Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain-inspired self-organization with cellular neuromorphic computing for multimodal unsupervised learning

Cortical plasticity is one of the main features that enable our ability to learn and adapt in our environment. Indeed, the cerebral cortex self-organizes itself through structural and synaptic plasticity mechanisms that are very likely at the basis of an extremely interesting characteristic of the human brain development: the multimodal association. In spite of the diversity of the sensory modalities, like sight, sound and touch, the brain arrives at the same concepts (convergence). Moreover, biological observations show that one modality can activate the internal representation of another modality when both are correlated (divergence). In this work, we propose the Reentrant Self-Organizing Map (ReSOM), a brain-inspired neural system based on the reentry theory using Self-Organizing Maps and Hebbian-like learning. We propose and compare different computational methods for unsupervised learning and inference, then quantify the gain of the ReSOM in a multimodal classification task. The divergence mechanism is used to label one modality based on the other, while the convergence mechanism is used to improve the overall accuracy of the system. We perform our experiments on a constructed written/spoken digits database and a Dynamic Vision Sensor (DVS)/EletroMyoGraphy (EMG) hand gestures database. The proposed model is implemented on a cellular neuromorphic architecture that enables distributed computing with local connectivity. We show the gain of the so-called hardware plasticity induced by the ReSOM, where the system’s topology is not fixed by the user but learned along the system’s experience through self-organization.
Integrality of twisted L-values of elliptic curves

Under suitable, fairly weak hypotheses on an elliptic curve $E/\mathbb{Q}$ and a primitive non-trivial Dirichlet character $\chi$, we show that the algebraic $L$-value $\mathscr{L}(E,\chi)$ at $s=1$ is an algebraic integer. For instance, for semistable curves $\mathscr{L}(E,\chi)$ is integral whenever $E$ admits no isogenies defined over $\mathbb{Q}$.
Decomposition of Total Effect with the Notion of Natural Counterfactual Interaction Effect

Mediation analysis serves as a crucial tool to obtain causal inference based on directed acyclic graphs, which has been widely employed in the areas of biomedical science, social science, epidemiology and psychology. Decomposition of total effect provides a deep insight to fully understand the casual contribution from each path and interaction term. Since the four-way decomposition method was proposed to identify the mediated interaction effect in counterfactual framework, the idea had been extended to a more sophisticated scenario with non-sequential multiple mediators. However, the method exhibits limitations as the causal structure contains direct causal edges between mediators, such as inappropriate modeling of dependence and non-identifiability. We develop the notion of natural counterfactual interaction effect and find that the decomposition of total effect can be consistently realized with our proposed notion. Furthermore, natural counterfactual interaction effect overcomes the drawbacks and possesses a clear and significant interpretation, which may largely improve the capacity of researchers to analyze highly complex causal structures.
Inter-Region Affinity Distillation for Road Marking Segmentation

We study the problem of distilling knowledge from a large deep teacher network to a much smaller student network for the task of road marking segmentation. In this work, we explore a novel knowledge distillation (KD) approach that can transfer ‘knowledge’ on scene structure more effectively from a teacher to a student model. Our method is known as Inter-Region Affinity KD (IntRA-KD). It decomposes a given road scene image into different regions and represents each region as a node in a graph. An inter-region affinity graph is then formed by establishing pairwise relationships between nodes based on their similarity in feature distribution. To learn structural knowledge from the teacher network, the student is required to match the graph generated by the teacher. The proposed method shows promising results on three large-scale road marking segmentation benchmarks, i.e., ApolloScape, CULane and LLAMAS, by taking various lightweight models as students and ResNet-101 as the teacher. IntRA-KD consistently brings higher performance gains on all lightweight models, compared to previous distillation methods. Our code is available at https://github.com/ cardwing/Codes-for-IntRA-KD.
Improving Expressivity of Graph Neural Networks

