An acousto-optic modulator based bi-frequency interferometer for quantum technology

Acousto-optic modulators (AOMs) have been widely used in quantum optical technology, but the non-ideal diffraction efficiency limits its application in a quantum system. Here we demonstrate a bi-frequency interferometer using AOMs as both the beam-splitter and the beam-combiner. The intensity of the input light can be as low as the single photon level, and the interferometer can work in a chopped phase locking mode. The modulation for the phase locking scheme is realized on the beam-splitting AOM driven by specially designed radio frequency signal, which avoids using extra optical modulators and makes the quantum efficiency of the system as high as $(95\pm1)\%$. By optimizing the factors that affect the mode matching, the visibility of the beating signal for the interferometer is $(99.5\pm0.2)\%$. This near prefect visibility allows the interferometer to be applied in high efficiency quantum technical schemes while leaving the diffraction efficiencies of each AOM for about $50\%$. This greatly reduced the demand for the driving of AOMs.Comment: 6 pages, 4 figure

Construction of trace element in coal of China Database Management System: based on WebGIS

The combination of geographic information system and mineral energy data management is helpful to promote the study of mineral energy and its ecological damage and environmental pollution caused by its development and utilization, which has important application value. The Trace Elements in Coal of China Database Management System (TECC) is established in this paper, applying the techniques of B/S three-layer structure, Oracle database, AJAX and WebGIS. TECC is the first database system which aims at managing the data of trace elements in coal in China. It includes data management and analysis module, document management module, trace elements in coal data maintenance module and authority management module. The data entry specification is put forward in the present study and the spatial data is included in TECC system. The system achieves the functions of data query, analysis, management, maintenance and map browsing, thematic map drawing as well as satellite video display, which lay the foundation for the analysis of large data of trace elements in coal. It is a practical platform for the acquisition, management, exchange and sharing of trace element research and geochemical research data of coal

RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmark

Ophthalmologists have used fundus images to screen and diagnose eye diseases. However, different equipments and ophthalmologists pose large variations to the quality of fundus images. Low-quality (LQ) degraded fundus images easily lead to uncertainty in clinical screening and generally increase the risk of misdiagnosis. Thus, real fundus image restoration is worth studying. Unfortunately, real clinical benchmark has not been explored for this task so far. In this paper, we investigate the real clinical fundus image restoration problem. Firstly, We establish a clinical dataset, Real Fundus (RF), including 120 low- and high-quality (HQ) image pairs. Then we propose a novel Transformer-based Generative Adversarial Network (RFormer) to restore the real degradation of clinical fundus images. The key component in our network is the Window-based Self-Attention Block (WSAB) which captures non-local self-similarity and long-range dependencies. To produce more visually pleasant results, a Transformer-based discriminator is introduced. Extensive experiments on our clinical benchmark show that the proposed RFormer significantly outperforms the state-of-the-art (SOTA) methods. In addition, experiments of downstream tasks such as vessel segmentation and optic disc/cup detection demonstrate that our proposed RFormer benefits clinical fundus image analysis and applications. The dataset, code, and models are publicly available at https://github.com/dengzhuo-AI/Real-FundusComment: IEEE J-BHI 2022; The First Benchmark and First Transformer-based Method for Real Clinical Fundus Image Restoratio

High CD8+tumor-infiltrating lymphocytes indicate severe exhaustion and poor prognosis in angioimmunoblastic T-cell lymphoma

BackgroundExhaustion of CD8+ tumor-infiltrating lymphocytes (TILs), characterized by the overexpression of immune checkpoints (IC), is a major impediment to anti-tumor immunity. However, the exhaustion status of CD8+TILs in angioimmunoblastic T cell lymphoma (AITL) remains unclear. Therefore, we aimed to elucidate the exhaustion status of CD8+TILs in AITL and its influence on prognosis.MethodsThe correlation between CD8+TILs and IC expression in AITL was analyzed using single-cell RNA sequencing (n = 2), flow cytometry (n = 20), and RNA sequencing (n = 20). Biological changes related to CD8+TILs exhaustion at different cytotoxic T lymphocyte (CTL) levels (mean expression levels of CD8A, CD8B, GZMA, GZMB, and PRF1) in AITL were evaluated using RNA sequencing (n = 20) and further validated using the GEO dataset (n = 51). The impact of CD8 protein expression and CTL levels on patient prognosis was analyzed using flow cytometry and RNA sequencing, respectively.ResultsOur findings demonstrated that the higher the infiltration of CD8+TILs, the higher was the proportion of exhausted CD8+TILs characterized by the overexpression of multiple IC. This was accompanied by extensive exhaustion-related biological changes, which suggested severe exhaustion in CD8+TILs and may be one of the main reasons for the poor prognosis of patients with high CD8+TILs and CTL.ConclusionOur study comprehensively reveals the exhaustion status of CD8+TILs and their potential negative impact on AITL prognosis, which facilitates further mechanistic studies and is valuable for guiding immunotherapy strategies

