1,434 research outputs found
Nonemptiness and Compactness of Solutions Set for Nondifferentiable Multiobjective Optimization Problems
A nondifferentiable multiobjective optimization problem with nonempty set constraints is considered, and the equivalence of weakly efficient solutions, the critical points for the nondifferentiable multiobjective optimization problems, and solutions for vector variational-like inequalities is established under some suitable conditions. Nonemptiness and compactness of the solutions set for the nondifferentiable multiobjective optimization problems are proved by using the FKKM theorem and a fixed-point theorem
The Cu induced ultraflat band in the PbCu(PO)O ()
Based on the first principle calculations, we investigate the geometry and
the electronic structures of the lead apatite with and without the Cu doped.
Our calculations found that without the Cu doping the lead apatite crystal is
an insulator with a flat band above the Fermi lever. Furthermore, our results
indicate that by introducing the O1 vacancies would results in the disappear of
the flat bands in the undopped crystal. While the Cu is doped forming the
LK-99, there exist the ultra-flat bands crossing the Fermi level induced by the
doped Cu atoms, which is due to the hybridization between the d states of the
Cu atoms and the p states of the fully occupied 1/4 occupied O1 atoms.
Moreover, we point out that the hybridization maybe the key for the realization
of the room temperature superconductivity for the LK-99, and a possible
solutions method to improve the quality of the crystal is proposed. Our work
provides a foundation for the future studies on the unique electronic and the
superconductivity properties of the LK-99 crystal.Comment: 8 pages, 7 figure
Magnetic phase transitions in the triangular-lattice spin-1 dimer compound K2Ni2(SeO3)3
In our study, we conduct magnetization and heat capacity measurements to
investigate field-induced magnetic phase transitions within the newly
synthesized compound K2Ni2(SeO3)3, a spin-1 dimer system arranged on a
triangular lattice. The Ni-Ni dimers exhibit a ferromagnetic intra-dimer
interaction, effectively behaving as an ensemble with a total spin of S=2. In
contrast, antiferromagnetic interactions manifest between these dimers on the
triangular lattice. The trigonal distortion of the NiO6 octahedra introduces
easy-axis magnetic anisotropy, accounting for the distinct magnetic phase
diagrams observed when applying c-axis directional and in-plnae magnetic
fields. Notably, our investigation unveils a two-step phase transition with the
magnetic field aligned with the c direction. We propose that the system at the
first transition is from a paramagnetic state to an up-up-down state,
characterized by the Z3 lattice-symmetry breaking. Subsequently, a
Berezinskii-Kosterlitz-Thouless transition, involving the breaking of the
c-axis spin-rotation symmetry, leads to the formation of the "Y state" at low
temperatures. These findings yield valuable insights into the magnetic phase
transitions inherent to geometrically frustrated magnetic systems featuring
dimer structures.Comment: 10 pages, 11 figure
LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving
A map, as crucial information for downstream applications of an autonomous
driving system, is usually represented in lanelines or centerlines. However,
existing literature on map learning primarily focuses on either detecting
geometry-based lanelines or perceiving topology relationships of centerlines.
Both of these methods ignore the intrinsic relationship of lanelines and
centerlines, that lanelines bind centerlines. While simply predicting both
types of lane in one model is mutually excluded in learning objective, we
advocate lane segment as a new representation that seamlessly incorporates both
geometry and topology information. Thus, we introduce LaneSegNet, the first
end-to-end mapping network generating lane segments to obtain a complete
representation of the road structure. Our algorithm features two key
modifications. One is a lane attention module to capture pivotal region details
within the long-range feature space. Another is an identical initialization
strategy for reference points, which enhances the learning of positional priors
for lane attention. On the OpenLane-V2 dataset, LaneSegNet outperforms previous
counterparts by a substantial gain across three tasks, \textit{i.e.}, map
element detection (+4.8 mAP), centerline perception (+6.9 DET), and the
newly defined one, lane segment perception (+5.6 mAP). Furthermore, it obtains
a real-time inference speed of 14.7 FPS. Code is accessible at
https://github.com/OpenDriveLab/LaneSegNet.Comment: Accepted in ICLR 202
All in Tokens: Unifying Output Space of Visual Tasks via Soft Token
Unlike language tasks, where the output space is usually limited to a set of
tokens, the output space of visual tasks is more complicated, making it
difficult to build a unified visual model for various visual tasks. In this
paper, we seek to unify the output space of visual tasks, so that we can also
build a unified model for visual tasks. To this end, we demonstrate a single
