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The ultimate aim of quantum key distribution (QKD) is improving the transmission distance and key generation speed. Unfortunately, it is believed to be limited by the secret-key capacity of quantum channel without quantum repeater. Recently, a novel twin-field QKD (TF-QKD) is proposed to break through the limit, where the key rate is proportional to the square-root of channel transmittance. Here, by using the vacuum and one-photon state as a qubit, we show that the TF-QKD can be regarded as a measurement-device-independent QKD (MDI-QKD) with single-photon Bell state measurement. Therefore, the MDI property of TF-QKD can be understood clearly. Importantly, the universal security proof theories can be directly used for TF-QKD, such as BB84 encoding, six-state encoding and reference-frame-independent scheme. Furthermore, we propose a feasible experimental scheme for the proof-of-principle experimental demonstration.

Breast cancer is the most prevalent malignancy among women. Although endocrine therapy is effective, the development of endocrine resistance is a major clinical challenge. The tumor microenvironment (TME) promotes tumor malignancy, and tumor‐associated macrophages (TAM) within the TME play a crucial role in endocrine resistance. Herein, we aimed to elucidate the relationship between TAM and the endocrine‐resistant phenotype of breast cancer. Macrophages were cultured with conditioned medium (CM) from tamoxifen‐sensitive (MCF7‐S) or ‐resistant (MCF7‐R) MCF7 breast cancer cells. M2 polarization was detected by CD163 immunofluorescence. To determine the effect on endocrine resistance, MCF7 cells were cultured in the supernatant of different TAM, and then treated with tamoxifen. CC‐chemokine ligand 2 (CCL2) immunohistochemistry was carried out on pathological sections from 100 patients with invasive estrogen receptor‐positive breast cancer. We found that macrophages cultured in the CM of MCF7‐S and MCF7‐R cells were induced into TAM, with a more obvious M2 polarization in the latter. Tamoxifen resistance was increased by culture in TAM medium. TAM secreted CCL2, which increased endocrine resistance in breast cancer cells through activation of the PI3K/Akt/mTOR signaling pathway. High expression of CCL2 was correlated with infiltration of CD163+macrophages (r = 0.548, P < .001), and patients with high CCL2 expression presented shorter progression‐free survival than those with low CCL2 expression (P < .05). We conclude that CCL2 secreted by TAM activates PI3K/Akt/mTOR signaling and promotes an endocrine resistance feedback loop in the TME, suggesting that CCL2 and TAM may be novel therapeutic targets for patients with endocrine‐resistant breast cancer. This study investigated the mechanisms underlying tumor‐associated macrophage (TAM)‐mediated endocrine resistance in breast cancer cells. We found that endocrine‐resistant breast cancer cells can induce M2 polarization of TAM, and M2‐polarized TAM in turn further promote endocrine resistance in breast cancer cells. We believe that this article will be of interest to the readership of this journal because we uncovered the underlying mechanism of TAM‐induced endocrine resistance: TAM secrete the cytokine CCL2, which activates the PI3K/Akt/mTOR signaling pathway.

Autonomous driving perception systems still encounter significant challenges in edge scenarios involving multi-scale target changes and adverse weather, which seriously compromise detection reliability. To address this issue, we introduce a novel edge case dataset that extends existing benchmarks by capturing extreme road conditions (fog, rain, snow, nighttime et al.) with precise annotations, and develop EdgeCaseDNet as an optimized object-detection framework. EdgeCaseDNet’s architecture extends YOLOv8 through four synergistic innovations: (1) a Haar_HGNetv2 backbone that enables hierarchical feature extraction with enhanced long-range dependencies, (2) an asymptotic feature pyramid network for context-aware multi-scale fusion, (3) a hybrid partial depth-wise separable convolution module, and (4) Wise-IoU loss optimization for accelerated convergence. Comprehensive evaluations demonstrated the superiority of EdgeCaseDNet over YOLOv8, achieving improvements of +10.6% in mAP@50, and +8.4% in mAP@[.5:.95]. All the relevant codes are available at https://github.com/yutianku/EdgeCaseDNet .

A record-breaking heavy rainfall event that occurred in Zhengzhou, Henan province during 19–21 July 2021 is simulated using the Weather Research and Forecasting Model, and the large-scale precipitation efficiency (LSPE) and cloud-microphysical precipitation efficiency (CMPE) of the rainfall are analyzed based on the model results. Then, the key physical factors that influenced LSPE and CMPE, and the possible mechanisms for the extreme rainfall over Zhengzhou are explored. Results show that water vapor flux convergence was the key factor that influenced LSPE. Water vapor was transported by the southeasterly winds between Typhoon In-Fa (2021) and the subtropical high, and the southerly flow of Typhoon Cempaka (2021), and converged in Zhengzhou due to the blocking by the Taihang and Funiu Mountains in western Henan province. Strong moisture convergence centers were formed on the windward slope of the mountains, which led to high LSPE in Zhengzhou. From the perspective of CMPE, the net consumption of water vapor by microphysical processes was the key factor that influenced CMPE. Quantitative budget analysis suggests that water vapor was mainly converted to cloud water and ice-phase particles and then transformed to raindrops through melting of graupel and accretion of cloud water by rainwater during the heavy precipitation stage. The dry intrusion in the middle and upper levels over Zhengzhou made the high potential vorticity descend from the upper troposphere and enhanced the convective instability. Moreover, the intrusion of cold and dry air resulted in the supersaturation and condensation of water vapor, which contributed to the heavy rainfall in Zhengzhou.

