Finite temperature damping of collective modes of a BCS-BEC crossover superfluid

A new mechanism is proposed to explain the puzzling damping of collective excitations, which was recently observed in the experiments of strongly interacting Fermi gases below the superfluid critical temperature on the fermionic (BCS) side of Feshbach resonance. Sound velocity, superfluid density and damping rate are calculated with effective field theory. We find that a dominant damping process is due to the interaction between superfluid phonons and thermally excited fermionic quasiparticles, in contrast to the previously proposed pair-breaking mechanism. Results from our effective model are compared quantitatively with recent experimental findings, showing a good agreement.Comment: final version, 9 pages, 4 figure

Stripe, checkerboard, and liquid-crystal ordering from anisotropic p-orbital Fermi surfaces in optical lattices

We study instabilities of single-species fermionic atoms in the p-orbital bands in two-dimensional optical lattices at noninteger filling against interactions. Charge density wave and orbital density wave orders with stripe or checkerboard patterns are found for attractive and repulsive interactions, respectively. The superfluid phase, usually expected of attractively interacting fermions, is strongly suppressed. We also use field theory to analyze the possible phase-transitions from orbital stripe order to liquid-crystal phases and obtain the phase diagram. The condition of nearly-perfect Fermisurface nesting, which is key to the above results, is shown robustly independent of fermion fillings in such p-orbital systems, and the $(2k_F,\pm2k_F)$ momentum of density wave oscillation is highly tunable. Such remarkable features show the promise of making those exotic orbital phases, which are of broad interest in condensed-matter physics, experimentally realizable with optical lattice gases.Comment: final version, 8 pages, 5 figure

Consistency and Consensus Driven for Hesitant Fuzzy Linguistic Decision Making with Pairwise Comparisons

Hesitant fuzzy linguistic preference relation (HFLPR) is of interest because it provides an efficient way for opinion expression under uncertainty. For enhancing the theory of decision making with HFLPR, the paper introduces an algorithm for group decision making with HFLPRs based on the acceptable consistency and consensus measurements, which involves (1) defining a hesitant fuzzy linguistic geometric consistency index (HFLGCI) and proposing a procedure for consistency checking and inconsistency improving for HFLPR; (2) measuring the group consensus based on the similarity between the original individual HFLPRs and the overall perfect HFLPR, then establishing a procedure for consensus ensuring including the determination of decision-makers weights. The convergence and monotonicity of the proposed two procedures have been proved. Some experiments are furtherly performed to investigate the critical values of the defined HFLGCI, and comparative analyses are conducted to show the effectiveness of the proposed algorithm. A case concerning the performance evaluation of venture capital guiding funds is given to illustrate the availability of the proposed algorithm. As an application of our work, an online decision-making portal is finally provided for decision-makers to utilize the proposed algorithms to solve decision-making problems.Comment: Pulished by Expert Systems with Applications (ISSN: 0957-4174

Time reversal symmetry breaking of pp-orbital bosons in a one-dimensional optical lattice

We study bosons loaded in a one-dimensional optical lattice of two-fold $p$-orbital degeneracy at each site. Our numerical simulations find an anti-ferro-orbital p$_x$+ip$_y$, a homogeneous p$_x$ Mott insulator phase and two kinds of superfluid phases distinguished by the orbital order (anti-ferro-orbital and para-orbital). The anti-ferro-orbital order breaks time reversal symmetry. Experimentally observable evidence is predicted for the phase transition between the two different superfluid phases. We also discover that the quantum noise measurement is able to provide a concrete evidence of time reversal symmetry breaking in the first Mott phase.Comment: 4+ pages, version accepted by Phys. Rev. Let

Masked Vision and Language Pre-training with Unimodal and Multimodal Contrastive Losses for Medical Visual Question Answering

