructose and curcumin in an open vessel leads to the
generation of capsules with sizes ranging between 100 and 150 nm independent of the
initial concentrations used. Our results demonstrate that hydrogen bonding displayed
by fructose can induce the self-assembly of hydrophobic molecules such as curcumin into
well-ordered structures, and serving as a simple and virtually instantaneous way of making
nanoparticles from curcumin in water with the potential for template polymerization and
nanocarriers.S.W. is grateful for UNSW PhD scholarship. J.H. acknowledges support from the Australian Research
Council (DE160100807) and supercomputer resources from the NCI, Pawsey Supercomputing
Centre and Intersect Australian Ltd. Finally, M.H.S. and C.J.G. would like to
thank the Australian Research Council (ARC DP 160101172) for fundin
Mechanism investigation on the formation of olefins and paraffin from the thermochemical catalytic conversion of triglycerides catalyzed by alkali metal catalysts
Triglycerides are a promising biomass feedstock that can be used for production of organic hydrocarbons including long-chain olefins and paraffin. The challenge for this production process lies on the lack of a clear mechanism of the conversion process. In this work, the conversion mechanism from triglycerides to olefins and paraffin using alkali metal catalysts was investigated adopting both computational calculations using density functional theory and experimental studies. The bond dissociation energies of the main bonds were calculated, especially for the α carbon‑carbon bond, which leads to effective removal of carboxyl groups during the thermochemical conversion process. The dynamic behavior of triglycerides catalyzed by alkali metal catalysts was also investigated using thermogravimetric analysis, which found that Li ion has lowest activation energy below 200 kJ/mol when compared with the other alkali ions studied. The catalytic conversion mechanism was proposed in this work based on the results obtained from TG-IR, GC, GC–MS and XRD analyses. The O atoms are removed in the form of CO, CO2 and H2O, product M + O and M+, which generates M2CO3. A more detailed mechanism has been proposed in this paper, which has significance toward guiding the cleavage of triglycerides to produce long‑carbon-chain terminal olefins and normal paraffin
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