Towards Accurate One-Stage Object Detection with AP-Loss

One-stage object detectors are trained by optimizing classification-loss and localization-loss simultaneously, with the former suffering much from extreme foreground-background class imbalance issue due to the large number of anchors. This paper alleviates this issue by proposing a novel framework to replace the classification task in one-stage detectors with a ranking task, and adopting the Average-Precision loss (AP-loss) for the ranking problem. Due to its non-differentiability and non-convexity, the AP-loss cannot be optimized directly. For this purpose, we develop a novel optimization algorithm, which seamlessly combines the error-driven update scheme in perceptron learning and backpropagation algorithm in deep networks. We verify good convergence property of the proposed algorithm theoretically and empirically. Experimental results demonstrate notable performance improvement in state-of-the-art one-stage detectors based on AP-loss over different kinds of classification-losses on various benchmarks, without changing the network architectures. Code is available at https://github.com/cccorn/AP-loss.Comment: 13 pages, 7 figures, 4 tables, main paper + supplementary material, accepted to CVPR 201

Generative artificial intelligence-enabled dynamic detection of nicotine-related circuits

The identification of addiction-related circuits is critical for explaining addiction processes and developing addiction treatments. And models of functional addiction circuits developed from functional imaging are an effective tool for discovering and verifying addiction circuits. However, analyzing functional imaging data of addiction and detecting functional addiction circuits still have challenges. We have developed a data-driven and end-to-end generative artificial intelligence(AI) framework to address these difficulties. The framework integrates dynamic brain network modeling and novel network architecture networks architecture, including temporal graph Transformer and contrastive learning modules. A complete workflow is formed by our generative AI framework: the functional imaging data, from neurobiological experiments, and computational modeling, to end-to-end neural networks, is transformed into dynamic nicotine addiction-related circuits. It enables the detection of addiction-related brain circuits with dynamic properties and reveals the underlying mechanisms of addiction

Sphere-shaped Mn3O4 catalyst with remarkable low-temperature activity for Methyl-Ethyl-Ketone combustion

Mn3O4, FeMnOx, and FeOx catalysts synthesized via a solvothermal method were employed for catalytic oxidation of methyl−ethyl−ketone (MEK) at low temperature. Mn3O4 with sphere-like morphology exhibited the highest activity for MEK oxidation, over which MEK was completely oxidized to CO2 at 200 °C, and this result can be comparable to typical noble metal loaded catalysts. The activation energy of MEK over Mn3O4 (30.8 kJ/mol) was much lower than that of FeMnOx (41.5 kJ/mol) and FeOx (47.8 kJ/mol). The dominant planes, surface manganese species ratio, surface-absorbed oxygen, and redox capability played important roles in the catalytic activities of catalysts, while no significant correlation was found between specific surface area and MEK removal efficiency. Mn3O4 showed the highest activity, accounting for abundant oxygen vacancies, low content of surface Mn4+ and strong reducibility. The oxidation of MEK to CO2 via an intermediate of diacetyl is a reaction pathway on Mn3O4 catalyst. Due to high efficiency and low cost, sphere-shaped Mn3O4 is a promising catalyst for VOCs abatement

The emergence of global phase coherence from local pairing in underdoped cuprates

In conventional metal superconductors such as aluminum, the large number of weakly bounded Cooper pairs become phase coherent as soon as they start to form. The cuprate high critical temperature ($T_c$) superconductors, in contrast, belong to a distinctively different category. To account for the high $T_c$, the attractive pairing interaction is expected to be strong and the coherence length is short. Being doped Mott insulators, the cuprates are known to have low superfluid density, thus are susceptible to phase fluctuations. It has been proposed that pairing and phase coherence may occur separately in cuprates, and $T_c$ corresponds to the phase coherence temperature controlled by the superfluid density. To elucidate the microscopic processes of pairing and phase ordering in cuprates, here we use scanning tunneling microscopy to image the evolution of electronic states in underdoped $\rm Bi_2La_xSr_{2-x}CuO_{6+{\delta}}$. Even in the insulating sample, we observe a smooth crossover from the Mott insulator to superconductor-type spectra on small islands with chequerboard order and emerging quasiparticle interference patterns following the octet model. Each chequerboard plaquette contains approximately two holes, and exhibits a stripy internal structure that has strong influence on the superconducting features. Across the insulator to superconductor boundary, the local spectra remain qualitatively the same while the quasiparticle interferences become long-ranged. These results suggest that the chequerboard plaquette with internal stripes plays a crucial role on local pairing in cuprates, and the global phase coherence is established once its spatial occupation exceeds a threshold

Kinerja Sistem Komunikasi FSO (Free Space Optics) Menggunakan Cell-site Diversity Di Daerah Tropis

Kebutuhan masyarakat akan adanya layanan komunikasi multimedia seperti video conference, high speed internet, video streaming, dan lain sebagainya, saat ini terus meningkat. Untuk memenuhi kebutuhan tersebut, perlu adanya suatu sistem komunikasi nirkabel dengan kecepatan tinggi. Salah satunya yaitu dengan menggunakan FSO (Free Space Optics). FSO merupakan sistem komunikasi yang memungkinkan memiliki koneksi layaknya serat optik, namun media transmisi yang digunakan yaitu melalui atmosfer. Penggunaan FSO di daerah tropis memiliki kendala yang cukup serius yaitu tingginya intensitas curah hujan yang dapat mempengaruhi kinerja dari FSO. Semakin tinggi intensitas curah hujan, maka nilai redaman hujan juga semakin besar. Untuk mengatasi dampak redaman hujan tersebut, maka digunakan teknik cell-site diversity dengan selection combining. Penerapan teknik cell-site diversity pada sistem komunikasi FSO menggunakan variasi panjang lintasan 0,5 km, 1 km, 1,5 km, dan 2 km serta variasi sudut antar link sebesar 45°, 90°, 135°, dan 180°. Hasil dari penerapan teknik cell-site diversity menunjukkan bahwa adanya peningkatan kualitas sinyal FSO, dalam hal ini yaitu nilai SNR. Peningkatan nilai SNR terbesar didapatkan pada panjang lintasan 2 km dengan sudut antar link 180° serta pada link availability 99,9 %. Untuk konfigurasi cell-site diversity terbaik didapatkan pada sudut antar link sebesar 90° dan 180°

Emergent normal fluid in the superconducting ground state of overdoped cuprates

The microscopic mechanism for the disappearance of superconductivity in overdoped cuprates is still under heated debate. Here we use scanning tunneling spectroscopy to investigate the evolution of quasiparticle interference phenomenon in $\rm Bi_2Sr_2CuO_{6+\delta}$ over a wide range of hole densities. We find that when the system enters the overdoped regime, a peculiar quasiparticle interference wavevector with quarter-circle pattern starts to emerge even at zero bias, and its intensity grows with increasing doping level. Its energy dispersion is incompatible with the octet model for d-wave superconductivity, but is highly consistent with the scattering interference of gapless normal carriers. The weight of the gapless quasiparticle interference is mainly located at the antinodes and is independent of temperature. We propose that the normal fluid emerges from the pair-breaking scattering between flat antinodal bands in the quantum ground state, which is the primary cause for the reduction of superfluid density and suppression of superconductivity in overdoped cuprates