52 research outputs found
Four-wave mixing with anti-parity-time symmetry in hot Rb vapor
We report an experimental demonstration of anti-parity-time (anti-PT)
symmetric optical four-wave mixing in thermal Rubidium vapor, where the
propagation of two conjugate optical fields in a double- scheme is
governed by a non-Hermitian Hamiltonian. We are particularly interested in
studying quantum intensity correlations between the two conjugate fields near
the exceptional point, taking into account loss and accompanied Langevin noise.
Our experimental measurements of classical four-wave mixing gain and the
associated two-mode relative-intensity squeezing are in reasonable agreement
with the theoretical predictions
Joint Design of Access and Backhaul in Densely Deployed MmWave Small Cells
With the rapid growth of mobile data traffic, the shortage of radio spectrum
resource has become increasingly prominent. Millimeter wave (mmWave) small
cells can be densely deployed in macro cells to improve network capacity and
spectrum utilization. Such a network architecture is referred to as mmWave
heterogeneous cellular networks (HetNets). Compared with the traditional wired
backhaul, The integrated access and backhaul (IAB) architecture with wireless
backhaul is more flexible and cost-effective for mmWave HetNets. However, the
imbalance of throughput between the access and backhaul links will constrain
the total system throughput. Consequently, it is necessary to jointly design of
radio access and backhaul link. In this paper, we study the joint optimization
of user association and backhaul resource allocation in mmWave HetNets, where
different mmWave bands are adopted by the access and backhaul links.
Considering the non-convex and combinatorial characteristics of the
optimization problem and the dynamic nature of the mmWave link, we propose a
multi-agent deep reinforcement learning (MADRL) based scheme to maximize the
long-term total link throughput of the network. The simulation results show
that the scheme can not only adjust user association and backhaul resource
allocation strategy according to the dynamics in the access link state, but
also effectively improve the link throughput under different system
configurations.Comment: 15 page
Hybrid Reluctance Machine with Skewed Permanent Magnets and Zero-Sequence Current Excitation
The reluctance machine is a potential candidate for electrical vehicle propulsion because of its reliable structure, low cost, flexible flux regulation ability, and wide speed range. However, the torque density is unsatisfactory because of the poor excitation ability and low stator core utilization factor. To solve this problem, in this paper, a novel hybrid reluctance machine (HRM) with the skewed permanent magnet (PM) and the zero-sequence current is proposed for electric vehicles. The skewed PM has two magnetomotive force (MMF) components with different functions. The radial MMF component provides extra torque by the flux modulation effect. The tangential MMF component can generate a constant biased field in the stator core to relieve the saturation caused by the zero-sequence current and thus improve the utilization factor of the stator core. Therefore, torque improvement and the relief of stator core saturation can be simultaneously achieved by the skewed PM. In this paper, the machine structure and principle of the proposed machine are introduced. And ultimately, the machine’s electromagnetic performances are evaluated under different PM magnetization directions and zero-sequence current angles by using finite element analysis (FEA)
Sum Rate Maximization under AoI Constraints for RIS-Assisted mmWave Communications
The concept of age of information (AoI) has been proposed to quantify
information freshness, which is crucial for time-sensitive applications.
