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Thermal conductance and noise of Majorana modes along interfaced ν= 52 fractional quantum Hall states
Full text linkIdentifying the topological order of the fractional quantum Hall state at filling ν=5/2 is an important step towards realizing non-Abelian Majorana modes in condensed matter physics. However, to unambiguously distinguish between various proposals for this order is a formidable challenge. Here, we present a detailed study of transport along interfaced edge segments of fractional quantum Hall states hosting non-Abelian Majorana modes. With an incoherent model approach, we compute, for edge segments based on Pfaffian, anti-Pfaffian, and particle-hole-Pfaffian topological orders, thermal conductances, voltage biased charge current noise, and delta-T noise. We determine how the thermal equilibration of edge modes impacts these observables and identify the temperature scalings of transitions between regimes of differently quantized thermal conductances. In combination with recent experimental data, we use our results to estimate thermal and charge equilibration lengths in real devices. We also propose an experimental setup, which permits measuring several transport observables for interfaced fractional quantum Hall edges in a single device. It can, e.g., be used to rule out edge reconstruction effects. In this context, we further point out some subtleties in two-terminal thermal conductance measurements and how to remedy them. Our findings are consistent with recent experimental results pointing towards a particle-hole-Pfaffian topological order at filling ν=5/2 in GaAs/AlGaAs, and provide further means to pinpoint the edge structure at this filling and possibly also other exotic fractional quantum Hall states
Messy space = creative space: Boundary work in organizational creativity
No full textIt is common knowledge that an organization can stimulate (or kill) creativity among its employees through office design, with colors and playful toys numbering among the key ingredients believed to make people creative. What is less known is how these and other spatial qualities influence work. This study looks at the connection between the space and creative work, with the help of boundary work. Using ethnographic methods, this study reveals how people mobilize and set up creative spaces (agencing space), and how such space helps (or doesn’t) people to work creatively (spatial agencing). Four different creative spaces are analyzed: hackathons, design thinking workshops, an innovation room, and an innovation helpdesk. It is shown how these spaces for creation can make creative practices legitimate, how temporality creates a sense of urgency, and how messiness signals what is expected of people. Furthermore, it is also shown how boundary practices help people engage in creative work
Applications of Artificial Intelligence in PSMA PET/CT for Prostate Cancer Imaging
Full text linkProstate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) has emerged as an important imaging technique for prostate cancer. The use of PSMA PET/CT is rapidly increasing, while the number of nuclear medicine physicians and radiologists to interpret these scans is limited. Additionally, there is variability in interpretation among readers. Artificial intelligence techniques, including traditional machine learning and deep learning algorithms, are being used to address these challenges and provide additional insights from the images. The aim of this scoping review was to summarize the available research on the development and applications of AI in PSMA PET/CT for prostate cancer imaging. A systematic literature search was performed in PubMed, Embase and Cinahl according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 26 publications were included in the synthesis. The included studies focus on different aspects of artificial intelligence in PSMA PET/CT, including detection of primary tumor, local recurrence and metastatic lesions, lesion classification, tumor quantification and prediction/prognostication. Several studies show similar performances of artificial intelligence algorithms compared to human interpretation. Few artificial intelligence tools are approved for use in clinical practice. Major limitations include the lack of external validation and prospective design. Demonstrating the clinical impact and utility of artificial intelligence tools is crucial for their adoption in healthcare settings. To take the next step towards a clinically valuable artificial intelligence tool that provides quantitative data, independent validation studies are needed across institutions and equipment to ensure robustness
Mechanically Adaptive Mixed Ionic-Electronic Conductors Based on a Polar Polythiophene Reinforced with Cellulose Nanofibrils
