Miracle-dz/UniFAR-FTUs huggingface dataset:
Bandwidth increase through distributed atomic receivers in a Rydberg vapour cell

The data transfer capacity of a communication channel is limited by the Shannon-Hartley theorem and scales as $\text{log}_2(1 + \text{SNR})$ for a single channel with a given power signal-to-noise ratio (SNR). We implement an array of atom-optical receiver antennas in a single-input-multi-output (SIMO) configuration by using spatially distributed probe light beams. The data capacity of the distributed receiver configuration is observed to scale as $\text{log}_2(1 + N^2\times\text{SNR})$ for an array consisting of $N$ receivers. Our result is independent on the modulation frequency, and we show that such enhancement of the bandwidth cannot be obtained by a single receiver with a similar level of combined optical power due to the saturation of the SNR. We investigate both theoretically and experimentally the origins of the single channel capacity limit for our implementation.
RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization

Various autonomous or assisted driving strategies have been facilitated through the accurate and reliable perception of the environment around a vehicle. Among the commonly used sensors, radar has usually been considered as a robust and cost-effective solution even in adverse driving scenarios, e.g., weak/strong lighting or bad weather. Instead of considering fusing the unreliable information from all available sensors, perception from pure radar data becomes a valuable alternative that is worth exploring. In this paper, we propose a deep radar object detection network, named RODNet, which is cross-supervised by a camera-radar fused algorithm without laborious annotation efforts, to effectively detect objects from the radio frequency (RF) images in real-time. First, the raw signals captured by millimeter-wave radars are transformed to RF images in range-azimuth coordinates. Second, our proposed RODNet takes a snippet of RF images as the input to predict the likelihood of objects in the radar field of view (FoV). Two customized modules are also added to handle multi-chirp information and object relative motion. The proposed RODNet is cross-supervised by a novel 3D localization of detected objects using a camera-radar fusion (CRF) strategy in the training stage. Due to no existing public dataset available for our task, we create a new dataset, named CRUW,11The dataset and code are available at https://www.cruwdataset. org/. which contains synchronized RGB and RF image sequences in various driving scenarios. With intensive experiments, our proposed cross-supervised RODNet achieves 86% average precision and 88% average recall of object detection performance, which shows the robustness in various driving conditions.
Global jump filters and realized volatility

For a semimartingale with jumps, we propose a new estimation method for integrated volatility, i.e., the quadratic variation of the continuous martingale part, based on the global jump filter proposed by Inatsugu and Yoshida [8]. To decide whether each increment of the process has jumps, the global jump filter adopts the upper α-quantile of the absolute increments as the threshold. This jump filter is called global since it uses all the observations to classify one increment. We give a rate of convergence and prove asymptotic mixed normality of the global realized volatility and its variant “Winsorized global volatility”. By simulation studies, we show that our estimators outperform previous realized volatility estimators that use a few adjacent increments to mitigate the effects of jumps.
Fast and stable deterministic approximation of general symmetric kernel matrices in high dimensions

Kernel methods are used frequently in various applications of machine learning. For large-scale applications, the success of kernel methods hinges on the ability to operate certain large dense kernel matrix K . To reduce the computational cost, Nystr¨om methods can eﬃciently compute a low-rank approximation to a symmetric positive semi-deﬁnite (SPSD) matrix K through landmark points and many variants have been developed in the past few years. For indeﬁnite kernels, however, it has not even been justiﬁed whether Nystr¨om approximations are applicable. In this paper, we study for the ﬁrst time, both theoretically and numerically, the Nystr¨om method for approximating general symmetric kernels, including indeﬁnite ones. We ﬁrst develop a uniﬁed theoretical framework for analyzing Nystr¨om approximations, which is valid for both SPSD and indeﬁnite kernels and is independent of the speciﬁc scheme for selecting landmark points. To address the accuracy and numerical stability issues in Nystr¨om approximation, we then study the impact of data geometry on the spectral property of the corresponding kernel matrix and leverage the discrepancy theory to propose the anchor net method for computing Nystr¨om approximations. The anchor net method operates entirely on the dataset without requiring the access to K or its matrix-vector product and scales linearly for both SPSD and indeﬁnite kernel matrices. Extensive numerical experiments suggest that indeﬁnite kernels are much more challenging than SPSD kernels and most existing methods will suﬀer from numerical instability. Results on various kinds of kernels and machine learning datasets demonstrate that the new method resolves the numerical instability and achieves better accuracy with smaller computation costs compared to the state-of-the-art Nystr¨om methods.
Electronic localization in small-angle twisted bilayer graphene

