Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mixed-Modeling Framework for Whole-Brain Dynamic 1 Network Analysis 2 3 4

37 The emerging area of dynamic brain network analysis has gained considerable attention in recent 38 years. However, development of multivariate statistical frameworks that allow for examining the 39 associations between phenotypic traits and dynamic patterns of system-level properties of the 40 brain, and drawing statistical inference about such associations, has largely lagged behind. To 41 address this need we developed a mixed-modeling framework that allows for assessing the 42 relationship between any desired phenotype and dynamic patterns of whole-brain connectivity 43 and topology. This novel framework also allows for simulating dynamic brain networks with 44 respect to desired covariates. Unlike current tools which largely use data-driven methods, our 45 model-based method enables aligning neuroscientific hypotheses with the analytic approach. We 46 demonstrate the utility of this model in identifying the relationship between fluid intelligence and 47 dynamic brain networks using resting-state fMRI (rfMRI) data from 200 participants in the 48 Human Connectome Project (HCP) study. We also demonstrate the utility of this model to 49 simulate dynamic brain networks at both group and individual levels. To our knowledge, this 50 approach provides the first model-based statistical method for examining dynamic patterns of 51 system-level properties of the brain and their relationships to phenotypic traits as well as 52 simulating dynamic brain networks. 53 54 55 56 57 58 59 60 61 D ow naded rom httpdirect.m it.edu/netn/article-pdf/doi_a_00238/1989227/netn_a_00238. pdf by gest on 17 Feruary 2022
Sustaining Open Data as a Digital Common – Design principles for Common Pool Resources applied to Open Data Ecosystems

Motivation. Digital commons is an emerging phenomenon and of increasing importance, as we enter a digital society. Open data is one example that makes up a pivotal input and foundation for many of today’s digital services and applications. Ensuring sustainable provisioning and maintenance of the data, therefore, becomes even more important. Aim. We aim to investigate how such provisioning and maintenance can be collaboratively performed in the community surrounding a common. Specifically, we look at Open Data Ecosystems (ODEs), a type of community of actors, openly sharing and evolving data on a technological platform. Method. We use Elinor Ostrom’s design principles for Common Pool Resources as a lens to systematically analyze the governance of earlier reported cases of ODEs using a theory-oriented software engineering framework. Results. We find that, while natural commons must regulate consumption, digital commons such as open data maintained by an ODE must stimulate both use and data provisioning. Governance needs to enable such stimulus while also ensuring that the collective action can still be coordinated and managed within the frame of available maintenance resources of a community. Subtractability is, in this sense, a concern regarding the resources required to maintain the quality and value of the data, rather than the availability of data. Further, we derive empirically-based recommended practices for ODEs based on the design principles by Ostrom for how to design a governance structure in a way that enables a sustainable and collaborative provisioning and maintenance of the data. Conclusion. ODEs are expected to play a role in data provisioning which democratize the digital society and enables innovation from smaller commercial actors. Our empirically based guidelines intend to support this development.
Multi-Bit Relaying Over a Tandem of Channels

We study error exponents for the problem of relaying a message over a tandem of two channels sharing the same transition law, in particular moving beyond the 1-bit setting studied in recent related works. Our main results show that the 1-hop and 2-hop exponents coincide in both of the following settings: (i) the number of messages is fixed, and the channel law satisfies a condition called pairwise reversibility, or (ii) the channel is arbitrary, and a zero-rate limit is taken from above. In addition, we provide various extensions of our results that relax the assumptions of pairwise reversibility and/or the two channels having identical transition laws, and we provide an example for which the 2-hop exponent is strictly below the 1-hop exponent.
The Sparkler: Evolved High-redshift Globular Cluster Candidates Captured by JWST

Using data from JWST, we analyse the compact sources (“sparkles”) located around a remarkable z spec = 1.378 galaxy (the ‘Sparkler) that is strongly gravitationally lensed by the z = 0.39 galaxy cluster SMACS J0723.3-7327. Several of these compact sources can be cross-identified in multiple images, making it clear that they are associated with the host galaxy. Combining data from JWSTs Near-Infrared Camera (NIRCam) with archival data from the Hubble Space Telescope (HST), we perform 0.4–4.4 μm photometry on these objects, finding several of them to be very red and consistent with the colors of quenched, old stellar systems. Morphological fits confirm that these red sources are spatially unresolved even in the strongly magnified JWST/NIRCam images, while the JWST/NIRISS spectra show [Oiii] λ5007 emission in the body of the Sparkler but no indication of star formation in the red compact sparkles. The most natural interpretation of these compact red companions to the Sparkler is that they are evolved globular clusters seen at z = 1.378. Applying Dense Basis spectral energy distribution fitting to the sample, we infer formation redshifts of z form ∼ 7–11 for these globular cluster candidates, corresponding to ages of ∼3.9–4.1 Gyr at the epoch of observation and a formation time just ∼0.5 Gyr after the Big Bang. If confirmed with additional spectroscopy, these red, compact sparkles represent the first evolved globular clusters found at high redshift, which could be among the earliest observed objects to have quenched their star formation in the universe, and may open a new window into understanding globular cluster formation. Data and code to reproduce our results will be made available at http://canucs-jwst.com/sparkler.html.
An Algorithm for Ennola's Second Theorem and Counting Smooth Numbers in Practice

