Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance analysis of SPAD-based optical wireless communication with OFDM

In recent years, there has been a growing interest in the use of a single-photon avalanche diode (SPAD) in optical wireless communication (OWC). The SPAD operates in the Geiger mode and can act as a photon counting receiver obviating the need for a transimpedance amplifier. Although a SPAD receiver can provide higher sensitivity compared to traditional linear photodetectors, it suffers from dead-time-induced nonlinearity. To improve the data rates of SPAD-based OWC systems, optical orthogonal frequency division multiplexing (OFDM) can be employed. This paper provides a comprehensive theoretical analysis of the SPAD-based OWC systems using direct-current-biased optical OFDM signaling considering the effects of signal clipping, SPAD nonlinearity, and signal-dependent shot noise. An equivalent additive Gaussian noise channel model is proposed to describe the performance of the SPAD-based OFDM system. The statistics of the proposed channel model and the analytical expressions of the signal-to-noise ratio and bit error rate are derived in closed forms. By means of extensive numerical results, the impact of the unique receiver nonlinearity on the system performance is investigated. The results demonstrate new insights into different optical power regimes of reliable operation for SPAD-based OFDM systems even well beyond the SPAD saturation level.
The periodic b-equation and Euler equations on the circle

In this note we show that the periodic b-equation can only be realized as a Euler equation on the Lie group Diff∞(S1) of all smooth and orientation preserving diffeomorphisms on the circle if b=2, i.e., for the Camassa–Holm equation. In this case the inertia operator generating the metric on Diff∞(S1) is given by A=1−∂x2. In contrast, the Degasperis–Procesi equation, for which b=3, is not a Euler equation on Diff∞(S1) for any inertia operator. Our result generalizes a recent result of Kolev [“Some geometric investigations on the Degasperis-Procesi shallow water equation,” Wave Motion 46, 412–419 (2009)].
Improving Ads-Profitability Using Traffic-Fingerprints

This paper introduces the concept of traffic-fingerprints, i.e., normalized 24-dimensional vectors representing a distribution of daily traffic on a web page. Using k-means clustering we show that similarity of traffic-fingerprints is related to the similarity of profitability time patterns for ads shown on these pages. In other words, these fingerprints are correlated with the conversions rates, thus allowing us to argue about conversion rates on pages with negligible traffic. By blocking or unblocking whole clusters of pages we were able to increase the revenue of online campaigns by more than 50%.
A Neural Corpus Indexer for Document Retrieval

Current state-of-the-art document retrieval solutions mainly follow an index-retrieve paradigm, where the index is hard to be directly optimized for the final retrieval target. In this paper, we aim to show that an end-to-end deep neural network unifying training and indexing stages can significantly improve the recall performance of traditional methods. To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query. To optimize the recall performance of NCI, we invent a prefix-aware weight-adaptive decoder architecture, and leverage tailored techniques including query generation, semantic document identifiers, and consistency-based regularization. Empirical studies demonstrated the superiority of NCI on two commonly used academic benchmarks, achieving +21.4% and +16.8% relative enhancement for Recall@1 on NQ320k dataset and R-Precision on TriviaQA dataset, respectively, compared to the best baseline method.
Surprising Instabilities in Training Deep Networks and a Theoretical Analysis

We discover restrained numerical instabilities in current training practices of deep networks with stochastic gradient descent (SGD). We show numerical error (on the order of the smallest floating point bit) induced from floating point arithmetic in training deep nets can be amplified significantly and result in significant test accuracy variance, comparable to the test accuracy variance due to stochasticity in SGD. We show how this is likely traced to instabilities of the optimization dynamics that are restrained, i.e., localized over iterations and regions of the weight tensor space. We do this by presenting a theoretical framework using numerical analysis of partial differential equations (PDE), and analyzing the gradient descent PDE of convolutional neural networks (CNNs). We show that it is stable only under certain conditions on the learning rate and weight decay. We show that rather than blowing up when the conditions are violated, the instability can be restrained. We show this is a consequence of the non-linear PDE associated with the gradient descent of the CNN, whose local linearization changes when over-driving the step size of the discretization, resulting in a stabilizing effect. We link restrained instabilities to the recently discovered Edge of Stability (EoS) phenomena, in which the stable step size predicted by classical theory is exceeded while continuing to optimize the loss and still converging. Because restrained instabilities occur at the EoS, our theory provides new predictions about the EoS, in particular, the role of regularization and the dependence on the network complexity.
PIDNet: A Real-time Semantic Segmentation Network Inspired from PID Controller

