Miracle-dz/UniFAR-FTUs huggingface dataset:
Noisy-Labeled NER with Confidence Estimation

Recent studies in deep learning have shown significant progress in named entity recognition (NER). However, most existing works assume clean data annotation, while real-world scenarios typically involve a large amount of noises from a variety of sources (e.g., pseudo, weak, or distant annotations). This work studies NER under a noisy labeled setting with calibrated confidence estimation. Based on empirical observations of different training dynamics of noisy and clean labels, we propose strategies for estimating confidence scores based on local and global independence assumptions. We partially marginalize out labels of low confidence with a CRF model. We further propose a calibration method for confidence scores based on the structure of entity labels. We integrate our approach into a self-training framework for boosting performance. Experiments in general noisy settings with four languages and distantly labeled settings demonstrate the effectiveness of our method.
Signatures of the quantum nature of gravity in the differential motion of two masses

We show that a signature of the quantum nature of gravity is the quantum mechanical squeezing of the differential motion of two identical masses with respect to their common mode. This is because the gravitational interaction depends solely on the relative position of the two masses. In principle, this squeezing is equivalent to quantum entanglement between the masses. In practice, detecting the squeezing is more feasible than detecting the entanglement. To that end, we propose an optical interferometric scheme to falsify hypothetical models of gravity.
Progressive extension of reinforcement learning action dimension for asymmetric assembly tasks

Reinforcement learning (RL) is always the preferred embodiment to construct the control strategy of complex tasks, like asymmetric assembly tasks. However, the convergence speed of reinforcement learning severely restricts its practical application. In this paper, the convergence is first accelerated by combining RL and compliance control. Then a completely innovative progressive extension of action dimension (PEAD) mechanism is proposed to optimize the convergence of RL algorithms. The PEAD method is verified in DDPG and PPO. The results demonstrate the PEAD method will enhance the data-efficiency and time-efficiency of RL algorithms as well as increase the stable reward, which provides more potential for the application of RL.
Towards On-Demand Heralded Single-Photon Sources via Photon Blockade

Jiangshan Tang,1, 2 Lei Tang,1 Haodong Wu,1 Yang Wu,1, 3 Hui Sun,3, ∗ Han Zhang,1, 2, † Tao Li,4 Yanqing Lu (陆延青),1, 2 Min Xiao,1, 2, 5 and Keyu Xia (夏可宇)1, 2, ‡ 1College of Engineering and Applied Sciences, National Laboratory of Solid State Microstructures, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210023, China 2School of Physics, Nanjing University, Nanjing 210023, China 3School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710062, China 4School of Science, Nanjing University of Science and Technology, Nanjing 210094, China 5Department of Physics, University of Arkansas, Fayetteville, Arkansas 72701, USA
Helping People Deal With Disinformation - A Socio-Technical Perspective

At the latest since the advent of the Internet, disinformation and conspiracy theories have become ubiquitous. Recent examples like QAnon and Pizzagate prove that false information can lead to real violence. In this motivation statement for the Workshop on Human Aspects of Misinformation at CHI 2021, I explain my research agenda focused on 1. why people believe in disinformation, 2. how people can be best supported in recognizing disinformation, and 3. what the potentials and risks of different tools designed to fight disinformation are.
Disentangling SMEFT operators with future low-energy PVES experiments

We study the potential of future Parity-Violating Electron Scattering (PVES) data to probe the parameter space of the Standard Model Effective Field Theory (SMEFT). We contrast the constraints derived from Drell-Yan data taken at the Large Hadron Collider (LHC) with projections of the planned PVES experiments SoLID and P2. We show that the PVES data can complement the bounds set by the LHC data in the dimension-6 operator space since it probes different combinations of operators than Drell-Yan. The lower characteristic energy of P2 and SoLID also helps disentangle effects of dimension-6 and dimension-8 operators that are difficult to resolve with LHC Drell-Yan data alone. ar X iv :2 10 4. 03 97 9v 1 [ he pph ] 8 A pr 2 02 1
What are Table Cartograms Good for Anyway? An Algebraic Analysis

Unfamiliar or esoteric visual forms arise in many areas of visualization. While such forms can be intriguing, it can be unclear how to make effective use of them without long periods of practice or costly user studies. In this work we analyze the table cartogram—a graphic which visualizes tabular data by bringing the areas of a grid of quadrilaterals into correspondence with the input data, like a heat map that has been “area‐ed” rather than colored. Despite having existed for several years, little is known about its appropriate usage. We mend this gap by using Algebraic Visualization Design to show that they are best suited to relatively small tables with ordinal axes for some comparison and outlier identification tasks. In doing so we demonstrate a discount theory‐based analysis that can be used to cheaply determine best practices for unknown visualizations.
Re-designing cities with conditional adversarial networks