We propose a Graph Neural Network with greater expressive power than commonly used GNNs — not constrained to only differentiate between graphs that Weisfeiler-Lehman test recognizes to be non-isomorphic. We use a graph attention network with expanding attention window that aggregates information from nodes exponentially far away. We also use partially random initial embeddings, allowing differentiation between nodes that would otherwise look the same. This could cause problem with a traditional dropout mechanism, therefore we use a "head dropout", randomly ignoring some attention heads rather than some dimensions of the embedding.
Quasi‐stationary Monte Carlo and the ScaLE algorithm

This paper introduces a class of Monte Carlo algorithms which are based on the simulation of a Markov process whose quasi‐stationary distribution coincides with a distribution of interest. This differs fundamentally from, say, current Markov chain Monte Carlo methods which simulate a Markov chain whose stationary distribution is the target. We show how to approximate distributions of interest by carefully combining sequential Monte Carlo methods with methodology for the exact simulation of diffusions. The methodology introduced here is particularly promising in that it is applicable to the same class of problems as gradient‐based Markov chain Monte Carlo algorithms but entirely circumvents the need to conduct Metropolis–Hastings type accept–reject steps while retaining exactness: the paper gives theoretical guarantees ensuring that the algorithm has the correct limiting target distribution. Furthermore, this methodology is highly amenable to ‘big data’ problems. By employing a modification to existing naive subsampling and control variate techniques it is possible to obtain an algorithm which is still exact but has sublinear iterative cost as a function of data size.
First-Principles Theory of Current-Induced Spin-Orbital Coupled Dynamics in Magnetic Heterostructures

Motivated by the rising importance of understanding various competing mechanisms to current-induced torque in complex magnets, we develop a unified theory of current-induced spin-orbital coupled dynamics, which tracks the transfer of angular momentum between different degrees of freedom in solids: spin and orbital of the electron, lattice, and local magnetic moment. From the continuity equations for the spin and orbital angular momenta, we derive equations of motion that relate spin and orbital current fluxes and torques describing the transfer of angular momentum between different degrees of freedom, in a steady state under an external electric field. We apply our formalism to two different magnetic bilayers, Fe/W(110) and Ni/W(110), where the orbital and spin Hall effects in W have opposite sign and the resulting spin- and orbital-mediated torques can compete with each other. We find that while the torque arising from the spin Hall effect of W is the dominant mechanism of the current-induced torque in Fe/W(110), the dominant mechanism in Ni/W(110) is the orbital torque originating in the orbital Hall effect of W. It leads to negative and positive effective spin Hall angles, respectively, which can be directly identified in experiments. This clearly demonstrates that our formalism is ideal for studying the angular momentum transfer dynamics in spin-orbit coupled systems as it goes beyond the "spin current picture" by incorporating the spin and orbital degrees of freedom on an equal footing. Our calculation reveals that, in addition to the spin and orbital torque, other contributions such as the interfacial torque and self-induced anomalous torque within the ferromagnet are not negligible in both material. We propose a classification scheme for the mechanisms of current-induced torque in magnetic bilayers and discuss experimental implications of our findings.
Optimizing Cursor Loops in Relational Databases

Loops that iterate over SQL query results are quite common, both in application programs that run outside the DBMS, as well as User Defined Functions (UDFs) and stored procedures that run within the DBMS. It can be argued that set-oriented operations are more efficient and should be preferred over iteration; but from real-world use cases, it is clear that loops over query results are inevitable in many situations, and are preferred by many users. Such loops, known as cursor loops, come with huge trade-offs and overheads w.r. t. performance, resource consumption and concurrency. We present Aggify, a technique for optimizing loops over query results that overcomes all these overheads. It achieves this by automatically generating custom aggregates that are equivalent in semantics to the loop. Thereby, Aggify completely eliminates the loop by rewriting the query to use this generated aggregate. This technique has several advantages such as: (i) pipelining of entire cursor loop operations instead of materialization, (ii) pushing down loop computation from the application layer into the DBMS, closer to the data, (iii) leveraging existing work on optimization of aggregate functions, resulting in efficient query plans. We describe the technique underlying Aggify and present our experimental evaluation over benchmarks as well as real workloads that demonstrate the significant benefits of this technique.
The H2O Spectrum of the Massive Protostar AFGL 2136 IRS 1 from 2 to 13 μm at High Resolution: Probing the Circumstellar Disk