Close to a magical angle, twisted bilayer graphene (TBLG) systems exhibit isolated flat electronic bands and, accordingly, strong electron localization. TBLGs have hence been ideal platforms to explore superconductivity, correlated insulating states, magnetism, and quantized anomalous Hall states in reduced dimension. Below a threshold twist angle (∼1.1∘), the TBLG superlattice undergoes lattice reconstruction, leading to a periodic moiré structure which presents a marked atomic corrugation. Using a tight-binding framework, this research demonstrates that superlattice reconstruction affects significantly the electronic structure of small-angle TBLGs. The first magic angle at ∼1.1∘ is found to be a critical case presenting globally maximized electron localization, thus separating reconstructed TBLGs into two classes with clearly distinct electronic properties. While low-energy Dirac fermions are still preserved at large twist angles >1.1∘ , small-angle ( ≲1.1° ) TBLG systems present common features such as large spatial variation and strong electron localization observed in unfavorable AA stacking regions. However, for small twist angles below 1.1∘, the relative contribution of the local AA regions is progressively reduced, thus precluding the emergence of further magic angles, in very good agreement with existing experimental evidence.
A Cognitive and Machine Learning-Based Software Development Paradigm Supported by Context

Advances in the use of cognitive and machine learning (ML) enabled systems fuel the quest for novel approaches and tools to support software developers in executing their tasks. First, as software development is a complex and dynamic activity, these tasks are highly dependent on the characteristics of the software project and its context, and developers need comprehensive support in terms of information and guidance based on the task context. Second, there is a lack of methods based on conversational-guided agents that consider cognitive aspects such as paying attention and remembering. Third, there is also a lack of techniques that make use of historical implicit or tacit data to infer new knowledge about the project tasks such as related tasks, task experts, relevant information needed for task completion and warnings, and navigation aspects of the process such as what tasks to perform next and optimal task sequencing. Based on these challenges, this paper introduces a novel paradigm for human-machine software support based on context, cognitive assistance, and machine learning, and briefly describes ongoing research activities to realize this paradigm. The research takes advantage of the synergy among emergent methods provided in context-aware software processes, cognitive computing such as chatbots, and machine learning such as recommendation systems. These novel paradigms have the potential to transform the way software development currently occurs by allowing developers to receive valuable information and guidance in real-time while they are participating in projects.
A Generic Object Re-identification System for Short Videos

Short video applications like TikTok and Kwai have been a great hit recently. In order to meet the increasing demands and take full advantage of visual information in short videos, objects in each short video need to be located and analyzed as an upstream task. A question is thus raised -- how to improve the accuracy and robustness of object detection, tracking, and re-identification across tons of short videos with hundreds of categories and complicated visual effects (VFX). To this end, a system composed of a detection module, a tracking module and a generic object re-identification module, is proposed in this paper, which captures features of major objects from short videos. In particular, towards the high efficiency demands in practical short video application, a Temporal Information Fusion Network (TIFN) is proposed in the object detection module, which shows comparable accuracy and improved time efficiency to the state-of-the-art video object detector. Furthermore, in order to mitigate the fragmented issue of tracklets in short videos, a Cross-Layer Pointwise Siamese Network (CPSN) is proposed in the tracking module to enhance the robustness of the appearance model. Moreover, in order to evaluate the proposed system, two challenge datasets containing real-world short videos are built for video object trajectory extraction and generic object re-identification respectively. Overall, extensive experiments for each module and the whole system demonstrate the effectiveness and efficiency of our system.
Inverse Design of Plasma Metamaterial Devices for Optical Computing