Let Ψ( x, y ) count the number of positive integers n ≤ x such that every prime divisor of n is at most y . There are a number of ap-plications where values of Ψ( x, y ) are needed, such as in optimizing integer factoring and discrete logarithm algorithms [9, 19] and gener-ating factored smooth numbers uniformly at random [3]. Note that such numbers are useful in at least one post-quantum cryptography protocol [8, 21]. Given inputs x and y , what is the best way to estimate Ψ( x, y )? We address this problem in three ways: with a new algorithm to estimate Ψ( x, y ), with a performance improvement to an established algorithm, and with empirically based advice on how to choose an algorithm to estimate Ψ for the given inputs. Our new algorithm to estimate Ψ( x, y ) is based on Ennola’s second theorem [10], which applies when y < (log x ) 3 / 4 − (cid:15) for (cid:15) > 0. It takes O ( y 2 / log y ) arithmetic operations of precomputation and O ( y log y ) operations per evaluation of Ψ. We show how to speed up Algorithm HT [16], which is based on the saddle-point method of Hildebrand and Tenenbaum [14], by a factor proportional to log log x , by applying Newton’s method in a new way. And ﬁnally we give our empirical advice based on ﬁve algorithms to compute estimates for Ψ( x, y ). The challenge here is that the bound-1 aries of the ranges of applicability, as given in theorems, often include unknown constants or small values of (cid:15) > 0, for example, that cannot be programmed directly.
The structure of the narrow emission bands near 10 microns

High quality spectra at 8-13 μm of five compact objects that display narrow infrared emission bands are presented. All of the objects display the well-known 11.25- and 8.56-μm features together with the long wavelength wing of the 7.7-μm band. In addition, weaker bands near 11.05 and 11.5 μm and/or plateau emission between the 11.25- and 12.7-μm features are evident in some of the objects. There is considerable dispersion as to the equivalent width of the features from object to object. The pre-main sequence star TY CrA has a remarkable spectrum, displaying an especially pronounced feature at 11.05 μm, with an intensity 25 per cent that of the 11.25-μm feature, and a very prominent 8.6-μm band
Decomposition and Prediction of Initial Uniform Bi-Directional Water Waves Using an Array of Wave-Rider Buoys

Prediction of incident waves to wave energy converters (WEC) is essential to maximize the energy absorption by controlling the WEC. Nevertheless, little work has been done on the deterministic prediction of bi-directional waves whose wave directions of components are 180 [deg. ] opposite. To decompose and predict such bi-directional waves, an array of three wave-rider buoys are considered. Buoys on both sides are used for decomposing bi-directional waves into progressive and regressive wave components, and the surface elevation of the middle buoy is predicted by these decomposed waves. The deterministic wave prediction is based on the impulse response function, and a cosine-filtered impulse response function is proposed to reduce an error due to the truncation of the infinite length of the function. Predictions of initial uniform bi-directional waves are shown to demonstrate the performance of the impulse response function method to time-series prediction. Both numerical and experimental comparisons are carried out to validate our proposals.
The null distance encodes causality

A Lorentzian manifold, N, endowed with a time function, τ, can be converted into a metric space using the null distance, [Formula: see text], defined by Sormani and Vega [Classical Quant. Grav. 33(8), 085001 (2016)]. We show that if the time function is a regular cosmological time function as studied by Andersson, Galloway, and Howard [Classical Quant. Grav. 15(2), 309–322 (1998)], and also by Wald and Yip [J. Math. Phys. 22, 2659–2665 (1981)], or if, more generally, it satisfies the anti-Lipschitz condition of Chruściel, Grant, and Minguzzi [Ann. Henri Poincare 17(10), 2801–2824 (2016)], then the causal structure is encoded by the null distance in the following sense: for any p ∈ N, there is an open neighborhood U p such that for any q ∈ U p, we have [Formula: see text] if and only if q lies in the causal future of p. The local encoding of causality can be applied to prove the global encoding of causality in a variety of settings, including spacetimes N where τ is a proper function. As a consequence, in dimension n + 1, n ≥ 2, we prove that if there is a bijective map between two such spacetimes, F : M1 → M2, which preserves the cosmological time function, τ2( F( p)) = τ1( p) for any p ∈ M1, and preserves the null distance, [Formula: see text] for any p, q ∈ M1, then there is a Lorentzian isometry between them, F∗ g1 = g2. This yields a canonical procedure allowing us to convert large classes of spacetimes into unique metric spaces with causal structures and time functions. This will be applied in our upcoming work to define spacetime intrinsic flat convergence.
The Core Population and Kinematics of a Massive Clump at Early Stages: An Atacama Large Millimeter/submillimeter Array View

