262 research outputs found
Dynamics of Vesicle Formation from Lipid Droplet: Mechanism and Controllability
A coarse-grained model developed by Marrink et al. [J. Phys. Chem. B 111,
7812 (2007)] is applied to investigate vesiculation of lipid
[dipalmitoylphosphatidylcholine (DPPC)] droplets in water. Three kinds of
morphologies of micelles are found with increasing lipid droplet size. When the
initial lipid droplet is smaller, the equilibrium structure of the droplet is a
spherical micelle. When the initial lipid droplet is larger, the lipid ball
starts to transform into a disk micelle or vesicle. The mechanism of vesicle
formation from a lipid ball is analyzed from the self-assembly of DPPC on the
molecular level, and the morphological transition from disk to vesicle with
increasing droplet size is demonstrated. Importantly, we discover that the
transition point is not very sharp, and for a fixed-size lipid ball, the disk
and vesicle appear with certain probabilities. The splitting phenomenon, i.e.,
the formation of a disk/vesicle structure from a lipid droplet, is explained by
applying a hybrid model of the Helfrich membrane theory. The elastic module of
the DPPC bilayer and the smallest size of a lipid droplet for certain formation
of a vesicle are successfully predicted.Comment: 22 pages, 11 figures Submitted to J. Chem. Phy
Strong Photoluminescence Enhancement of MoS2 through Defect Engineering and Oxygen Bonding
We report on a strong photoluminescence (PL) enhancement of monolayer MoS2
through defect engineering and oxygen bonding. Micro- PL and Raman images
clearly reveal that the PL enhancement occurs at cracks/defects formed during
high temperature vacuum annealing. The PL enhancement at crack/defect sites
could be as high as thousands of times after considering the laser spot size.
The main reasons of such huge PL enhancement include: (1) the oxygen chemical
adsorption induced heavy p doping and the conversion from trion to exciton; (2)
the suppression of non-radiative recombination of excitons at defect sites as
verified by low temperature PL measurements. First principle calculations
reveal a strong binding energy of ~2.395 eV for oxygen molecule adsorbed on an
S vacancy of MoS2. The chemical adsorbed oxygen also provides a much more
effective charge transfer (0.997 electrons per O2) compared to physical
adsorbed oxygen on ideal MoS2 surface. We also demonstrate that the defect
engineering and oxygen bonding could be easily realized by oxygen plasma
irradiation. X-ray photoelectron spectroscopy further confirms the formation of
Mo-O bonding. Our results provide a new route for modulating the optical
properties of two dimensional semiconductors. The strong and stable PL from
defects sites of MoS2 may have promising applications in optoelectronic
devices.Comment: 23 pages, 9 figures, to appear in ACS Nan
Tuning the Dzyaloshinskii-Moriya Interaction in Pt/Co/MgO heterostructures through MgO thickness
The interfacial Dzyaloshinskii-Moriya interaction (DMI) in the
ferromagnetic/heavy metal ultra-thin film structures , has attracted a lot of
attention thanks to its capability to stabilize Neel-type domain walls (DWs)
and magnetic skyrmions for the realization of non-volatile memory and logic
devices. In this study, we demonstrate that magnetic properties in
perpendicularly magnetized Ta/Pt/Co/MgO/Pt heterostructures, such as
magnetization and DMI, can be significantly influenced through both the MgO and
the Co ultrathin film thickness. By using a field-driven creep regime domain
expansion technique, we find that non-monotonic tendencies of DMI field appear
when changing the thickness of MgO and the MgO thickness corresponding to the
largest DMI field varies as a function of the Co thicknesses. We interpret this
efficient control of DMI as subtle changes of both Pt/Co and Co/MgO interfaces,
which provide a method to investigate ultra-thin structures design to achieve
skyrmion electronics.Comment: 18 pages, 11 figure
Explain-then-Translate: An Analysis on Improving Program Translation with Self-generated Explanations
This work explores the use of self-generated natural language explanations as
an intermediate step for code-to-code translation with language models. Across
three types of explanations and 19 programming languages constructed from the
MultiPL-E dataset, we find the explanations to be particularly effective in the
zero-shot case, improving performance by 12% on average. Improvements with
natural language explanations are particularly pronounced on difficult
programs. We release our dataset, code, and canonical solutions in all 19
languages.Comment: 9 pages, 4 figures, 5 tables, 48 pages total. To be published in
EMNLP Findings 202
Machine Learning for Multi-Action Classification of Lower Limbs for BCI