This paper introduces a conditional generative adversarial network to redesign a street-level image of urban scenes by generating 1) an urban intervention policy, 2) an attention map that localises where intervention is needed, 3) a high-resolution street-level image (1024 X 1024 or 1536 X1536) after implementing the intervention. We also introduce a new dataset that comprises aligned street-level images of before and after urban interventions from real-life scenarios that make this research possible. The introduced method has been trained on different ranges of urban interventions applied to realistic images. The trained model shows strong performance in re-modelling cities, outperforming existing methods that apply image-to-image translation in other domains that is computed in a single GPU. This research opens the door for machine intelligence to play a role in re-thinking and re-designing the different attributes of cities based on adversarial learning, going beyond the mainstream of facial landmarks manipulation or image synthesis from semantic segmentation.
Ultrathin continuous lossy metal film for broadband light absorption and hot electron collection

Abstract. A broadband perfect light absorption scheme relying on planar layers of lossy metallic and semiconductor films without structure pattering for hot electron photodetection is proposed and demonstrated. The nontrivial reflection phase shift occurring in the ultrathin lossy metal film is responsible for the strong resonance effects of the metal–semiconductor–metal (M-S-M) structures. Broadband and perfect light absorption is demonstrated experimentally for the platinum (Pt)—titanium dioxide (TiO2)—aluminum (Al) absorber, in which the ultrathin (10 nm) Pt layer electrically serves as the hot electron emitter. Under the monochromatic light illumination, the proposed M-S-M diode shows a clear hot-electron-based photoresponse.
New Biological Method for Detoxification and Removal of Hexavalent Chromium

Hexavalent chromium (Cr6+) is toxic for most organisms. We isolated a bacterial strain that is capable of reducing toxic Cr6+ to trivalent chromium ( Cr3+ ). The reduced chromium formed insoluble hydroxides at a neutral pH and precipitated, thus making it less available to biological systems. The bacterial ability to reduce Cr6+ was proved to be useful for treating a Cr6+-contaminated industrial effluent.
Second allogeneic haematopoietic cell transplantation using HLA‐matched unrelated versus T‐cell replete haploidentical donor and survival in relapsed acute myeloid leukaemia

Optimal donor choice for a second allogeneic haematopoietic cell transplant (allo‐HCT) in relapsed acute myeloid leukaemia (AML) remains unknown. We compared overall survival (OS) using registry data from the Acute Leukemia Working Party (ALWP) of the European Society for Blood and Marrow Transplantation (EBMT) involving 455 adults who received a second allo‐HCT from a human leucocyte antigen (HLA)‐matched unrelated (MUD) (n = 320) or a haploidentical (n = 135) donor. Eligibility criteria required adults aged ≥18 years who received a second allo‐HCT for treating AML relapse between 2005 and 2019. The primary end‐point was OS. There was no statistically significant difference in the median (interquartile range) age between the groups, MUD 46 (35–58) versus haploidentical 44 (33–53) years (P = 0·07). The median OS was not different between the MUD and the haploidentical groups (10 vs. 11 months, P = 0·57). Similarly, the 2‐year OS was 31% for the MUD and 29% for the haploidentical donor groups. The OS was worse if the procedure was performed with active AML [hazard ratio (HR) 1·42, 95% confidence interval (CI) 1·07–1·89; P = 0·02]. Conversely, a longer time from first allo‐HCT to relapse (>13·2 months) was associated with better OS (HR 0·50, 95% CI 0·37–0·69; P < 0·0001). The results of the present analysis limit the ability to recommend one donor type over another when considering a second allo‐HCT for relapsed AML. Our findings highlight that best OS is achieved when receiving the second allo‐HCT in complete remission.
Anxiety levels and solution‐focused thinking skills of nurses and midwives working in primary care during the COVID‐19 pandemic: A descriptive correlational study

Abstract Aims To determine the state–trait anxiety levels and solution‐focused thinking skills of primary care nurses/midwives during the COVID‐19 pandemic, and to evaluate the factors affecting these variables and the determinants of state–trait anxiety levels. Background The COVID‐19 outbreak has created intense anxiety in nurses/midwives that may affect the care they provide. Nurses and midwives may manage anxiety using solution‐focused thinking skills. Methods This descriptive correlational study included 170 nurses/midwives at 61 family health centres evaluated from 1 August to 14 September 2020. Results The participants' state and trait anxiety scores were above average, indicating a moderate level of anxiety and the mean total solution‐focused inventory scores were at a moderate level. It was determined that 47.9% of the variance in state anxiety scores could be explained by trait anxiety, age, years of professional experience, chronic illness, type of work shift during the pandemic, follow‐up of patients diagnosed with COVID‐19 using computed tomography or a COVID‐19 test, and whether the institution was taking necessary measures against COVID‐19. There was a negative relationship between state anxiety and solution‐focused inventory total score. Conclusion Nurses/midwives displayed a moderate level of anxiety and solution‐focused thinking skills during the COVID‐19 pandemic. Implications for Nursing Management Steps should be taken to improve nurses' solution‐focused thinking skills to enable them to organise quickly and manage care processes successfully in extraordinary circumstances such as pandemics. Moreover, personal empowerment programmes should be recommended for nurses and midwives to help them cope with anxiety.
CCR8 marks highly suppressive Treg cells within tumours but is dispensable for their accumulation and suppressive function

