400 research outputs found
Side-chain and backbone ordering in Homopolymers
In order to study the relation between backbone and side chain ordering in
proteins, we have performed multicanonical simulations of deka-peptide chains
with various side groups. Glu10, Gln10, Asp10, Asn10, and Lys10 were selected
to cover a wide variety of possible interactions between the side chains of the
monomers. All homopolymers undergo helix-coil transitions. We found that
peptides with long side chains that are capable of hydrogen bonding, i.e.
Glu10, and Gln10, exhibit a second transition at lower temperatures connected
with side chain ordering. This occurs in gas phase as well as in solvent,
although the character of the side chain structure is different in each case.
However, in polymers with short side chains capable of hydrogen bonding, i.e.
Asp10 and Asn10, side chain ordering takes place over a wide temperature range
and exhibits no phase transition like character. Moreover, non-backbone
hydrogen bonds show enhanced formation and fluctuations already at the
helix-coil transition temperature, indicating competition between side chain
and backbone hydrogen bond formation. Again, these results are qualitatively
independent of the environment. Side chain ordering in Lys10, whose side groups
are long and polar, also takes place over a wide temperature range and exhibits
no phase transition like character in both environments. Reasons for the
observed chain length threshold and consequences from these results for protein
folding are discussed.Comment: 12 pages,11 figure
Review of 3D Printed Millimeter-Wave and Terahertz Passive Devices
The 3D printing technology is catching attention nowadays. It has certain advantages over the traditional fabrication processes. We give a chronical review of the 3D printing technology from the time it was invented. This technology has also been used to fabricate millimeter-wave (mmWave) and terahertz (THz) passive devices. Though promising results have been demonstrated, the challenge lies in the fabrication tolerance improvement such as dimensional tolerance and surface roughness. We propose the design methodology of high order device to circumvent the dimensional tolerance and suggest specific modelling of the surface roughness of 3D printed devices. It is believed that, with the improvement of the 3D printing technology and related subjects in material science and mechanical engineering, the 3D printing technology will become mainstream for mmWave and THz passive device fabrication
Feature Interaction Aware Automated Data Representation Transformation
Creating an effective representation space is crucial for mitigating the
curse of dimensionality, enhancing model generalization, addressing data
sparsity, and leveraging classical models more effectively. Recent advancements
in automated feature engineering (AutoFE) have made significant progress in
addressing various challenges associated with representation learning, issues
such as heavy reliance on intensive labor and empirical experiences, lack of
explainable explicitness, and inflexible feature space reconstruction embedded
into downstream tasks. However, these approaches are constrained by: 1)
generation of potentially unintelligible and illogical reconstructed feature
spaces, stemming from the neglect of expert-level cognitive processes; 2) lack
of systematic exploration, which subsequently results in slower model
convergence for identification of optimal feature space. To address these, we
introduce an interaction-aware reinforced generation perspective. We redefine
feature space reconstruction as a nested process of creating meaningful
features and controlling feature set size through selection. We develop a
hierarchical reinforcement learning structure with cascading Markov Decision
Processes to automate feature and operation selection, as well as feature
crossing. By incorporating statistical measures, we reward agents based on the
interaction strength between selected features, resulting in intelligent and
efficient exploration of the feature space that emulates human decision-making.
Extensive experiments are conducted to validate our proposed approach.Comment: Accepted to SIAM Conference on Data Mining(SDM) 202
Backbone and Sidechain Ordering in a small Protein
We investigate the relation between backbone and side-chain ordering in a
small protein. For this purpos e we have performed multicanonical simulations
of the villin headpiece subdomain HP-36, an often used to y model in protein
studies. Concepts of circular statistics are introduced to analyze side-chain
fluctuations. In contrast to earlier studies on homopolypeptides (Wei et al.,
J. Phys. Chem. B, 111 (2007) 4244) we do not find collective effects leading to
a separate transition. Rather, side-chain ordering is spread over a wide
temperature range. Our results indicate a thermal hierarchy of ordering events,
with side-chain ordering appearing at temperatures below the helix-coil
transition but above the folding transition. We conjecture that this thermal
hierarchy reflects an underlying temporal order, and that side-chain ordering
facilitates the search for the correct backbone topology.Comment: accepted in J. Chem. Phy
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