Medical visual question answering (VQA) is a challenging task that requires answering clinical questions of a given medical image, by taking consider of both visual and language information. However, due to the small scale of training data for medical VQA, pre-training fine-tuning paradigms have been a commonly used solution to improve model generalization performance. In this paper, we present a novel self-supervised approach that learns unimodal and multimodal feature representations of input images and text using medical image caption datasets, by leveraging both unimodal and multimodal contrastive losses, along with masked language modeling and image text matching as pretraining objectives. The pre-trained model is then transferred to downstream medical VQA tasks. The proposed approach achieves state-of-the-art (SOTA) performance on three publicly available medical VQA datasets with significant accuracy improvements of 2.2%, 14.7%, and 1.7% respectively. Besides, we conduct a comprehensive analysis to validate the effectiveness of different components of the approach and study different pre-training settings. Our codes and models are available at https://github.com/pengfeiliHEU/MUMC.Comment: accepted by MICCAI202

Research on unsteady performance of a two-stage self-priming centrifugal pump

In order to study the unsteady performance of a two-stage self-priming centrifugal pump, the unsteady numerical calculation in a two-stage self-priming centrifugal pump was performed and energy characteristics experiments and self-priming experiments were carried out. The pressure pulsation and radial force in the pump were then analyzed. The results show that numerical calculation values are close to the experiment values. Head deviation of the pump is less than 3 %, and efficiency deviation of the pump is less than 2 percentage points. Compared with monitoring point P1, the pressure fluctuation coefficient of monitoring point P3 at the design flow rate is reduced by 61 %. Compared with monitoring point P8, the pressure fluctuation coefficient of monitoring point P5 is reduced by 70 %. The radial force on the radial guide-vane is obviously smaller than that on the volute. Under the same flow rate, radial force on the volute of second-stage pump is almost 20 times larger than that on the radial guide-van of first-stage pump

An Integration Mechanism between Demand and Supply Side Management of Electricity Markets

One of the main challenges in the emerging smart grid is to jointly consider the demand and supply, which is also reflected in the wholesale market (supply side) and the retail market (demand side). When integrating the demand and supply side into one framework, the mechanism for determining the market clearing price has been changed. This is due to the demand variations in the demand side in response to the market clearing price and the change of generation costs in the supply side from the demand variation. In order to find the best balance between the supply and demand under the demand response management scheme, this paper proposes a new integrated supply and demand coordination mechanism for the electricity market and smart pricing methods for generator and retailers. Another important contribution of this paper is to develop an efficient algorithm to find the match equilibrium between the demand and supply sides in the new proposed mechanism. Experimental results demonstrate that the new mechanism can effectively handle unpredictable demand under dynamic retail pricing and support the ISO to dispatch the generation economically. It can also help in achieving the goals of dynamic pricing such as maximizing the profits for retailers

Exceptional Performance of Hierarchical Ni-Fe (hydr)oxide@NiCu Electrocatalysts for Water Splitting

Developing low‐cost bifunctional electrocatalysts with superior activity for both the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is of great importance for the widespread application of the water splitting technique. In this work, using earth‐abundant transition metals (i.e., nickel, iron, and copper), 3D hierarchical nanoarchitectures, consisting of ultrathin Ni–Fe layered‐double‐hydroxide (Ni–Fe LDH) nanosheets or porous Ni–Fe oxides (NiFeOx) assembled to a metallic NiCu alloy, are delicately constructed. In alkaline solution, the as‐prepared Ni–Fe LDH@NiCu possesses outstanding OER activity, achieving a current density of 10 mA cm−2 at an overpotential of 218 mV, which is smaller than that of RuO2 catalyst (249 mV). In contrast, the resulting NiFeOx@NiCu exhibits better HER activity, yielding a current density of 10 mA cm−2 at an overpotential of 66 mV, which is slightly higher than that of Pt catalyst (53 mV) but superior to all other transition metal (hydr)oxide‐based electrocatalysts. The remarkable activity of the Ni–Fe LDH@NiCu and NiFeOx@NiCu is further demonstrated by a 1.5 V solar‐panel‐powered electrolyzer, resulting in current densities of 10 and 50 mA cm−2 at overpotentials of 293 and 506 mV, respectively. Such performance renders the as‐prepared materials as the best bifunctional electrocatalysts so far