We apply inverse-design methods to produce two-dimensional plasma metamaterial (PMM) devices. Backpropagated finite-difference frequency-domain (FDFD) simulations are used to design waveguides and demultiplexers operating under both TE and TM modes. Demultiplexing and waveguiding are demonstrated for devices composed of plasma elements with reasonable plasma densities of approximately 7 GHz, allowing for future in situ training and experimental realization of these designs. We also explore the possible applicability of PMMs to nonlinear boolean operations for use in optical computing. Functionally complete logical connectives (OR and AND) are achieved in the TM mode.
Production and properties of micro‐porous glas bubble zinc and aluminium composites

Micro‐porous syntactic foams were produced by means of integration of glass bubbles into aluminium and zinc matrices. Preforms of glass bubbles were pressure infiltrated with the alloys AlSi9Cu9 ans ZnAl4Cu using squeeze casting. The preforms were sintered thermically without the use of bonding agents. Using the combination of different sintering steps syntactic foams with locally different densities could be produced. The mechanical properties of the foams were tested indicating a high compression strength of the foams and a very good compression energy absorption. Furthermore, corrosion behaviour and behaviour at higher temperatures were investigated.
Study of the $\eta$ to $\pi^0$ Ratio in Heavy-Ion Collisions

We demonstrate that the pT dependence of the η/π 0 ratio is universal within a few percent for high energy p+p, p+A and d+A collisions, over a broad range of collision energies. The η/π ratio increases with pT up to 4 to 5 GeV/c where it saturates at a nearly constant value of 0.487±0.024. Above pT = 5 GeV/c the same constant value is also observed in A+A collisions independent of collision system, energy, and centrality. At lower pT , where accurate η/π 0 data is absent for A+A collisions, we estimate possible deviations from the universal behavior, which could arise due to the rapid radial hydrodynamic expansion of the A+A collision system. For A+A collisions at RHIC we find that possible deviations are limited to the pT range from 0.4 to 3 GeV/c, and remain less than 20% for the most central collisions.
Computational deconvolution to estimate cell type-specific gene expression from bulk data

Abstract Computational deconvolution is a time and cost-efficient approach to obtain cell type-specific information from bulk gene expression of heterogeneous tissues like blood. Deconvolution can aim to either estimate cell type proportions or abundances in samples, or estimate how strongly each present cell type expresses different genes, or both tasks simultaneously. Among the two separate goals, the estimation of cell type proportions/abundances is widely studied, but less attention has been paid on defining the cell type-specific expression profiles. Here, we address this gap by introducing a novel method Rodeo and empirically evaluating it and the other available tools from multiple perspectives utilizing diverse datasets.
ULTRA-RAPID 3D-ACEO ELECTROKINETIC PRECONCENTRATION FOR VIRUS DETECTION

High-sensitivity screening of biomarkers is a critical issue for early disease detection and diagnosis. Here the development of integrated electrostatic exclusion and AC electrokinetic flow control devices for rapidly attomolar detection of virus is reported. An insulated-CNTs electrode modified with monoclonal antibody for 80 nm bacteriophages exhibit close to a 10 4 increase in sensitivity due to streaming ACEO and corresponding electrostatic contribution to the binding affinity after application of an AC electric-field. We demonstrate that bacteriophages can be dynamically positioned with an electric-field strength as small as 2×10 3-5 V/m and define the operating parameters for increasing the concentration of phages by 4 orders of magnitude less than 10 minutes. These results show general applicability of this method, and could open up opportunities in early stage disease detection and the analysis of proteins from single cells.
The Effects of Cognitive and Visual Functions of Korean Elderly Taxi Drivers on Safe Driving Behavior