Hcverso1 and 2: Faldaprevir with deleobuvir (BI 207127) and ribavirin for treatment-naïve patients with chronic hepatitis C virus genotype-1b infection

he interferon-free combination of once-daily faldaprevir 120 mg, twice-daily deleobuvir 600 mg, and weight-based ribavirin was evaluated in two Phase III studies (HCVerso1, HCVerso2) in hepatitis C virus genotype-1b-infected, treatment-naïve patients, including those ineligible for peginterferon (HCVerso2). Patients without cirrhosis were randomized to 16 weeks (Arm 1; n=208 HCVerso1, n=213 HCVerso2) or 24 weeks (Arm 2; n=211 in both studies) of faldaprevir + deleobuvir + ribavirin. Patients with compensated cirrhosis received open-label faldaprevir + deleobuvir + ribavirin for 24 weeks (Arm 3; n=51, n=72). Primary endpoints were comparisons of adjusted sustained virologic response (SVR) rates with historical rates: 71% (HCVerso1) and 68% (HCVerso2). Adjusted SVR12 rates were significantly greater than historical controls for Arms 1 and 2 in HCVerso2 (76%, 95% confidence interval [CI] 71-81, P=0.002; 81%, 95% CI 76-86, P<0.0001) and Arm 2 in HCVerso1 (81%, 95% CI 77-86, P<0.0001), but not for Arm 1 of HCVerso1 (72%, 95% CI 66-77, P=0.3989). Unadjusted SVR12 rates in Arms 1, 2, and 3 were 71.6%, 82.5%, and 72.5%, respectively, in HCVerso1 and 75.6%, 82.0%, and 73.6%, respectively, in HCVerso2. Virologic breakthrough and relapse occurred in 24-week arms in 8%-9% and 1% of patients, respectively, and in 16-week arms in 7%-8% and 9%-11% of patients, respectively. The most common adverse events were nausea (46%-61%) and vomiting (29%-35%). Adverse events resulted in discontinuation of all medications in 6%-8% of patients. In treatment-naïve patients with hepatitis C virus genotype-1b infection, with or without cirrhosis, faldaprevir + deleobuvir + ribavirin treatment for 24 weeks resulted in adjusted SVR12 rates significantly higher than historical controls. Both studies were registered in ClinicalTrials.gov (NCT01732796, NCT01728324)

Hydrodynamic modelling of physical habitat conditions for fish in the Ekso river near Flatekval

In this study, a 2D hydrodynamic model HEC-RAS is used to simulate the flood inundation, water depths and flow velocities of the river reach in the Eksingedal watercourse near Flatekval in western Norway. The objectives are to simulate the water depths and flow velocities with different scenarios and to assess the effect of flood regulation on habitat quality of the brown trout. The data is pre-processed and post-processed in ArcGIS. The model is set up and calibrated from historical flow data as well as the flood inundation area of the drone image. In addition, the sensitivity analysis of various factors such as roughness values, mesh resolution and time steps are conducted. Based on the results from the 2D HEC-RAS model, the information about the suitable area for different life stages of the brown trout and the distribution of the different habitats are obtained. This area covers the requirements of water depth and flow velocity for fish of different life stages decreases after regulation. Based on literature review, other factors (for example shore vegetation, water temperature, water chemistry, fish food etc) that may have affected the fish population are also discussed

A nonparametric change-point control chart

The assumption of fully known in-control distributions has long been recognized as an idealization, at best approximately true. Recent development of normal-based change-point methods has allowed the assumption of exactly known in-control mean and variance to be relaxed, but retained the assumption of normality. In this paper, we develop a nonparametric tool based on the change-point model for statistical process control. This method is shown to perform well, even beating the parametric approach for small to moderate shifts in normal data, and to involve relatively light computation

Visual Tracking with FPN Based on Transformer and Response Map Enhancement

Siamese network-based trackers satisfy the balance between performance and efficiency for visual tracking. However, they do not have enough robustness to handle the challenges of target occlusion and similar objects. In order to improve the robustness of the tracking algorithm, this paper proposes visual tracking with FPN based on Transformer and response map enhancement. In this paper, a feature pyramid structure based on Transformer is designed to encode robust target-specific appearance features, as well as the response map enhanced module to improve the tracker&rsquo;s ability to distinguish object and background. Extensive experiments and ablation experiments are conducted on many challenging benchmarks such as UAV123, GOT-10K, LaSOT and OTB100. These results show that the tracking algorithm we proposed in this paper can effectively improve the tracking robustness against the challenges of target occlusion and similar object, and thus improve the precision rate and success rate of the tracking algorithm