High-mass star formation theories make distinct predictions on the properties of the prestellar seeds of high-mass stars. Observations of the early stages of high-mass star formation can provide crucial constraints, but they are challenging and scarce. We investigate the properties of the prestellar core population embedded in the high-mass clump AGAL014.492-00.139, and we study the kinematics at the clump and clump-to-core scales. We have analyzed an extensive data set acquired with the Atacama Large Millimeter/submillimeter Array interferometer. Applying a dendrogram analysis to the Band 7 o‐H2D+ data, we identified 22 cores. We fitted their average spectra in local thermodinamic equilibrium conditions, and we analyzed their continuum emission at 0.8 mm. The cores have transonic to mildly supersonic turbulence levels and appear to be mostly low-mass, with Mcore<30M⊙ . Furthermore, we have analyzed Band 3 observations of the N2H+ (1–0) transition, which traces the large-scale gas kinematics. Using a friend-of-friend algorithm, we identify four main velocity coherent structures, all of which are associated with prestellar and protostellar cores. One of them presents a filament-like structure, and our observations could be consistent with mass accretion toward one of the protostars. In this case, we estimate a mass accretion rate of Ṁacc≈2×10−4M⊙yr−1 . Our results support a clump-fed accretion scenario in the target source. The cores in the prestellar stage are essentially low-mass, and they appear to be subvirial and gravitationally bound, unless further support is available, for instance, due to magnetic fields.
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift

Machine learning systems may encounter unexpected problems when the data distribution changes in the deployment environment. A major reason is that certain combinations of domains and labels are not observed during training but appear in the test environment. Although various invariance-based algorithms can be applied, we ﬁnd that the performance gain is often marginal. To formally analyze this issue, we provide a unique algebraic formulation of the combination shift problem based on the concepts of homomorphism, equivariance, and a reﬁned deﬁnition of disentanglement. The algebraic requirements naturally derive a simple yet effective method, referred to as equivariant disentangled transformation (EDT), which augments the data based on the algebraic structures of labels and makes the transformation satisfy the equivariance and disentanglement requirements. Experimental results demonstrate that invariance may be insufﬁcient, and it is important to exploit the equivariance structure in the combination shift problem.
Empirical Study of Overfitting in Deep FNN Prediction Models for Breast Cancer Metastasis

—Overfitting is defined as the fact that the current model fits a specific data set perfectly, resulting in weakened generalization, and ultimately may affect the accuracy in predicting future data. In this research we used an EHR dataset concerning breast cancer metastasis to study overfitting of deep feedforward Neural Networks (FNNs) prediction models. We included 11 hyperparameters of the deep FNNs models and took an empirical approach to study how each of these hyperparameters was affecting both the prediction performance and overfitting when given a large range of values. We also studied how some of the interesting pairs of hyperparameters were interacting to influence the model performance and overfitting. The 11 hyperparameters we studied include activate function; weight initializer, number of hidden layers, learning rate, momentum, decay, dropout rate, batch size, epochs, L1, and L2. Our results show that most of the single hyperparameters are either negatively or positively corrected with model prediction performance and overfitting. In particular, we found that overfitting overall tends to negatively correlate with learning rate, decay, batch sides, and L2, but tends to positively correlate with momentum, epochs, and L1. According to our results, learning rate, decay, and batch size may have a more significant impact on both overfitting and prediction performance than most of the other hyperparameters, including L1, L2, and dropout rate, which were designed for minimizing overfitting. We also find some interesting interacting pairs of hyperparameters such as learning rate and momentum, learning rate and decay, and batch size and epochs.
The Casimir-Polder effect for an approximate Pauli-Fierz model: the atom plus wall case

We study a system composed of a hydrogen atom interacting with an infinite conductor wall. The interaction energy decays like $L^{-3}$, where $L$ is the distance between the atom and the wall, due to the emergence of the van der Waals forces. In this paper we show how, considering the contributions from the quantum fluctuations of the electromagnetic field, the interaction is weakened to a decay of order $L^{-4}$ giving rise to the retardation effects which fall under the name of Casimir-Polder effect. The analysis is done by studying a suitable Pauli-Fierz model associated to the system, in dipole approximation and reduced to the interaction with 0 and 1 photon.
Calibrating the Solar Dynamo: Magnetic Activity Cycles of Southern Sun-like Stars