Purpose In this study, we investigated the effect of visual and cognitive functions of elderly taxi drivers on safe driving behavior. We aimed to identify factors that interfere with safe driving in an aging Korean society in elderly taxi drivers. Participants and Methods A total of 203 elderly taxi drivers, aged >65, working at 3 companies in a single city were assessed over 4 weeks from December 1 to December 30, 2017, using the Motor-Free Visual Perception Test, Korean Montreal Cognitive Assessment, and Korean Safe Driving Behavior Measure. To examine the effects of cognitive and visual functions on driving behavior, we performed a stepwise multiple linear regression analysis (p<0.05). Results All 4 subdomains of safe driving behaviors were significantly correlated with the cognitive subdomains of attention and abstraction and the visual perception subdomains of visual closure 1 and figure-ground. Conclusion More systematic assessments of the relationship between driving behavior and cognitive and visual function in elderly individuals are needed.
A systematic review and meta-analysis of laparotomy compared with laparoscopic management of interstitial pregnancy

Background Interstitial pregnancy is a rare but life-threatening condition accounting for 1-4% of all types of tubal ectopic pregnancies. It can be managed by open and minimally invasive surgical techniques. Our goal was to compare laparoscopic and open surgery for managing interstitial pregnancy. Search Strategy We searched PubMed, Scopus, Web of Science, and Cochrane up to May 2020. Selection Criteria 1) Women with interstitial pregnancy, 2) Intervention: laparoscopic surgery, 3) Comparator: open surgery, 4) Outcomes: Hospital stay, operation time, pain scale, blood loss. Secondary outcomes: any other reported 5) Study designs: interventional and observational. Data collection and analysis Data was extracted from the relevant articles and was pooled as mean difference (MD) or relative risk (RR) with a 95% confidence interval (CI). Main Results We included six studies, three of which provided eligible data. The duration of hospital stay was lower in the laparoscopic surgery group (MD = -1.42, 95% CI [-1.72, -0.76], P < 0.0001). There was no significant difference in operative time (MD = 5.90, 95% CI [-11.30, 23.09], P = 0.50, blood loss (MD = -9.43, 95% CI [-214.18, 195.32], P = 0.93), complications (RR = 1.54, 95% CI [0.20, 11.85], P = 0.68), or blood transfusions (RR = 0.77, 95% CI [0.50, 1.25], P = 0.30). Conclusion Laparoscopic surgery is associated with shorter hospital stay, with no difference in terms of blood loss, post-, and intraoperative complications, and need for blood transfusion compared with laparotomy.
Co-Production of NDM-1, CTX-M-9 Family and mcr-1 in a Klebsiella pneumoniae ST4564 Strain in China

Purpose To identify novel sequence types 4564 (ST4564) carbapenem-resistant Klebsiella pneumoniae (CRKP). Characterizing the feature of the clinic, resistance, and virulence of a co-producing NDM-1 and CTX-M-9 family and mcr-1 ST4564 strain. Methods A novel ST4564 CRKP was collected from June 2018 to July 2018. We investigated its antimicrobial susceptibility by the microdilution method. Using the modified carbapenem inactivation method (mCIM) to screen phenotype of carbapenemases. Resistance mechanisms, virulence-associated genes, multilocus sequence typing (MLST), and capsular serotypes were characterized by polymerase chain reaction (PCR) and DNA sequencing. Next-generation sequencing (NGS) was carried out to determine the genetic features of carbapenem resistance and virulence. Results ST4564, co-carrying NDM-1, CTX-M-9 and mcr-1, was resistant to carbapenems, cephamycin, third- or fourth-generation cephalosporins, β-lactam combination agents, quinolones and tigecycline but remained susceptible to amikacin (AMK) and colistin (COL). Through the NGS analysis with the G+C content of 56.65%, multiple resistance and virulence genomes were detected. The genes encoding the β-lactams, aminoglycosides, quinolones, macrolides, sulfonamide, polysaccharide capsule, type-I fimbriae cluster, siderophore genes, transporter and pumps, T6SS and pullulanase secretion protein. goeBURST analysis showed that ST4564 belonged to the CC1571 and it was not related to the prevalent high-risk clones. Conclusion We first identified the novel ST4564 CRKP. Our finding suggested that the urgent need for infection control of the new clone to prevent it from becoming a high-risk clone of CRKP.
Label-Free, Smartphone-Based, and Sensitive Nano-Structural Liquid Crystal Aligned by Ceramic Silicon Compound–Constructed DMOAP-Based Biosensor for the Detection of Urine Albumin