CD4+ regulatory T (Treg) cells, dependent upon the transcription factor Foxp3, contribute to tumour immunosuppression but are also required for immune homeostasis. There is interest in developing therapies that selectively target the immunosuppressive function of Treg cells within tumours without disrupting their systemic anti‐inflammatory function. High levels of expression of chemokine (C‐C motif) receptor 8 (CCR8) discriminate Treg cells within tumours from those found in systemic lymphoid tissues. It has recently been proposed that disruption of CCR8 function using blocking anti‐CCR8 antibodies results in reduced accumulation of Treg cells within tumours and disruption of their immunosuppressive function. Here, using Ccr8−/− mice, we show that CCR8 function is not required for Treg cell accumulation or immunosuppression in the context of syngeneic MC38 colorectal adenocarcinoma and B16 melanoma tumours. We observed high levels of CCR8 expression on tumour‐infiltrating Treg cells which were abolished in Ccr8−/− mice. High levels of CCR8 marked cells with high levels of suppressive function. However, whereas systemic ablation of Treg cells resulted in strikingly diminished tumour burden, growth of subcutaneously implanted tumours was unaffected by systemic CCR8 loss. Consistently, we observed minimal impact of systemic CCR8 ablation on the frequency, phenotype and function of tumour‐infiltrating Treg cells and conventional T (Tconv) function. These findings suggest that CCR8 is not required for Treg cell accumulation and immunosuppressive function within tumours and that depletion of CCR8+ Treg cells rather than blockade of CCR8 function is a more promising avenue for selective immunotherapy.
Introducing Rolled‐Up Nanotechnology for Advanced Energy Storage Devices

Energy storage devices, acting as complementing units for renewable energy sources, play a key role in modern society, and they serve as the dominant power supply for most portable electronics. At the heart of the development of next‐generation energy storage devices lies the exploration of intrinsic material properties, architectural design and fabrication methods. Rolled‐up nanotechnology, a unique method to self‐assemble nanomembranes into 3D structures using strain engineering, has advanced the development of energy storage devices with superior performance. In this review, the recent progress of employing rolled‐up nanotechnology is focused to design rational electrodes for Li‐ion (LIBs) and Li‐O2 batteries. A comprehensive summary of the fabrication and application of diverse rolled‐up structures in these electrochemical energy storage devices is provided. Apart from this, the great potential of this approach is also highlighted for scalable miniaturized microdevice fabrication, including micro‐LIBs, microsupercapacitors, and microscale ultracompact capacitors. These devices offer a promising platform not only for electrochemical microprobes, but also for lab‐on‐a‐chip applications. Finally, prospects and challenges of employing rolled‐up nanotechnology for future research and development in the broad field of energy storage systems are discussed.
NOREBA: a compiler-informed non-speculative out-of-order commit processor

Modern superscalar processors execute instructions out-of-order, but commit them in program order to provide precise exception handling and safe instruction retirement. However, in-order instruction commit is highly conservative and holds on to critical resources far longer than necessary, severely limiting the reach of general-purpose processors, ultimately reducing performance. Solutions that allow for efficient, early reclamation of these critical resources could seize the opportunity to improve performance. One such solution is out-of-order commit, which has traditionally been challenging due to inefficient, complex hardware used to guarantee safe instruction retirement and provide precise exception handling. In this work, we present NOREBA, a processor for Non-speculative Out-of-order Retirement via Branch Reconvergence Analysis. In NOREBA, we enable non-speculative out-of-order commit and resource reclamation in a light-weight manner, improving performance and efficiency. We accomplish this through a combination of (1) automatic compiler annotation of true branch dependencies, and (2) an efficient re-design of the reorder buffer from traditional processors. By exploiting compiler branch dependency information, this system achieves 95% of the performance of aggressive, speculative solutions, without any additional speculation, and while maintaining energy efficiency.
Enclosure: language-based restriction of untrusted libraries

