Deterministic realization of collective measurements via photonic quantum walks

Collective measurements on identically prepared quantum systems can extract more information than local measurements, thereby enhancing information-processing efficiency. Although this nonclassical phenomenon has been known for two decades, it has remained a challenging task to demonstrate the advantage of collective measurements in experiments. Here we introduce a general recipe for performing deterministic collective measurements on two identically prepared qubits based on quantum walks. Using photonic quantum walks, we realize experimentally an optimized collective measurement with fidelity 0.9946 without post selection. As an application, we achieve the highest tomographic efficiency in qubit state tomography to date. Our work offers an effective recipe for beating the precision limit of local measurements in quantum state tomography and metrology. In addition, our study opens an avenue for harvesting the power of collective measurements in quantum information processing and for exploring the intriguing physics behind this power.Comment: Close to the published versio

DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning

Federated learning (FL) has emerged as a powerful paradigm for learning from decentralized data, and federated domain generalization further considers the test dataset (target domain) is absent from the decentralized training data (source domains). However, most existing FL methods assume that domain labels are provided during training, and their evaluation imposes explicit constraints on the number of domains, which must strictly match the number of clients. Because of the underutilization of numerous edge devices and additional cross-client domain annotations in the real world, such restrictions may be impractical and involve potential privacy leaks. In this paper, we propose an efficient and novel approach, called Disentangled Prompt Tuning (DiPrompT), a method that tackles the above restrictions by learning adaptive prompts for domain generalization in a distributed manner. Specifically, we first design two types of prompts, i.e., global prompt to capture general knowledge across all clients and domain prompts to capture domain-specific knowledge. They eliminate the restriction on the one-to-one mapping between source domains and local clients. Furthermore, a dynamic query metric is introduced to automatically search the suitable domain label for each sample, which includes two-substep text-image alignments based on prompt tuning without labor-intensive annotation. Extensive experiments on multiple datasets demonstrate that our DiPrompT achieves superior domain generalization performance over state-of-the-art FL methods when domain labels are not provided, and even outperforms many centralized learning methods using domain labels

A Project-based Quantification of BIM Benefits

In the construction industry, research is being carried out to look for feasible methods and technologies to cut down project costs and waste. Building Information Modelling (BIM) is certainly currently a promising technology/method that can achieve this. The output of the construction industry has a considerable scale; however, the concentration of the industry and the level of informatization are still not high. There is still a large gap in terms of productivity between the construction industry and other industries. Due to the lack of first-hand data regarding how much of an effect can be genuinely had by BIM in real cases, it is unrealistic for construction stakeholders to take the risk of widely adopting BIM. This paper focuses on the methodological quantification (through a case study approach) of BIM’s benefits in building construction resource management and real-time costs control, in contrast to traditional non-BIM technologies. Through the use of BIM technology for the dynamic querying and statistical analysis of construction schedules, engineering, resources and costs, the three implementations considered demonstrate how BIM can facilitate the comprehensive grasp of a project’s implementation and progress, identify and solve the contradictions and conflicts between construction resources and costs controls, reduce project over-spends and protect the supply of resources

Changes in lymphocyte subsets in patients with Guillain-Barré syndrome treated with immunoglobulin

BACKGROUND: Guillain-Barré syndrome (GBS) is an autoimmune condition characterized by peripheral neuropathy. The pathogenesis of GBS is not fully understood, and the mechanism of how intravenous immunoglobulin (IVIG) cures GBS is ambiguous. Herein, we investigated lymphocyte subsets in patients with two major subtypes of GBS (acute inflammatory demyelinating polyneuropathy, AIDP, and acute motor axonal neuropathy, AMAN) before and after treatment with IVIG, and explored the possible mechanism of IVIG action. METHODS: Sixty-four patients with GBS were selected for our study and divided into two groups: AIDP (n = 38) and AMAN (n = 26). Thirty healthy individuals were chosen as the control group. Relative counts of peripheral blood T and B lymphocyte subsets were detected by flow cytometry analysis. RESULTS: In the AIDP group, the percentage of CD4(+)CD45RO(+) T cells was significantly higher, while the percentage of CD4(+)CD45RA(+) T cells was notably lower, than in the control group. After treatment with IVIG, the ratio of CD4(+)/CD8(+) T cells and the percentage of CD4(+)CD45RA(+) T cells increased, while the percentages of CD8(+) T cells and CD4(+)CD45RO(+) T cells decreased significantly, along with the number of CD19(+) B cells. However, there were not such obvious changes in the AMAN group. The Hughes scores were significantly lower in both the AIDP and AMAN groups following treatment with IVIG, but the changes in Hughes scores showed no significant difference between the two groups. CONCLUSIONS: This study suggested that the changes in T and B-lymphocyte subsets, especially in CD4(+)T-lymphocyte subsets, might play an important role in the pathogenesis of AIDP, and in the mechanism of IVIG action against AIDP

Enhancing Cell Proliferation and Migration by MIR-Carbonyl Vibrational Coupling: Insights from Transcriptome Profiling

Cell proliferation and migration highly relate to normal tissue self-healing, therefore it is highly significant for artificial controlling. Recently, vibrational strong coupling between biomolecules and Mid-infrared (MIR) light photons has been successfully used to modify in vitro bioreactions, neuronal signaling and even animal behavior. However, the synergistic effects from molecules to cells remains unclear, and the regulation of MIR on cells needs to be explained from the molecular level. Herein, the proliferation rate and migration capacity of fibroblasts were increased by 156% and 162.5%, respectively, by vibratory coupling of 5.6 micrometers photons with carbonyl groups in biomolecules. Through transcriptome sequencing analysis, the regulatory mechanism of infrared light in 5.6 micrometers was explained from the level of signal pathway and cell components. 5.6 micrometers optical high power lasers can regulate cell function through vibrational strong coupling while minimizing photothermal damage. This work not only sheds light on the non-thermal effect on MIR light-based on wound healing, but also provides new evidence to future frequency medicine.Comment: 20 pages, 5 figure