Two-branch network architecture has shown its efﬁciency and effectiveness for real-time semantic segmentation tasks. However, direct fusion of low-level details and high-level semantics will lead to a phenomenon that the detailed features are easily overwhelmed by surrounding contextual information, namely overshoot in this paper, which limits the improvement of the accuracy of existed two-branch models. In this paper, we bridge a connection between Convolu-tional Neural Network (CNN) and Proportional-Integral-Derivative (PID) controller and reveal that the two-branch network is nothing but a Proportional-Integral (PI) controller, which inherently suffers from the similar overshoot issue. To alleviate this issue, we propose a novel three-branch network architecture: PIDNet, which possesses three branches to parse the detailed, context and boundary information (derivative of semantics), respectively, and employs boundary attention to guide the fusion of detailed and context branches in ﬁnal stage. The family of PIDNets achieve the best trade-off between inference speed and accuracy and their test accuracy surpasses all the existed models with similar inference speed on Cityscapes, CamVid and COCO-Stuff datasets. Especially, PIDNet-S achieves 78.6% mIOU with inference speed of 93.2 FPS on Cityscapes test set and 80.1% mIOU with speed of 153.7 FPS on CamVid test set.
Spread of SARS-CoV-2 in a SIS model with vaccination and breakthrough infection (preprint)

Although previous infection and vaccination provide protection against SARS-CoV-2 infection, both reinfection and breakthrough infection are possible events whose occurrence would increase with time after first exposure to the antigen and with the emergence of new variants of the virus. Periodic vaccination could counteract this decline in protection. In the present work, our aim was to develop and explore a model of SARS-CoV-2 spread with vaccination, reinfection and breakthrough infection. A modified deterministic SIS (Susceptible-Infected-Susceptible) model represented by a system of differential equations was designed. As in any SIS model, the population was divided into susceptible and infected individuals. But in our design, susceptible individuals were, in turn, grouped into three consecutive categories whose susceptibility increases with time after infection or vaccination. The model was studied by means of computer simulations, which were analysed qualitatively. The results obtained show that the prevalence, after oscillating between peaks and valleys, reaches a plateau phase. Moreover, as might be expected, the magnitude of the peaks and plateaus increases as the infection rate rises, the vaccination rate decreases and the rate of decay of protection conferred by vaccination or previous infection increases. Therefore, the present study suggests that, at least under certain conditions, the spread of SARS-CoV-2, although it could experience fluctuations, would finally evolve into an endemic form, with a more or less stable prevalence that would depend on the levels of infection and vaccination, and on the kinetics of post-infection and post-vaccination protection. However, it should be kept in mind that our development is a theoretical scheme with many limitations. For this reason, its predictions should be considered with great care.
Simulations of the spectral resolving power of a compact space-borne immersion-echelle spectrometer using mid-infrared wave tracing

Abstract. We performed wave-optics-based numerical simulations at mid-infrared wavelengths to investigate how the presence or absence of entrance slits and optical aberrations affect the spectral resolving power R of a compact, high-spectral-resolving-power spectrometer containing an immersion-echelle grating. We tested three cases of telescope aberration (aberration-free, astigmatism, and spherical aberration), assuming the aberration budget of the Space Infrared Telescope for Cosmology and Astrophysics, which has a 20 μm wavelength diffraction limit. In cases with a slit, we found that the value of R at around 10 to 20 μm is approximately independent of the assumed aberrations, which is significantly different from the prediction of geometrical optics. Our results also indicate that diffraction from the slit improves R by enlarging the effective illuminated area on the grating window and that this improvement decreases at short wavelengths. For the slit-less cases, we found that the impact of aberrations on R can be roughly estimated using the Strehl ratio.
The Effect of External Debt on Greenhouse Gas Emissions

We estimate the causal effect of external debt on greenhouse gas emissions in a panel of 78 emerging market and developing economies over the 1990-2015 period. Unlike previous literature, we use external instruments to address the potential endogeneity in the relationship between external debt and greenhouse gas emissions. Specifically, we use international liquidity shocks as instrumental variables for external debt. We find that dealing with the potential endogeneity problem brings about a positive and statistically significant effect of external debt on greenhouse gas emissions: a 1 percentage point (pp.) rise in external debt causes, on average, a 0.4% increase in greenhouse gas emissions. One possible mechanism of action could be that, as external debt increases, governments are less able to enforce environmental regulations because their main priority is to increase the tax base to pay increasing debt services or because they are captured by the private sector who owns that debt and prevented from tightening such regulations.
A highly dynamic small-scale jet in a polar coronal hole