The function and susceptibility of various drugs are tested with renal proximal tubular epithelial cells; yet, replicating the morphology and kidneys function using the currently available in vitro models remains difficult. To overcome this difficulty, in the study presented in this paper, a device and a three-layer microfluidic chip were developed, which provides a simulated environment for kidney organs. This device includes two parts: (1) microfluidic drug concentration gradient generator and (2) a flow-temperature controlled platform for culturing of kidney cells. In chip study, renal proximal tubular epithelial cells (RPTECs) and peritubular capillary endothelial cells (PCECs) were screened with the drugs to assess the drug-induced nephrotoxicity. Unlike cells cultured in petri dishes, cells cultured in the microfluidic device exhibited higher performance in terms of both cell growth and drug nephrotoxicity evaluation. It is worth mentioning that a significant decrease in cisplatin-induced nephrotoxicity was found because of the intervention of cimetidine in the microfluidic device. In conclusion, the different in the cell performance between the microfluidic device and the petri dishes demonstrates the physiological relevance of the nephrotoxicity screening technology along with the microfluidic device developed in this study. Furthermore, this technology can also facilitate the development of reliable kidney drugs and serve as a useful and efficient test-bed for further investigation of the drug nephrotoxicity evaluation.

Quantum conference key agreement (CKA) enables key sharing among multiple trusted users with information-theoretic security. Currently, the key rates of most quantum CKA protocols suffer from the limit of the total efficiency among quantum channels. Inspired by the coherent one-way and twin-field quantum key distribution (QKD) protocols, we propose a quantum CKA protocol of three users. Exploiting coherent states with intensity 0 and μ to encode logic bits, our protocol can break the limit. Additionally, the requirements of phase randomization and multiple intensity modulation are removed in our protocol, making its experimental demonstration simple.

Large-scale quantum communication networks are still a huge challenge due to the rate-distance limit of quantum key distribution (QKD). Recently, twin-field (TF) QKD has been proposed to overcome this limit. Here, we prove that coherent-state-based TF-QKD is a time-reversed entanglement protocol, where the entanglement generation is realized with entanglement swapping operation via an entangled coherent state measurement. We propose a coherent-state-based TF-QKD with optimal secret key rate under symmetric and asymmetric channels by using coherent state and cat state coding. Furthermore, we show that our protocol can be converted to all recent coherent-state-based TF-QKD protocols by using our security proof. By using the entanglement purification with two-way classical communication, we improve the transmission distance of all coherent-state-based TF-QKD protocols.

To address the multi-objective flexible job shop scheduling problem in rolling production mode (FJSP-RPM), this study proposes a Multi Objective Improved of Salp Swarm Algorithm (MISSA) that simultaneously optimizes equipment utilization and total tardiness. The MISSA generates initial population through various heuristic strategies to improve the initial population quality. The exploitation capability of the algorithm is enhanced through the global crossover strategy and variety of local search strategies. In terms of improvement strategies, the MISSA (using all three strategies) outperforms other incomplete variant algorithms (using only two strategies) in three metrics: Generational Distance (GD), Inverted Generational Distance (IGD), and diversity metric, achieving superior results in 9 test cases, 8 test cases, and 4 test cases respectively. When compared with NSGA2, NSGA3, and SPEA2 algorithms, the MISSA demonstrates advantages in 8 test cases for GD, 8 test cases for IGD, and 7 test cases for the diversity metric. Additionally, the distribution of the obtained solution sets is significantly better than that of the comparative algorithms, which validats the effectiveness of the MISSA in solving FJSP-RPM.

Long-distance quantum key distribution (QKD) has long time seriously relied on trusted relay or quantum repeater, which either has security threat or is far from practical implementation. Recently, a solution called twin-field (TF) QKD and its variants have been proposed to overcome this challenge. However, most security proofs are complicated, a majority of which could only ensure security against collective attacks. Until now, the full and simple security proof can only be provided with asymptotic resource assumption. Here, we provide a composable finite-key analysis for coherent-state-based TF-QKD with rigorous security proof against general attacks. Furthermore, we develop the optimal statistical fluctuation analysis method to significantly improve secret key rate in high-loss regime. The results show that coherent-state-based TF-QKD is practical and feasible, with the potential to apply over nearly one thousand kilometers.

Unmanned ship navigates on the water in an autonomous or semiautonomous way, which can be widely used in maritime transportation, intelligence collection, maritime training and testing, reconnaissance, and evidence collection. In this paper, we use deep reinforcement learning to solve the optimization problem in the path planning and management of unmanned ships. Specifically, we take the waiting time (phase and duration) at the corner of the path as the optimization goal to minimize the total travel time of unmanned ships passing through the path. We propose a new reward function, which considers the environment and control delay of unmanned ships at the same time, which can reduce the coordination time between unmanned ships at the same time. In the simulation experiment, through the quantitative and qualitative results of deep reinforcement learning of unmanned ship navigation and path angle waiting, the effectiveness of our solution is verified.