Programming languages and systems have failed to address the security implications of the increasingly frequent use of public libraries to construct modern software. Most languages provide tools and online repositories to publish, import, and use libraries; however, this double-edged sword can incorporate a large quantity of unknown, unchecked, and unverified code into an application. The risk is real, as demonstrated by malevolent actors who have repeatedly inserted malware into popular open-source libraries. This paper proposes a solution: enclosures, a new programming language construct for library isolation that provides a developer with fine-grain control over the resources that a library can access, even for libraries with complex inter-library dependencies. The programming abstraction is language-independent and could be added to most languages. These languages would then be able to take advantage of hardware isolation mechanisms that are effective across language boundaries. The enclosure policies are enforced at run time by LitterBox, a language-independent framework that uses hardware mechanisms to provide uniform and robust isolation guarantees, even for libraries written in unsafe languages. LitterBox currently supports both Intel VT-x (with general-purpose extended page tables) and the emerging Intel Memory Protection Keys (MPK). We describe an enclosure implementation for the Go and Pythonlanguages. Our evaluation demonstrates that the Go implementation can protect sensitive data in real-world applications constructed using complex untrusted libraries with deep dependencies. It requires minimal code refactoring and incurs acceptable performance overhead. The Python implementation demonstrates LitterBox’s ability to support dynamic languages.
Computing with time: microarchitectural weird machines

Side-channel attacks such as Spectre rely on properties of modern CPUs that permit discovery of microarchitectural state via timing of various operations. The Weird Machine concept is an increasingly popular model for characterization of emergent execution that arises from side-effects of conventional computing constructs. In this work we introduce Microarchitectural Weird Machines (µWM): code constructions that allow performing computation through the means of side effects and conflicts between microarchitectual entities such as branch predictors and caches. The results of such computations are observed as timing variations. We demonstrate how µWMs can be used as a powerful obfuscation engine where computation operates based on events unobservable to conventional anti-obfuscation tools based on emulation, debugging, static and dynamic analysis techniques. We demonstrate that µWMs can be used to reliably perform arbitrary computation by implementing a SHA-1 hash function. We then present a practical example in which we use a µWM to obfuscate malware code such that its passive operation is invisible to an observer with full power to view the architectural state of the system until the code receives a trigger. When the trigger is received the malware decrypts and executes its payload. To show the effectiveness of obfuscation we demonstrate its use in the concealment and subsequent execution of a payload that exfiltrates a shadow password file, and a payload that creates a reverse shell.
Photochemical production of dissolved inorganic carbon from terrestrial organic matter: significance to the oceanic organic carbon cycle

Water collected from riverine, near coastal, and salt marsh sources in the Southeastern United States was evaluated for its ability to produce both carbon monoxide (CO) and dissolved inorganic carbon (DIC) by photochemical oxidation of natural dissolved organic carbon (DOC). Irradiation of whole water samples using simulated sunlight produced CO at rates similar to those measured previously. Production rates for DIC were more than an order of magnitude higher than those observed for CO. Based on observed DIC formation rates, photo-oxidation of DOC by sunlight should be considered a dominant removal mechanism of organic carbon from the ocean.
Linking the prepositions: using power analysis to inform strategies for social action

ABSTRACT This article reviews longstanding debates about the relationship between power over and power to – often posed as the tension between domination and emancipation. It then turns to several frameworks which integrate these approaches to inform strategies for social action. In particular, it focuses on recent empirical studies which apply one such framework, the ‘powercube’, to glean insights into how social actors navigate across multiple forms, spaces and levels of power. In so doing, we gain clues into how relatively powerless groups develop the capacities for agency and action which challenge domination and in turn give new possibilities for emancipation.
Microbial Community Characteristics Largely Unaffected by X-Ray Computed Tomography of Sediment Cores

X-ray computed tomography (CT) scanning is used to study the physical characteristics of soil and sediment cores, allowing scientists to analyze stratigraphy without destroying core integrity. Microbiologists often work with geologists to understand the microbial properties in such cores; however, we do not know whether CT scanning alters microbial DNA such that DNA sequencing, a common method of community characterization, changes as a result of X-ray exposure. Our objective was to determine whether CT scanning affects the estimates of the composition of microbial communities that exist in cores. Sediment cores were extracted from a salt marsh and then submitted for CT scanning. We observed a minimal effect of CT scanning on microbial community composition in the sediment cores either when the cores were examined shortly after recovery from the field or after the cores had been stored for several weeks. In contrast, properties such as sediment layer and marsh location did affect microbial community structure. While we observed that CT scanning did not alter microbial community composition as a whole, we identified a few amplicon sequence variants (13 out of 7,037) that showed differential abundance patterns between scanned and unscanned samples among paired sample sets. Our overall conclusion is that the CT-scanning conditions typically used to obtain images for geological core characterization do not significantly alter microbial community structure. We stress that minimizing core exposure to X-rays is important if cores are to be studied for biological properties. Future investigations might consider variables, such as the length and energy of radiation exposure, the volume of the core, or the degree, to which microbial communities are stressed as important factors in assessing the impact of X-rays on microbes in geological cores.