We present an observational study of the plasma dynamics at the base of a solar coronal jet, using high resolution extreme ultraviolet imaging data taken by the Extreme Ultraviolet Imager on board Solar Orbiter, and by the Atmospheric Imaging Assembly on board Solar Dynamics Observatory. We observed multiple plasma ejection events over a period of ∼ 1 hour from a dome-like base that is ca. 4 Mm wide and is embedded in a polar coronal hole. Within the dome below the jet spire, multiple plasma blobs with sizes around 1–2 Mm propagate upwards to the dome apex with speeds of the order of the sound speed (ca. 120 km s − 1 ). Upon reaching the apex, some of these blobs initiate ﬂows with similar speeds towards the other footpoint of the dome. At the same time, high speed super- sonic outﬂows ( ∼ 230 km s − 1 ) are detected along the jet spire. These outﬂows as well as the intensity near the dome apex appear to be repetitive. Furthermore, during its evolution, the jet undergoes many complex morphological changes, including transitions between the standard and blowout type eruption. These new observational results highlight the underlying complexity of the reconnection process that powers these jets and they also provide insights into the plasma response when subjected to rapid energy
A quantum central limit theorem for non-equilibrium systems: exact local relaxation of correlated states

We prove that quantum many-body systems on a one-dimensional lattice locally relax to Gaussian states under non-equilibrium dynamics generated by a bosonic quadratic Hamiltonian. This is true for a large class of initial states—pure or mixed—which have to satisfy merely weak conditions concerning the decay of correlations. The considered setting is a proven instance of a situation where dynamically evolving closed quantum systems locally appear as if they had truly relaxed, to maximum entropy states for fixed second moments. This furthers the understanding of relaxation in suddenly quenched quantum many-body systems. The proof features a non-commutative central limit theorem for non-i.i. d. random variables, showing convergence to Gaussian characteristic functions, giving rise to trace-norm closeness. We briefly link our findings to the ideas of typicality and concentration of measure.
On the duality between contrastive and non-contrastive self-supervised learning

Recent approaches in self-supervised learning of image representations can be categorized into different families of methods and, in particular, can be divided into contrastive and non-contrastive approaches. While differences between the two families have been thoroughly discussed to motivate new approaches, we focus more on the theoretical similarities between them. By designing contrastive and covariance based non-contrastive criteria that can be related algebraically and shown to be equivalent under limited assumptions, we show how close those families can be. We further study popular methods and introduce variations of them, allowing us to relate this theoretical result to current practices and show the influence (or lack thereof) of design choices on downstream performance. Motivated by our equivalence result, we investigate the low performance of SimCLR and show how it can match VICReg's with careful hyperparameter tuning, improving significantly over known baselines. We also challenge the popular assumption that non-contrastive methods need large output dimensions. Our theoretical and quantitative results suggest that the numerical gaps between contrastive and non-contrastive methods in certain regimes can be closed given better network design choices and hyperparameter tuning. The evidence shows that unifying different SOTA methods is an important direction to build a better understanding of self-supervised learning.
Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future

Annotated data is an essential ingredient in natural language processing for training and evaluating machine learning models. It is therefore very desirable for the annotations to be of high quality. Recent work, however, has shown that several popular datasets contain a surprising number of annotation errors or inconsistencies. To alleviate this issue, many methods for annotation error detection have been devised over the years. While researchers show that their approaches work well on their newly introduced datasets, they rarely compare their methods to previous work or on the same datasets. This raises strong concerns on methods’ general performance and makes it difficult to assess their strengths and weaknesses. We therefore reimplement 18 methods for detecting potential annotation errors and evaluate them on 9 English datasets for text classification as well as token and span labeling. In addition, we define a uniform evaluation setup including a new formalization of the annotation error detection task, evaluation protocol, and general best practices. To facilitate future research and reproducibility, we release our datasets and implementations in an easy-to-use and open source software package.1
On the relation of Carleson's embedding and the maximal theorem in the context of Banach space geometry

Hyt\"onen, McIntosh and Portal (J. Funct. Anal., 2008) proved two vector-valued generalizations of the classical Carleson embedding theorem, both of them requiring the boundedness of a new vector-valued maximal operator, and the other one also the type p property of the underlying Banach space as an assumption. We show that these conditions are also necessary for the respective embedding theorems, thereby obtaining new equivalences between analytic and geometric properties of Banach spaces.
A Comparative Cost Analysis of Local Anesthesia versus Brachial Plexus Block for Complex Hand Surgery