unified model that simultaneously handles two typical visual tasks of instance
segmentation and depth estimation, which have discrete/fixed-length and
continuous/varied-length outputs, respectively. We propose several new
techniques that take into account the particularity of visual tasks: 1) Soft
token. We employ soft token to represent the task output. Unlike hard tokens in
the common VQ-VAE which are assigned one-hot to discrete
codebooks/vocabularies, the soft token is assigned softly to the codebook
embeddings. Soft token can improve the accuracy of both the next token
inference and decoding of the task output; 2) Mask augmentation. Many visual
tasks have corruption, undefined or invalid values in label annotations, i.e.,
occluded area of depth maps. We show that a mask augmentation technique can
greatly benefit these tasks. With these new techniques and other designs, we
show that the proposed general-purpose task-solver can perform both instance
segmentation and depth estimation well. Particularly, we achieve 0.279 RMSE on
the specific task of NYUv2 depth estimation, setting a new record on this
benchmark. The general-purpose task-solver, dubbed AiT, is available at
\url{https://github.com/SwinTransformer/AiT}
Neurochemical characterization of pERK-expressing spinal neurons in histamine-induced itch
Date of Acceptance: 08/07/2015 Acknowledgements This work was supported by grants from the Ministry of Science and Technology of China (2012CB966904, 2011CB51005), National Natural Science Foundation of China (31271182, 81200692, 91232724, 81200933, 81101026), Shanghai Natural Science Foundation (12ZR1434300), Key Specialty Construction Project of Pudong Health Bureau of Shanghai (PWZz2013-17), Shenzhen Key Laboratory for Molecular Biology of Neural Development (ZDSY20120617112838879), Fundamental Research Funds for the Central Universities (1500219072) and Sino-UK Higher Education Research Partnership for PhD Studies.Peer reviewedPublisher PD
Bis(μ2-4-amino-3-nitrobenzoato)bis(4-amino-3-nitrobenzoato)octabutyldi-μ3-oxido-tetratin(IV)
The tetranuclear molecules of the title compound, [Sn4(C4H9)8(C7H5N2O4)4O2], reside on a crystallographic inversion center. Both the two independent Sn atoms are five-coordinate, with distorted trigonal–bipyramidal geometries. One Sn atom is coordinated by two O atoms of the carboxylate anions, one bridging O atom and two butyl groups and the other Sn atom is coordinated by an O atom of the carboxylate anion, two bridging O atoms and two butyl groups. All the butyl groups are equatorial with respect to the SnO3 trigonal plane. The molecular structure is stabilized by intramolecular N—H⋯O hydrogen bonds. In the crystal, pairs of intermolecular bifurcated acceptor N—H⋯O and C—H⋯O hydrogen bonds link the molecules into chains along [10]. Weak intermolecular C—H⋯π and π–π interactions [centroid–centroid distance = 3.713 (2) Å] are also observed
Modified Glucose-Insulin-Potassium Regimen Provides Cardioprotection With Improved Tissue Perfusion in Patients Undergoing Cardiopulmonary Bypass Surgery
Background Laboratory studies demonstrate glucose-insulin-potassium (GIK) as a potent cardioprotective intervention, but clinical trials have yielded mixed results, likely because of varying formulas and timing of GIK treatment and different clinical settings. This study sought to evaluate the effects of modified GIK regimen given perioperatively with an insulin-glucose ratio of 1:3 in patients undergoing cardiopulmonary bypass surgery. Methods and Results In this prospective, randomized, double-blinded trial with 930 patients referred for cardiac surgery with cardiopulmonary bypass, GIK (200 g/L glucose, 66.7 U/L insulin, and 80 mmol/L KCl) or placebo treatment was administered intravenously at 1 mL/kg per hour 10 minutes before anesthesia and continuously for 12.5 hours. The primary outcome was the incidence of in-hospital major adverse cardiac events including all-cause death, low cardiac output syndrome, acute myocardial infarction, cardiac arrest with successful resuscitation, congestive heart failure, and arrhythmia. GIK therapy reduced the incidence of major adverse cardiac events and enhanced cardiac function recovery without increasing perioperative blood glucose compared with the control group. Mechanistically, this treatment resulted in increased glucose uptake and less lactate excretion calculated by the differences between arterial and coronary sinus, and increased phosphorylation of insulin receptor substrate-1 and protein kinase B in the hearts of GIK-treated patients. Systemic blood lactate was also reduced in GIK-treated patients during cardiopulmonary bypass surgery. Conclusions A modified GIK regimen administered perioperatively reduces the incidence of in-hospital major adverse cardiac events in patients undergoing cardiopulmonary bypass surgery. These benefits are likely a result of enhanced systemic tissue perfusion and improved myocardial metabolism via activation of insulin signaling by GIK. Clinical Trial Registration URL: clinicaltrials.gov. Identifier: NCT01516138
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