We have observed the massive protostar AFGL 2136 IRS 1 in multiple wavelength windows in the near- to mid-infrared at high (∼3 km s−1) spectral resolution using VLT+CRIRES, SOFIA+EXES, and Gemini North+TEXES. There is an abundance of H2O absorption lines from the ν1 and ν3 vibrational bands at 2.7 μm, from the ν2 vibrational band at 6.1 μm, and from pure rotational transitions near 10–13 μm. Analysis of state-specific column densities derived from the resolved absorption features reveals that an isothermal absorbing slab model is incapable of explaining the relative depths of different absorption features. In particular, the strongest absorption features are much weaker than expected, indicating optical depth effects resulting from the absorbing gas being well mixed with the warm dust that serves as the “background” continuum source at all observed wavelengths. The velocity at which the strongest H2O absorption occurs coincides with the velocity centroid along the minor axis of the compact disk in Keplerian rotation recently observed in H2O emission with ALMA. We postulate that the warm regions of this dust disk dominate the continuum emission at near- to mid-infrared wavelengths, and that H2O and several other molecules observed in absorption are probing this disk. Absorption line profiles are not symmetric, possibly indicating that the warm dust in the disk that produces the infrared continuum has a nonuniform distribution similar to the substructure observed in 1.3 mm continuum emission.
Properties of the environment around active galactic nucleus / luminous galaxy pairs through the HSC wide survey

We investigated the properties of AGN environments, particularly environments where the association of luminous galaxies (LGs) is found within 4~Mpc from AGNs with redshifts of 0.8 -- 1.1. For comparison, three additional AGN environments, (namely, AGNs of all types, type~1 AGNs with X-ray and/or radio detection, and type~2 AGNs) and an environment of blue $M_{*}$, characteristic luminosity of the Schechter function, galaxies were investigated. The cross-correlation function with the surrounding galaxies was measured and compared between the AGN and blue galaxy samples. We also compared the distributions of color, absolute magnitude, and stellar mass of the galaxies around such target objects. The properties of clusters detected using surrounding galaxies selected based on a photometric redshift were examined and compared for different samples. The target AGNs were drawn from the Million Quasars (MILLIQUAS) catalog, and the blue galaxies were drawn from six redshift survey catalogs (SDSS, WiggleZ, DEEP2, VVDS, VIPERS, and PRIMUS). The galaxies used as a measure of the environment around the targets are drawn from S18a internal data released by the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). We found that, among the five AGN and blue galaxy samples considered, the environment of AGN-LG pairs is the most enriched with luminous galaxies. We also found an enhancement in the number of mass-selected clusters in the AGN-LG pair sample against those in the other samples. The results obtained in this study indicate that existence of multiple clusters is the major driver in the association of AGNs and LGs, rather than a single large-mass dark matter halo hosting the AGN.
Vaginal Cleansing Prior to Cesarean Section and Post-Operative Infectious Morbidity

Objective: To compare the frequency of post-operative infectious morbidity in patients undergoing emergency cesarean section with and without pre-operative vaginal cleansing.Methodology: A Randomized controlled trial in the department of obstetrics and gynecology, PIMS, Islamabad from 1st September 2014 to 31st January 2015 was conducted including 434 patients. Group B women received only abdominal and vulval scrubbing while Group A received additional vaginal cleansing with pyodine. Patients were followed up for development of infectious morbidity up to three weeks. Results: Mean age of 28.4 ± 4.6 years in group A and 27.6 ± 5.9 years in group B. Fever was seen in 9 (4.1%) women in group A and 16 (7.4%) in group B (p=0.149). Endometritis was noted in 3 (1.4%) women in group A and 19 (8.8%) in group B (p=0.000). Wound Infection occurred in 3 (1.4%) women in group A and 8 (3.7%) in group B (p=0.126). Conclusion: Use of antiseptic for vaginal cleaning before cesarean section decreased postpartum infectious morbidity due to endometritis.
Computable analysis and notions of continuity in Coq