Introduction The sensitive interfacial interaction of liquid crystals (LC) holds potential for precision biosensors. In the past, the developments of LC biosensors were limited by the complicated manufacturing process, which hinders commercialization and wider applications of such devices. In this report, we demonstrate the first nano-structural polymeric stabilized-cholesteric LC (PSCLC) thin films to be a new label-free biosensing technology. Methods The transmission spectra of PSCLC devices were measured by the fiber-optic spectrometer with high-resolution. In addition, a smartphone was set on the stage, and the camera of smartphone was placed and aligned with a set of lenses embedded in the designed stage. To decrease the chromatic and spherical aberrations, an achromatic lens set composition, consisting of both dual-convex lens and concave-plane lens, was applied for measuring and imaging the PSCLC texture. The average and the estimated standard deviation (SD) were used to present quantitative experimental results. The test BSA was immobilized and fulfilled by the ceramic silicon-constructed DMOAP-coated glass in aqueous BSA solutions at 1 mg/mL, 1 µg/mL, and 1 ng/mL. Results The fabrication process of PSCLC is much simplified compared to previous LC biosensors. The color of PSCLC biosensor altered with the BSA concentration, making detection result easy to read. The detection limit of 1 ng/mL is achieved for label-free PSCLC biosensor. The PSCLC biosensor was able to successfully detect due to the albumin concentration’s alteration, with a linear range of 1 ng/mL–2 mg/mL. Thus, the label-free-proposed design-integrated nanoscale PSCLCs smartphone-based biosensor could successfully detect BSA in a preclinical urine sample. Conclusion Finally, we propose a design to integrate the PSCLC biosensor with a smartphone. The PSCLC owns potential for high performance, low cost for detecting various disease biomarkers in home use. Owing to its great potential for high performance and low cost, the PSCLC biosensors can be used as a label-free point-of-care for detecting various disease biomarkers for patients in care homes.
Is telephone follow-up useful in preventing post-extraction bleeding in patients on antithrombotic treatment?

Background The aim of the study was to investigate the usefulness of telephone follow-up in preventing post-extraction bleeding and improving wound healing in patients on chronic antithrombotic treatment. Material and Methods A prospective randomized clinical trial was carried out on 256 patients (test group = 128; control group = 128). The exact two-tailed Fisher test and the two-tailed non-parametric Mann-Whitney test were used for statistical analysis. Results The incidence of post-extraction bleeding was 15.6% and there was no difference between test and control groups. However, the study group was significantly, though weakly, associated with the severity of bleeding. Patient satisfaction with post-operative follow-up differed significantly between patients who had and those who did not have post-extraction bleeding. Conclusions Telephone follow-up after tooth extraction may play a role in the prevention of severe post-operative bleeding as well as in monitoring and managing the surgical wound. Key words:Post-operative instructions, patient satisfaction, wound healing.
Effect of acupoint catgut embedding in chronic fatigue syndrome patients

Abstract Background: Chronic fatigue syndrome (CFS) is a relatively complex and disabling illness with a substantial economic burden and functional impairment. Until now, many CFS patients lack appropriate healthcare. Acupoint catgut embedding is an effective and emerging alternative therapy for CFE. With this research, we endeavor to investigate the effect and safety of ACE for CFS. Methods: Eight databases will be searched from inception to December 2020: PubMed, EMBASE, The Cochrane Library, Web of Science, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, Chong-Qing VIP database, and Wan-fang database. We regard studies as eligible for inclusion if they were RCTs done in CFS patients, compare acupoint catgut embedding to another treatment strategy, and report fatigue changes at the end of the intervention period. Two independent reviewers complete the study selection, data extraction, and the risk of bias assessment. We assess pooled data using a random-effects model through Revman software (v.5.3) and Stata (version 15.0). Ethics and dissemination: Ethics approval is not required because the individual patient data will not be involved, with no privacy concerns. This systematic review and meta-analysis will provide a reference for CFS patients and clinicians on the non-drug interventions. We will publish and disseminate the results of this review in a peer-reviewed journal or relevant conference. OSF Registration number: 10.17605/OSF.IO/7SHD9 (https://osf.io/7shd9).