Full text linkConjugated polymers with oligoether side chains are promising mixed ionic-electronic conductors, but they tend to feature a low glass transition temperature and hence a low elastic modulus, which prevents their use if mechanical robust materials are required. Carboxymethylated cellulose nanofibrils (CNF) are found to be a suitable reinforcing agent for a soft polythiophene with tetraethylene glycol side chains. Dry nanocomposites feature a Young’s modulus of more than 400 MPa, which reversibly decreases to 10 MPa or less upon passive swelling through water uptake. The presence of CNF results in a slight decrease in electronic mobility but enhances the ionic mobility and volumetric capacitance, with the latter increasing from 164 to 197 F cm-3 upon the addition of 20 vol % CNF. Overall, organic electrochemical transistors (OECTs) feature a higher switching speed and a transconductance that is independent of the CNF content up to at least 20 vol % CNF. Hence, CNF-reinforced conjugated polymers with oligoether side chains facilitate the design of mechanically adaptive mixed ionic-electronic conductors for wearable electronics and bioelectronics
3D Localization with a Single Partially-Connected Receiving RIS: Positioning Error Analysis and Algorithmic Design
No full textIn this paper, we introduce the concept of partially-connected receiving reconfigurable intelligent surfaces (R-RISs), which refers to metasurfaces designed to efficiently sense electromagnetic waveforms impinging on them, and perform localization of the users emitting them. The presented R-RIS hardware architecture comprises subarrays of meta-atoms, with each of them incorporating a waveguide assigned to direct the waveforms reaching its meta-atoms to a reception radio-frequency (RF) chain, enabling signal/channel parameter estimation. We particularly focus on the scenarios where the user is located in the far-field of all the R-RIS subarrays, and present a three-dimensional (3D) localization method which is based on narrowband signaling and angle of arrival (AoA) estimates of the impinging signals at each single-receive-RF R-RIS subarray. For the AoA estimation, which relies on spatially sampled versions of the received signals via each subarray\u27s phase configuration of meta-atoms, we devise an off-grid atomic norm minimization approach, which is followed by subspace-based root multiple signal classification (MUSIC). The AoA estimates are finally combined via a least-squared line intersection method to obtain the position coordinates of a user emitting synchronized localization pilots. Our derived theoretical Cram\ue9r Rao lower bounds (CRLBs) on the estimation parameters, which are compared with extensive computer simulation results of our localization approach, verify the effectiveness of the proposed R-RIS-empowered 3D localization system, which is showcased to offer cm-level positioning accuracy. Our comprehensive performance evaluations also demonstrate the impact of various system parameters on the localization performance, namely the training overhead and the distance between the R-RIS and the user, as well as the spacing among the R-RIS\u27s subarrays and its partitioning patterns
The Schottky barrier transistor in emerging electronic devices
Full text linkThis paper explores how the Schottky barrier (SB) transistor is used in a variety of applications and material systems. A discussion of SB formation, current transport processes, and an overview of modeling are first considered. Three discussions follow, which detail the role of SB transistors in high performance, ubiquitous and cryogenic electronics. For high performance computing, the SB typically needs to be minimized to achieve optimal performance and we explore the methods adopted in carbon nanotube technology and two-dimensional electronics. On the contrary for ubiquitous electronics, the SB can be used advantageously in source-gated transistors and reconfigurable field-effect transistors (FETs) for sensors, neuromorphic hardware and security applications. Similarly, judicious use of an SB can be an asset for applications involving Josephson junction FETs
Similarities of Testing Programmed and Learnt Software
No full textThis study examines to what extent the testing of traditional software components and machine learning (ML) models fundamentally differs or not. While some researchers argue that ML software requires new concepts and perspectives for testing, our analysis highlights that, at a fundamental level, the specification and testing of a software component are not dependent on the development process used or on implementation details. Although the software engineering/computer science (SE/CS) and Data Science/ML (DS/ML) communities have developed different expectations, unique perspectives, and varying testing methods, they share clear commonalities that can be leveraged. We argue that both areas can learn from each other, and a non-dual perspective could provide novel insights not only for testing ML but also for testing traditional software. Therefore, we call upon researchers from both communities to collaborate more closely and develop testing methods and tools that can address both traditional and ML software components. While acknowledging their differences has merits, we believe there is great potential in working on unified methods and tools that can address both types of software
