AMST2: aggregated multi-level spatial and temporal context-based transformer for robust aerial tracking.

Recently, many existing visual trackers have made significant progress by incorporating either spatial information from multi-level convolution layers or temporal information for tracking. However, the complementary advantages of both spatial and temporal information cannot be leveraged when these two types of information are used separately. In this paper, we present a new approach for robust visual tracking using a transformer-based model that incorporates both spatial and temporal context information at multiple levels. To integrate the refined similarity maps through multi-level spatial and temporal encoders, we propose an aggregation encoder. Consequently, the output of the proposed aggregation encoder contains useful features that integrate the global contexts of multi-level spatial and the temporal contexts. The feature we propose offers a contrasting yet complementary representation of multi-level spatial and temporal contexts. This characteristic is particularly beneficial in complex aerial scenarios, where tracking failures can occur due to occlusion, motion blur, small objects, and scale variations. Also, our tracker utilizes a light-weight network backbone, ensuring fast and effective object tracking in aerial datasets. Additionally, the proposed architecture can achieve more robust object tracking against significant variations by updating the features of the latest object while retaining the initial template information. Extensive experiments on seven challenging short-term and long-term aerial tracking benchmarks have demonstrated that the proposed tracker outperforms state-of-the-art tracking methods in terms of both real-time processing speed and performance.

Characterization of Cu2O/CuO heterostructure photocathode by tailoring CuO thickness for photoelectrochemical water splitting.

Cu2O/CuO heterostructure is a well-known strategy to improve the performance of Cu2O photocathodes for photoelectrochemical (PEC) water splitting. The CuO thickness in the Cu2O/CuO heterostructure is considered as a critical factor affecting the PEC performance because it is highly related to the light utilization and charge separation/transport. In this study, the Cu2O/CuO photocathode tailoring the CuO thickness was investigated to examine the CuO thickness influence on the PEC performance. Cu2O/CuO photocathodes were prepared by the electrodeposition and subsequent thermal annealing process and the Cu2O/CuO heterostructure was controlled by the annealing temperature and time. It was demonstrated that the increased CuO thickness enhances the light absorption in the long wavelength region and improves the charge separation by the reinforced band bending. However, the thick CuO hinders the efficient charge transport in the Cu2O/CuO heterostructure, resulting in the decreased PEC performance. Therefore, it is necessary to optimize the CuO thickness for the enhanced PEC performance of Cu2O/CuO photocathodes. Consequently, the Cu2O/CuO photocathode consisting of the similar CuO thickness with its minority carrier diffusion length (∼90 nm) was fabricated by annealing at 350 °C for 20 min, and it shows the optimal PEC performance (-1.2 mA cm-2 at 0 V vs. RHE) in pH 6.5 aqueous solution, resulting from the enhanced light utilization and the reinforced band bending.

Electrocatalytic Properties of Pulse-Reverse Electrodeposited Nickel Phosphide for Hydrogen Evolution Reaction.

Nickel phosphide (Ni-P) films as a catalytic cathode for the hydrogen evolution reaction (HER) of a water splitting were fabricated by a pulse-reverse electrodeposition technique. The electrochemical behaviors for the electrodeposition of Ni-P were investigated by the characterization of peaks in a cyclic voltammogram. The composition of the electrodeposited Ni-P alloys was controlled by adjusting duty cycles of the pulse-reverse electrodeposition. The HER electrocatalytic properties of the Ni-P electrodeposits with an amorphous phase as a function of phosphorous contents existing in Ni-P were electrochemically characterized by the analysis of overpotentials, Tafel slopes, and electrochemical impedance spectrometry. Additionally, the elemental Ni-embedded crystalline Ni3P was prepared by an annealing process with the amorphous Ni69P31 electrodeposit with high contents of phosphorus. The crystalline structure with Ni inclusions in the matrix of Ni3P was formed by the precipitation of excess Ni. The electrocatalytic properties of crystalline Ni3P with elemental Ni inclusions were also investigated by electrochemical characterization.

High-Temperature Carbonized Ceria Thermophotovoltaic Emitter beyond Tungsten.

Thermophotovoltaics (TPVs) require emitters with a regulated radiation spectrum tailored to the spectral response of integrated photovoltaic cells. Such spectrally engineered emitters developed thus far are structurally too complicated to be scalable, are thermally unstable, or lack reliability in terms of temperature cycling. Herein, we report wafer-scale, thermal-stress-free, and wavelength-selective emitters that operate for high-temperature TPVs equipped with GaSb photovoltaic cells. One inch crystalline ceria wafers were prepared by sequentially pressing and annealing the pellets of ceria nanoparticles. The direct pyrolysis of citric acid mixed with ceria nanoparticles created agglomerated, pyrolytic carbon and ceria microscale dots, thus forming a carbonized film strongly adhering to a wafer surface. Depending on the thickness of the carbonized film that was readily tuned based on the amount of citric acid used in the reaction, the carbonized ceria emitter behaved as a tungsten-like emitter, a graphite-like emitter, or their hybrid in terms of the absorptivity spectrum. A properly synthesized carbonized ceria emitter produced a power density of 0.63 W/cm2 from the TPV system working at 900 °C, providing 13 and 9% enhancements compared to tungsten and graphite emitters, respectively. Furthermore, only the carbonized ceria emitter preserved its pristine absorptivity spectrum after a 48 h heating test at 1000 °C. The scalable and facile fabrication of thermostable emitters with a structured spectrum will prompt the emergence of thermal emission-harnessed energy devices.

Uniformity Attentive Learning-Based Siamese Network for Person Re-Identification.

Person re-identification (Re-ID) has a problem that makes learning difficult such as misalignment and occlusion. To solve these problems, it is important to focus on robust features in intra-class variation. Existing attention-based Re-ID methods focus only on common features without considering distinctive features. In this paper, we present a novel attentive learning-based Siamese network for person Re-ID. Unlike existing methods, we designed an attention module and attention loss using the properties of the Siamese network to concentrate attention on common and distinctive features. The attention module consists of channel attention to select important channels and encoder-decoder attention to observe the whole body shape. We modified the triplet loss into an attention loss, called uniformity loss. The uniformity loss generates a unique attention map, which focuses on both common and discriminative features. Extensive experiments show that the proposed network compares favorably to the state-of-the-art methods on three large-scale benchmarks including Market-1501, CUHK03 and DukeMTMC-ReID datasets.

A Case of Community-acquired Bacteremic Empyema Caused by Kocuria kristinae.

Kocuria kristinae, part of the normal flora of the skin and oral mucosa, is seldom reported as a human pathogen; infection is mostly associated with immunocompromised patients in healthcare facilities. Here, we describe the first case of bacteremic empyema caused by K. kristinae acquired from the community. K. kristinae was isolated from pleural effusion and two sets of peripheral blood samples drawn from two different sites. The empyema resolved after the insertion of a chest tube and intravenous administration of piperacillin-tazobactam and levofloxacin.