Background: Local anesthesia has shown to be safe and cost-effective for elective hand surgery procedures performed outside of the operating room. The economic benefits of local anesthesia compared to regional anesthesia for hand surgeries performed in the operating room involving repair of tendons, nerves, arteries, or bones are unclear. This study aimed to compare costs pertinent to hand surgeries performed in the main operating room under local anesthesia (LA) or brachial plexus (BP) block. Methods: We performed a cross-sectional study on the first 70 randomized patients from a prospective controlled trial of anesthesia modalities for hand surgery. The primary objective was to determine the mean anesthesia-related cost, and the secondary objectives were to analyze block performance time, block onset time, duration of anesthesia, duration of surgery, and time in the recovery room. Results: The mean anesthesia-related cost of performing hand surgery under LA as a wrist and/or digital block was $236 ± 30, compared to $435 ± 43 for BP, a difference of $199 per case. The mean block performance time was shorter for LA (1.3 minutes) versus BP (7.0 minutes). The mean anesthesia-related time was longer in BP (30.7 ± 16 minutes) compared to LA (17.7 ± 6.7 minutes), and consequently the total anesthesia time was longer in BP. Conclusions: We demonstrated that local anesthesia compared to brachial plexus block achieved substantial cost savings in complex hand surgeries by decreasing major expenses. In an era of cost-consciousness, the use of LA represents an important modality for health systems to optimize patient flow and increase cost-effectiveness.
Nilpotent groups without exactly polynomial Dehn function

We prove super‐quadratic lower bounds for the growth of the filling area function of a certain class of nilpotent Lie groups. This class contains groups for which it is known that their Dehn function grows no faster than n2log n. We therefore obtain the existence of (finitely generated) nilpotent groups whose Dehn functions do not have exactly polynomial growth and we thus answer a well‐known question about the possible growth rate of Dehn functions of nilpotent groups.
Ameloblastomas mimicking apical periodontitis: a case series

Background Ameloblastomas are benign odontogenic tumors that can eventually mimic the clinical and radiological features of apical periodontitis. The aim of the present study was to evaluate the clinical, radiological and histological characteristics from a series of ameloblastomas mimicking apical periodontitis diagnosed in a 14-year period. Material and Methods all cases histologically diagnosed as ameloblastomas from 2005 to 2018 presenting a clinical diagnosis of periapical lesion of endodontic origin were selected for the study. Clinical, radiological and histological characteristics from all cases were tabulated and descriptively and comparatively analyzed. Results Twenty cases composed the final sample, including 18 solid and 2 unicystic ameloblastomas. Mean age of the affected patients was in the fifth decade with predilection for males (72%). The most common anatomical location was the posterior mandible (55%) and most cases presented a radiolucent unilocular (80%) well-defined (95%) image. Most cases were asymptomatic, but the presence of local swelling and bone cortical rupture were common. Conclusions Ameloblastomas mimicking periapical lesions of endodontic origin are mostly diagnosed in adult males as well-defined radiolucent unilocular lesions producing local swelling and bone cortical rupture. Key words:Ameloblastoma, apical periodontitis, cyst, differencial diagnosis, granuloma, periapical lesion.
Strings from position-dependent noncommutativity

We introduce a new set of noncommutative spacetime commutation relations in two space dimensions. The space–space commutation relations are deformations of the standard flat noncommutative spacetime relations taken here to have position-dependent structure constants. Some of the new variables are non-Hermitian in the most natural choice. We construct their Hermitian counterparts by means of a Dyson map, which also serves to introduce a new metric operator. We propose -like symmetries, i.e. antilinear involutory maps, respected by these deformations. We compute minimal lengths and momenta arising in this space from generalized versions of Heisenberg's uncertainty relations and find that any object in this two-dimensional space is string like, i.e. having a fundamental length in one direction beyond which a resolution is impossible. Subsequently, we formulate and partly solve some simple models in these new variables, the free particle, its -symmetric deformations and the harmonic oscillator.
Reducing age-related Memory Deficits: The Roles of Environmental Support and self-initiated Processing Activities

ABSTRACT Background: The notion that memory performance in older adults can be boosted by information provided by the environment was proposed by Craik (1983). The suggestion was that age-related memory deficits can be attenuated and sometimes even eliminated by a complementary combination of environmental support and consciously controlled self-initiated activities. Objective: The objective of the present article was to review the subsequent empirical and theoretical work on the topics of environmental support and self-initiated ativities as they relate to the effects of aging on human memory. Discussion: The notion of schematic support from the person’s knowledge base is introduced and its relevance discussed. In addition, the effects of various types of support on encoding and retrieval processes in older adults are desribed, and the increasing theoretical importance of executive processes in reducing age-related memory deficits is discussed. Conclusion: As one main conclusion, it is suggested that self-initiated control processes interact with both information provided by the environment and by the person’s knowledge base to improve the effectiveness of encoding and retrieval processing in older adults.
Nearly pseudo-K\"ahler and nearly para-K\"ahler six-manifolds

The subject of this paper is six-dimensional nearly (para-)K\"ahler geometry with pseudo-Riemannian metrics. Firstly, we derive the analogue of the well-known exterior differential system characterising a nearly K\"ahler manifold and prove applications to the automorphism group of a nearly (para-)K\"ahler structure. Secondly, we prove existence and uniqueness results for left-invariant nearly (para-)K\"ahler structures on Lie groups $G \times G$ where $G$ is three-dimensional and simple.