A ring-like accretion structure in M87 connecting its black hole and jet
Full text linkThe nearby radio galaxy M87 is a prime target for studying black hole accretion and jet formation1,2. Event Horizon Telescope observations of M87 in 2017, at a wavelength of 1.3 mm, revealed a ring-like structure, which was interpreted as gravitationally lensed emission around a central black hole3. Here we report images of M87 obtained in 2018, at a wavelength of 3.5 mm, showing that the compact radio core is spatially resolved. High-resolution imaging shows a ring-like structure of [Formula: see text] Schwarzschild radii in diameter, approximately 50% larger than that seen at 1.3 mm. The outer edge at 3.5 mm is also larger than that at 1.3 mm. This larger and thicker ring indicates a substantial contribution from the accretion flow with absorption effects, in addition\ua0to the gravitationally lensed ring-like emission. The images show that the edge-brightened jet connects to the accretion flow of the black hole. Close to the black hole, the emission profile of the jet-launching region is wider than the expected profile of a black-hole-driven jet, suggesting the possible presence of a wind associated with the accretion flow
Performance of Quantized Massive MIMO with Fronthaul Rate Constraint over Quasi-Static Channels
Full text linkWe provide a rigorous framework for characterizing and numerically evaluating the error probability achievable in the uplink and downlink of a fully digital quantized multiuser multiple-input multiple-output (MIMO) system. We assume that the system operates over a quasi-static channel that does not change across the finite-length transmitted codewords, and only imperfect channel state information (CSI) is available at the base station (BS) and at the user equipments. The need for the novel framework developed in this paper stems from the fact that, for the quasi-static scenario, commonly used signal-to-interference-and-distortion-ratio expressions that depend on the variance of the channel estimation error are not relatable to any rigorous information-theoretic achievable-rate bound. We use our framework to investigate how the performance of a fully digital massive MIMO system subject to a fronthaul rate constraint, which imposes a limit on the number of samples per second produced by the analog-to-digital and digital-to-analog converters (ADCs and DACs), depends on the number of BS antennas and on the precision of the ADCs and DACs. In particular, we characterize, for a given fronthaul constraint, the trade-off between the number of antennas and the resolution of the data converters, and discuss how this trade-off is influenced by the accuracy of the available CSI. Our framework captures explicitly the cost, in terms of spectral efficiency, of pilot transmission—an overhead that the outage capacity, the classic asymptotic metric used in this scenario, cannot capture. We present extensive numerical results that validate the accuracy of the proposed framework and allow us to characterize, for a given fronthaul constraint, the optimal number of antennas and the optimal resolution of the converters as a function of the transmitted power and of the available CSI
Cheap and secure metatransactions on the blockchain using hash-based authorisation and preferred batchers
Full text linkSmart contracts are self-executing programs running in the blockchain allowing for decentralised storage and execution without a middleman. On-chain execution is expensive, with miners charging fees for distributed execution according to a cost model defined in the protocol. In particular, transactions have a high fixed cost. We present MultiCall, a transaction-batching interpreter for Ethereum that reduces the cost of smart contract executions by gathering multiple users’ transactions into a batch. Our current implementation of MultiCall includes the following features: the ability to emulate Ethereum calls and create transactions, both from MultiCall itself and using an identity unique to the user; the ability to cheaply pay Ether to other MultiCall users; and the ability to authorise emulated transactions on behalf of multiple users in a single transaction using hash-based authorisation rather than more expensive signatures. This improves upon a previous version of MultiCall. Our experiments show that MultiCall provides a saving between 57% and 99% of the fixed transaction cost compared with the standard approach of sending Ethereum transactions directly. Besides, we also show how to prevent an economic attack exploiting the metatransaction feature, describe a generic protocol for hash-based authorisation of metatransactions, and analyse how to minimise its off-chain computational and storage cost