作者机构：
[Li, Yong; Lou, Ruitao] Hohai Univ, Coll Environm, Key Lab Integrated Regulat & Resource Dev Shallow, Minist Educ, Nanjing, Jiangsu, Peoples R China.;[Jiang, Qianjing; Lou, Ruitao; He, Yong; Wu, Qingguan] Zhejiang Univ, Biosyst Engn, Hangzhou, Zhejiang, Peoples R China.;[Li, Yong] Hohai Univ, Natl Engn Res Ctr Water Resources Efficient Utiliz, Nanjing, Jiangsu, Peoples R China.;[Liu, Ying] Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess Pl, Yangling, Peoples R China.;[Liu, Ji] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.
通讯机构：
[Jiang, QJ ] Z;[Li, Y ] H;Hohai Univ, Coll Environm, Key Lab Integrated Regulat & Resource Dev Shallow, Minist Educ, Nanjing, Jiangsu, Peoples R China.;Zhejiang Univ, Biosyst Engn, Hangzhou, Zhejiang, Peoples R China.
关键词：
Green manure;Greenhouse gas;Methane;Nitrous oxide;Global warming potential intensity
摘要：
Green manure is a widely applied to increase grain yield, while it also attributes to greenhouse gas (GHG) emissions in agriculture ecosystems. Combining green manure with inorganic fertilizer inputs is a common practice that can influence soil GHG emissions and grain yield, however, its impacts on grain yield and global warming potential (GWP) under different initial soil conditions before rotating experiments and agronomic management in paddy fields remain unclear. We synthesized 508 data pairs to evaluate the responses of CO2 emissions, CH4 emissions, N2O emissions, and grain yield to combined inputs of green manure plus inorganic fertilizer compared with only inorganic fertilizer application. Our findings indicate that both inorganic fertilizer plus extra green manure (GM-E) and green manure substitutes for inorganic fertilizer (GM-S) could increase CO2 emissions (22.5 %-76.8 %), CH4 emissions (100 %-103 %), N2O emissions (29.8 %-50.9 %), and yield (2.21 %-19.6 %). Except for GM-E, which showed a non-significant increase in grain yield. The initial soil properties before rotating experiments, the types and timing of green manure application were key drivers of GHG emissions and yield, and extra green manure applied in areas with low initial soil pH and high C:N can increase GWP and yield. Overall, the mixed green manure application had greater impact than leguminous or non-leguminous green manure applied alone. The responses of GHG emissions and yield to GM-S were modulated by mean annual precipitation and initial soil properties before rotating experiments, and green manure substitutes for inorganic fertilizer in areas with high initial soil pH and low C:N can increase GWP and yield. Meanwhile, excessive precipitation caused a reduction in yield and a significant increase in GWP intensity. Our results showed that extra green manure applications of less than 68.1 kg N ha-1 would not significantly increase GWP. Therefore, an effective green manure strategy can achieve a win-win situation for the dual challenge of agricultural production and climate change mitigation.
作者机构：
[Belmonta, Ron] Univ North Carolina Greensboro, Greensboro, NC USA.;[Brewer, Jasmine; Mazeliauskas, Aleksas] CERN, Geneva, Switzerland.;[Brodskyc, Quinn; Rajagopal, Krishna] MIT, Cambridge, MA USA.;[Caucal, Paul] Univ Nantes, SUBATECH, IMT Atlantique, IN2P3 CNRS, Nantes, France.;[Connors, Megan] Georgia State Univ, Atlanta, GA USA.
通讯机构：
[Perepelitsat, DV ] U;Univ Colorado, Boulder, CO 80309 USA.