We give a number of formal proofs of theorems from the field of computable analysis. Many of our results specify executable algorithms that work on infinite inputs by means of operating on finite approximations and are proven correct in the sense of computable analysis. The development is done in the proof assistant Coq and heavily relies on the Incone library for information theoretic continuity. This library is developed by one of the authors and the paper can be used as an introduction to the library as it describes many of its most important features in detail. While the ability to have full executability in a formal development of mathematical statements about real numbers and the like is not a feature that is unique to the Incone library, its original contribution is to adhere to the conventions of computable analysis to provide a general purpose interface for algorithmic reasoning on continuous structures. The results that provide complete computational content include that the algebraic operations and the efficient limit operator on the reals are computable, that certain countably infinite products are isomorphic to spaces of functions, compatibility of the enumeration representation of subsets of natural numbers with the abstract definition of the space of open subsets of the natural numbers, and that continuous realizability implies sequential continuity. We also formalize proofs of non-computational results that support the correctness of our definitions. These include that the information theoretic notion of continuity used in the library is equivalent to the metric notion of continuity on Baire space, a complete comparison of the different concepts of continuity that arise from metric and represented-space structures and the discontinuity of the unrestricted limit operator on the real numbers and the task of selecting an element of a closed subset of the natural numbers.
Prevalence of congenital heart disease among school children of Sahafa Town, Sudan

The prevalence of congenital heart disease among schoolchildren aged 5-15 years was studied as part of Phase 1 of the WHO Global Rheumatic Fever/Rheumatic Heart Disease Prevention Programme in Sudan. A total of 13 322 schoolchildren in Sahafa Town, Khartoum, was examined from 1986 to 1990 representing 70% of the total target population. There were 27 cases of congenital heart disease giving a prevalence rate of 2.0 per 1000. Ventricular septal defect, atrial septal defect [ASD], patent ductus arteriosus [PDA] and tetralogy of Fallot made up 85% of the cases. PDA and ASD were twice as common in females as in males. The prevalence rate is comparable to that of similar African countries but lower than European and north American rates
Discovery of radio jets in the Phoenix galaxy cluster center

We report the results of the Australia Telescope Compact Array (ATCA) 15 mm observation of the Phoenix galaxy cluster possessing an extreme star-burst brightest cluster galaxy (BCG) at the cluster center. We spatially resolved radio emission around the BCG, and found diffuse bipolar and bar-shape structures extending from the active galactic nucleus (AGN) of the BCG. They are likely radio jets/lobes, whose sizes are ∼10–20 kpc and locations are aligned with X-ray cavities. If we assume that the radio jets/lobes expand with the sound velocity, their ages are estimated to be ∼10 Myr. We also found compact radio emissions near the center and suggest that they are more young bipolar jets ∼1 Myr in age. Moreover, we found extended radio emission surrounding the AGN and discussed the possibility that the component is a product of the cooling flow, by considering synchrotron radiation partially absorbed by molecular clumps, free–free emission from the warm ionized gas, and the spinning dust emission from the dusty circumgalactic medium.
Growth of quadratic forms under Anosov subgroups