However, in millimeter wave (mmWave) communication systems, the link blockage
caused by obstacles and the severe path loss greatly impair the freshness of
information received by the user equipments (UEs). In this paper, we focus on
reconfigurable intelligent surface (RIS)-assisted mmWave communications, where
beamforming is performed at transceivers to provide directional beam gain and a
RIS is deployed to combat link blockage. We aim to maximize the system sum rate
while satisfying the information freshness requirements of UEs by jointly
optimizing the beamforming at transceivers, the discrete RIS reflection
coefficients, and the UE scheduling strategy. To facilitate a practical
solution, we decompose the problem into two subproblems. For the first per-UE
data rate maximization problem, we further decompose it into a beamforming
optimization subproblem and a RIS reflection coefficient optimization
subproblem. Considering the difficulty of channel estimation, we utilize the
hierarchical search method for the former and the local search method for the
latter, and then adopt the block coordinate descent (BCD) method to alternately
solve them. For the second scheduling strategy design problem, a low-complexity
heuristic scheduling algorithm is designed. Simulation results show that the
proposed algorithm can effectively improve the system sum rate while satisfying
the information freshness requirements of all UEs
Wave-front reconstruction via single-pixel homodyne imaging
We combine single-pixel imaging and homodyne detection to perform full object recovery (phase and amplitude). Our method does not require any prior information about the object or the illuminating fields. As a demonstration, we reconstruct the optical properties of several semi-transparent objects and find that the reconstructed complex transmission has a phase precision of 0.02 radians and a relative amplitude precision of 0.01.
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Cost-effectiveness of neoadjuvant pembrolizumab plus chemotherapy with adjuvant pembrolizumab for early-stage non-small cell lung cancer in the United States
IntroductionPerioperative (neoadjuvant and adjuvant) pembrolizumab has shown favorable efficacy in patients with early-stage non-small cell lung cancer (NSCLC). This study aims to evaluate the cost-effectiveness of this treatment from the perspective of the United States healthcare payers.MethodsWe established a Markov model to compare the cost-effectiveness of perioperative pembrolizumab with that of neoadjuvant chemotherapy in 21-day cycles, utilizing data from the phase 3 KEYNOTE-671 trial. Additional data were extracted from other publications or online sources. Sensitivity analyses were conducted to evaluate the robustness of the findings. A willingness-to-pay threshold of 224,779.1 and 94,222.29 per QALY gained. The NMB at the WTP threshold at 67,931.3. One-way sensitivity analysis identified the cost of pembrolizumab as the primary factor influencing cost-effectiveness. Probabilistic sensitivity analysis indicated a 97.7% probability of perioperative pembrolizumab being cost-effective at the WTP threshold.ConclusionsFrom the perspective of the United States healthcare payers, perioperative pembrolizumab is a cost-effective treatment for patients with early-stage NSCLC
Spatiotemporal Variation in Driving Factors of Vegetation Dynamics in the Yellow River Delta Estuarine Wetlands from 2000 to 2020
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).Natural Science Foundation of Shandong Province (grant number ZR2022QD118) and the National Natural Science Foundation of China (grant numbers 42201312 and 32271678)Peer ReviewedPrevious studies of vegetation dynamics in the Yellow River Delta (YRD) predominantly relied on sparse time series or coarse-resolution images, which not only overlooked the rapid and spatially heterogeneous changes, but also limited our understanding of driving mechanisms. Here, employing spatiotemporal data fusion methods, we constructed a novel fused enhanced vegetation index (EVI) dataset with a high spatiotemporal resolution (30-meter and 8-day resolution) for the YRD from 2000 to 2020, and we analyzed the vegetation variations and their driving factors within and outside the YRD Nation Natural Reserve (YRDNRR). The fused EVI effectively captured spatiotemporal vegetation dynamics. Notably, within the YRDNRR core area, the fused EVI showed no significant trend before 2010, while a significant increase emerged post-2010, with an annual growth of 7%, the invasion of Spartina alterniflora explained 78% of this EVI increment. In the YRDNRR experimental area, the fused EVI exhibited a distinct interannual trend, which was characterized by an initial increase (2000–2006, p 0.05); the dynamics of the fused EVI were mainly affected by the spring runoff (R2 = 0.71), while in years with lower runoff, it was also affected by the spring precipitation (R2 = 0.70). Outside of the protected area, the fused EVI demonstrated a substantial increase from 2000 to 2010 due to agricultural land expansion and human management practices, followed by stabilization post-2010. These findings enhance our comprehension of intricate vegetation dynamics in the YRD, holding significant relevance in terms of wetland preservation and management
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