Over the past two decades, significant progress has been made in brain-computer interfaces (BCIs), devices which enable direct communications between human brains and external devices. One of the prevalent control paradigms is motor imagery-based BCI (MI-BCI), by which users imagine specific actions to express their intentions. Left-hand and right-hand motor imageries are frequently used in the MI-BCI. If a third class is needed, the imagination of both feet is usually added. However, it is relatively rare to separate feet into left lower limb and right limb in MI-BCI systems. In addition, previous studies have demonstrated that real movements can be distinguished from one another via processing the electroencephalogram (EEG). Similarly, motor imagery (MI) and movement observations (MO) can also be distinguished from one another. However, classification of left lower limb actions and right lower limb actions between MI, Real Movement (RM), and MO actions, has not been thoroughly explored. To address these questions, we performed a comprehensive experiment to collect EEG under six actions (i.e., Left-MI, Right-MI, Left-RM, Right-RM, Left-MO, and Right-MO) and used three models (convolutional neural network [CNN], support vector machine [SVM], and a K-Nearest Neighbours [KNN]) to classify these actions. Our CNN achieved the highest performance (37.77%) in the classification of six actions. Although the performance of SVM (37.21%) and KNN (25.26%) was worse, it is still better than the chance level (16.67%). Our results suggest that it is possible to distinguish between these six lower limb actions. This study has implications for developing multi-class BCI systems and promoting the research of multiple-action classification
Phase transition of a single star polymer: a Wang-Landau sampling study
Star polymer is a typical nonlinear macromolecule possessing special
thermodynamic behaviors for the existence of a jointing point. The
thermodynamic transitions of a single star polymer are systematically studied
with bond fluctuation model using Wang-Landau sampling technique. A new
analysis method applying the shape factor is proposed to determine coil-globule
(CG) and liquid-crystal (LC) transitions, which shows higher efficiency and
precision than canonical specific heat function. It is found that the LC
transition of star polymer at lower temperature obeys the identical scaling law
as linear polymer. With the increase of the arm density of star polymer,
however, the CG transition point, corresponding to {\theta} temperature, shifts
towards the LC transition and the reason comes from the high density arms of
star polymer, which requires the lower temperature for attracting force to
overcome the volume excluding effects of chain. This work clearly demonstrates
that the distinction of linear and star polymers in structures only affects CG
transition and has no influence on LC transition.Comment: 30 pages, 10 figures, submit to JC
Association between angiotensin-converting enzyme inhibitor-induced cough and the risk of lung cancer: a Mendelian randomization study
Background: Observational studies and meta-analyses have demonstrated a positive correlation between the use of angiotensin-converting enzyme inhibitors (ACEIs) and lung cancer. However, the findings remain controversial; furthermore, the relationship between ACEI-induced cough and lung cancer development remains unknown. We used Mendelian randomization (MR) to verify the association between ACEI use, ACEI-induced cough, and the risk of lung cancer.Methods: We performed a two-sample MR analysis to determine the unconfounded relationships between ACE inhibition, which mimics the effects of ACEIs, and genetic proxies for ACEI-induced cough and lung cancer. Single nucleotide polymorphisms that imitate ACE receptors and ACEI-induced cough were collected and integrated into a meta-analysis of existing genome-wide association studies for various lung cancers. The relationship was quantified using inverse variance weighting, weighted median, and MR-Egger methods.Results: A statistically significant association was observed between ACE inhibition and the risk of small cell lung cancer for Europeans (excluding rs118121655/rs80311894). Associations were identified between ACEI-induced cough and the risk of lung cancer for Europeans, although not for Asians, and between ACEI-induced cough and lung adenocarcinoma (excluding rs360206).Conclusion: Our findings reveal a relationship between ACE inhibition and lung cancer development, as well as a significant association between ACEI-induced cough and a higher risk of lung cancer for Europeans. Patients with hypertension who experience dry cough as a side effect of ACEI use should consider switching to an alternative antihypertensive treatment
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