关键词：
Relativistic Heavy Ion Collider;Heavy-ion collisions;Quark-gluon plasma;Jet quenching;Heavy flavor;Thermalization
摘要：
sPHENIX is a next -generation detector experiment at the Relativistic Heavy Ion Collider, designed for a broad set of jet and heavy -flavor probes of the Quark -Gluon Plasma created in heavy ion collisions. In anticipation of the commissioning and first data -taking of the detector in 2023, a RIKEN-BNL Research Center (RBRC) workshop was organized to collect theoretical input and identify compelling aspects of the physics program. This paper compiles theoretical predictions from the workshop participants for jet quenching, heavy flavor and quarkonia, cold QCD, and bulk physics measurements at sPHENIX.
摘要：
Currently, most fatigue driving detection methods rely on complex neural networks whose feasibility in hardware implementation needs to be further improved. This paper proposes an embedded device-oriented fatigue driving detection method based on a lightweight YOLOv5s. Firstly, a YOLOv5s face detection network with a parametric-free attention mechanism is designed to enhance the focus on face regions during face detection. Then, a practical facial landmark detector model is improved by integrating multi-scale feature fusion with Ghost module, which can adapt to the variations brought by different scale targets. Next, a fatigue determination approach is investigated by using multiple features of the face. Finally, experiments of the proposed detection model with the public YawDD dataset are implemented on the PC platform and the embedded device, respectively. The experimental results demonstrate that the proposed method achieves a detection accuracy of 95.3% and a processing speed of 22FPS on the PC platform. Meanwhile, the hardware test on an Orange Pi5 embedded device achieves a detection accuracy of 93.3% and a processing speed of 12FPS, which has good prospects for applications.
期刊：
Journal of Functional Analysis,2024年286(3):110243 ISSN：0022-1236
通讯作者：
Guo, YJ;Li, Y
作者机构：
[Guo, Yujin; Luo, Yong] Cent China Normal Univ, Sch Math & Stat, Minist Educ, POB 71010, Wuhan 430079, Peoples R China.;[Guo, Yujin] Cent China Normal Univ, Key Lab Nonlinear Anal & Applicat, Minist Educ, POB 71010, Wuhan 430079, Peoples R China.;[Li, Yan] Cent China Normal Univ, Sch Math & Stat, POB 71010, Wuhan 430079, Peoples R China.;[Luo, Yong] Cent China Normal Univ, Hubei Key Lab Math Sci, POB 71010, Wuhan 430079, Peoples R China.
通讯机构：
[Li, Y ; Guo, YJ ] C;Cent China Normal Univ, Sch Math & Stat, Minist Educ, POB 71010, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Key Lab Nonlinear Anal & Applicat, Minist Educ, POB 71010, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Sch Math & Stat, POB 71010, Wuhan 430079, Peoples R China.
摘要：
This paper is concerned with ground states of attractive Bose gases confined in an anharmonic trap V(x) = omega(vertical bar x vertical bar(2)+ k vertical bar x vertical bar(4)) rotating at the velocity Omega > 0, where omega > 0 denotes the trapping frequency, and k > 0 represents the strength of the quartic term. It is known that for any Omega > 0, ground states exist in such traps if and only if 0 < a < a*, where a*:= parallel to Q parallel to(2)(2) and Q > 0 is the unique positive solution of Delta Q - Q + Q(3)= 0 in R-2. By analyzing the refined energies and expansions of ground states, we prove that there exists a constant C > 0, independent of 0 < a < a*, such that ground states do not have any vortex in the region R(a) := {x is an element of R-2 : vertical bar x vertical bar <= C(a* - a)(-1-6 beta 20)} as a NE arrow a*, for the case where omega= 3 Omega(2)/4, k = 1/6, and Omega = C-0(a*- a)(-beta) varies for some beta is an element of[0, 1/6) and C-0 > 0. (c) 2023 Elsevier Inc. All rights reserved.
作者机构：
[Wu, Yanwen; Cao, Shuangshuang; Ma, Yanmei; Ge, Di] Cent China Normal Univ, Sch Phys Sci & Technol, Wuhan 430079, Peoples R China.;[Cheng, Yuhang] Shaanxi GSXZ Technol Co Ltd, Xian 710018, Peoples R China.;[Wu, Yanwen] Cent China Normal Univ, Natl Digital Learning Engn Technol Res Ctr, Wuhan 430079, Peoples R China.