Let $\rho:\Gamma\rightarrow PSL_d(\mathbb{R})$ be a Zariski dense Anosov representation (in the full flag variety of $PSL_d(\mathbb{R})$), where $d\geq 3$. Let also $0<p<d$ be an integer. To each homothety class $o$ of quadratic forms of signature $(p,d-p)$ on $\mathbb{R}^d$ we look at a totally geodesic copy $\mathsf{S}^o$ of the Riemannian symmetric space of $PSO(o)$, inside the Riemannian symmetric space of $PSL_d(\mathbb{R})$. We precisely describe an open subset of quadratic forms $o$ for which the function $$t\mapsto\#\lbrace \gamma\in\Gamma: \hspace{0,3cm} d(\mathsf{S}^o,\rho\gamma\cdot\mathsf{S}^o)\leq t\rbrace$$ is finite and bounded between two purely exponential functions of the same rate. Under an extra assumption, satisfied for instance when the limit set of $\rho$ is connected, we show a precise asymptotic as $t\rightarrow\infty$ when a linear functional in the interior of the dual limit cone is given.
The Role of Stem Noise in Visual Perception and Image Quality Measurement

This paper considers reference free quality assessment of distorted and noisy images. Specifically, it considers the first and second order statistics of stem noise that can be evaluated given any image. In the research field of Image quality Assessment (IQA), the stem noise is defined as the input of an Auto Regressive (AR) process, from which a low-energy and de-correlated version of the image can be recovered. To estimate the AR model parameters and associated stem noise energy, the Yule-walker equations are used such that the accompanying Auto Correlation Function (ACF) coefficients can be treated as model parameters for image reconstruction. To characterize systematic signal dependent and signal independent distortions, the mean and variance of stem noise can be evaluated over the image. Crucially, this paper shows that these statistics have a predictive validity in relation to human ratings of image quality. Furthermore, under certain kinds of image distortion, stem noise statistics show very significant correlations with established measures of image quality.
Detecting critical bugs in SMT solvers using blackbox mutational fuzzing

Formal methods use SMT solvers extensively for deciding formula satisfiability, for instance, in software verification, systematic test generation, and program synthesis. However, due to their complex implementations, solvers may contain critical bugs that lead to unsound results. Given the wide applicability of solvers in software reliability, relying on such unsound results may have detrimental consequences. In this paper, we present STORM, a novel blackbox mutational fuzzing technique for detecting critical bugs in SMT solvers. We run our fuzzer on seven mature solvers and find 29 previously unknown critical bugs. STORM is already being used in testing new features of popular solvers before deployment.
On the monopole Lefschetz number of finite-order diffeomorphisms

Let $K$ be a knot in an integral homology 3-sphere $Y$, and $\Sigma$ the corresponding $n$-fold cyclic branched cover. Assuming that $\Sigma$ is a rational homology sphere (which is always the case when $n$ is a prime power), we give a formula for the Lefschetz number of the action that the covering translation induces on the reduced monopole homology of $\Sigma$. The proof relies on a careful analysis of the Seiberg--Witten equations on 3-orbifolds and of various $\eta$-invariants. We give several applications of our formula: (1) we calculate the Seiberg--Witten and Furuta--Ohta invariants for the mapping tori of all semi-free actions of $Z/n$ on integral homology 3-spheres; (2) we give a novel obstruction (in terms of the Jones polynomial) for the branched cover of a knot in $S^3$ being an $L$-space; (3) we give a new set of knot concordance invariants in terms of the monopole Lefschetz numbers of covering translations on the branched covers.
On Error Correction Neural Networks for Economic Forecasting

Recurrent neural networks (RNNs) are more suitable for learning non-linear dependencies in dynamical systems from observed time series data. In practice, all the external variables driving such systems are not known a priori, especially in economical forecasting. A class of RNNs called Error Correction Neural Networks (ECNNs) was designed to compensate for missing input variables. It does this by feeding back in the current step the error made in the previous step. The ECNN is implemented in Python by the computation of the appropriate gradients and it is tested on stock market predictions. As expected it outperformed the simple RNN and LSTM and other hybrid models which involve a de-noising pre-processing step. The intuition for the latter is that de-noising may lead to loss of information.