通讯机构：
[Wu, YW ] C;Cent China Normal Univ, Sch Phys Sci & Technol, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Natl Digital Learning Engn Technol Res Ctr, Wuhan 430079, Peoples R China.
关键词：
Anomaly detection;Multivariate time-series;Spatiotemporal;Abnormal information expression;Graph contrastive learning
摘要：
The detection of anomalies in high-dimensional time-series has always played a crucial role in the domain of system security. Recently, with rapid advancements in transformer model and graph neural network (GNN) technologies, spatiotemporal modeling approaches for anomaly detection tasks have been greatly improved. However, most methods focus on optimizing upstream time-series prediction tasks by leveraging joint spatiotemporal features. Through experiments, we found that this modeling approach not only risks the loss of some original anomaly information during data preprocessing, but also focuses on optimizing the performance of the upstream prediction task and does not directly enhance the performance of the downstream detection task. We propose a spatiotemporal anomaly detection model that incorporates an improved attention mechanism in the process of temporal modeling. We adopt a heterogeneous graph contrastive learning approach in spatio modeling to compensate for the representation of anomalous behavioral information, thereby guiding the model through thorough training. Through validation on two widely used real-world datasets, we demonstrate that our model outperforms baseline methods. We also explore the impact of multivariate time-series prediction tasks on the detection task, and visualize the reasons behind the benefits gained by our model.
通讯机构：
[Gu, WJ ] Y;[Li, GX ] H;Yangtze Univ, Sch Phys & Optoelect Engn, Jingzhou 434023, Peoples R China.;Huazhong Normal Univ, Dept Phys, Wuhan 430079, Peoples R China.
摘要：
We investigate the scattering processes of two photons in a one-dimensional waveguide coupled to two giant atoms. By adjusting the accumulated phase shifts between the coupling points, we are able to effectively manipulate the characteristics of these scattering photons. Utilizing the Lippmann-Schwinger formalism, we derive analytical expressions for the wave functions describing two-photon interaction in separate, braided, and nested configurations. Based on these wave functions, we also obtain analytical expressions for the incoherent power spectra and second-order correlation functions. In contrast to small atoms, the incoherent spectrum, which is defined by the correlation of the bound state, can exhibit more tunability due to the phase shifts. Additionally, the second-order correlation functions in the transmission and reflection fields could be tuned to exhibit either bunching or antibunching upon resonant driving. These unique features offered by the giant atoms in waveguide QED could benefit the generation of nonclassical itinerant photons in quantum networks.
期刊：
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS,2024年:1-14 ISSN：1951-6355
通讯作者：
Ya Jia
作者机构：
[Qianming Ding; Yong Wu; Weifang Huang; Ya Jia] Department of Physics, Central China Normal University, Wuhan, China
通讯机构：
[Ya Jia] D;Department of Physics, Central China Normal University, Wuhan, China
摘要：
The mathematical optimization techniques may control the network to target firing patterns by adjusting the weights of network nodes. Inspired by the dynamics of dynamical learning, we recently proposed a technique for dynamic learning of synchronous (DLS) to control the firing state of neural networks. In this study, we apply the DLS technique to a Hodgkin–Huxley-style neural network, and investigate in regular, random, small-world and scale-free networks. We use the DLS technique to accomplish the network adaptive global synchronization, adaptive local synchronization, and phase locking with a single supervisory node. Furthermore, we investigated the robustness of the DLS technique in noisy environments and find that the DLS technique demonstrates remarkable effectiveness even in the presence of weak noise. However, in scenarios with stronger noise, there is a trade-off between optimizing training and avoiding overfitting, i.e., a too narrow weight adjustment range may hinder training effectiveness, while an excessively wide range results in abnormal node firing dynamics. We expect the DLS technique to be potentially valuable for more studies of nonlinear systems.