The solar magnetic activity cycle is responsible for periodic episodes of severe space weather, which can perturb satellite orbits, interfere with communications systems, and bring down power grids. Much progress has recently been made in forecasting the strength and timing of this 11-year cycle, using a predictive flux-transport dynamo model (Dikpati 2005, Dikpati et al. 2006). We can strengthen the foundation of this model by extending it to match observations of similar magnetic activity cycles in other Sun-like stars, which exhibit variations in their Ca II H and K emission on time scales from 2.5 to 25 years (Baliunas et al. 1995). This broad range of cycle periods is thought to reflect differences in the rotational properties and the depth of the surface convection zone for stars with various masses and ages. Asteroseismology is now yielding direct measurements of these quantities for individual stars, but the most promising asteroseismic targets are in the southern sky (alpha Cen A, alpha Cen B, beta Hyi), while the existing activity cycle survey is confined to the north. We are initiating a long-term survey of Ca II H and K emission for a sample of 92 southern Sun-like stars to measure their magnetic activity cycles and rotational properties, which will ultimately provide independent tests of solar dynamo models.
Asymptotic Tracking Control of Uncertain MIMO Nonlinear Systems with Less Conservative Controllability Conditions

For uncertain multiple inputs multi-outputs (MIMO) nonlinear systems, it is nontrivial to achieve asymptotic tracking, and most existing methods normally demand certain controllability conditions that are rather restrictive or even impractical if unexpected actuator faults are involved. In this note, we present a method capable of achieving zero-error steady-state tracking with less conservative (more practical) controllability condition. By incorporating a novel Nussbaum gain technique and some positive integrable function into the control design, we develop a robust adaptive asymptotic tracking control scheme for the system with time-varying control gain being unknown its magnitude and direction. By resorting to the existence of some feasible auxiliary matrix, the current state-of-art controllability condition is further relaxed, which enlarges the class of systems that can be considered in the proposed control scheme. All the closed-loop signals are ensured to be globally ultimately uniformly bounded. Moreover, such control methodology is further extended to the case involving intermittent actuator faults, with application to robotic systems. Finally, simulation studies are carried out to demonstrate the effectiveness and flexibility of this method.
Conditional Contact Angle Distribution in LEO Satellite-Relayed Transmission

This letter characterizes the contact angle distribution based on the condition that the relay low earth orbit (LEO) satellite is in the communication range of both the ground transmitter and the ground receiver. As one of the core distributions in stochastic geometry-based routing analysis, the analytical expression of the Cumulative Distribution Function (CDF) of the conditional contact angle is derived. Furthermore, the conditional contact angle is applied to analyze the inaccessibility of common satellites between the ground transmitter and receiver. Finally, with the help of the conditional contact angle, coverage probability and achievable data rate in LEO satellite-relayed transmission are studied.
Null subjects, expletives and locatives in Sardinian

If we look at subtypes of expletive subjects, as identified by Svenonius (2002:5) for English, for example, we see that they can be pronouns, as is the case for extrapositional it or weather it, or they can consist of a locative element, like impersonal there. It is the latter in particular that will be at the centre of interest in this paper. The specific aim of this paper is to describe, interpret and analyse two subtypes of “subjectless” constructions in Sardinian that involve such a locative element, namely existential constructions and presentational impersonal constructions with intransitives. The paper will focus on the status and role of the locative element with respect to null subjects and/or expletives. More details concerning the relation between empty and overt expletives and overt locatives even in a null subject language such as Sardinian will be discussed in section 2. Sardinian displays wide diatopic variation; nevertheless it is often stated that there are roughly two main dialect areas, although these are not clearly defined and have several transitional areas. One is Logudorese in the North of the island; the other is Campidanese in the South. Thus there is a variation of forms with respect to locatives or existentials in Sardinian. Here, only the clitic locatives will be considered, which can be bi, bie / ikke, ke, nke, ank, inchi, for the Logudorese varieties, and iddhoi, ddhoi, ddhui, ddhue, ddhu / inci, ci, ince, nce for the Campidanese varieties. All varieties, however, have null subjects. In what follows I shall principally use examples with bi, most of them stemming from the mailing list Sa Limba (cf. Sa-Limba 1999-2007). The occurrences of a locative or existential element are glossed with LOC. This, however, does not mean that bi always is to be interpreted as a true locative. All examples at issue here are thetic sentences (cf. Sasse 1987) or so-called presentational clauses, i.e. constructions that do not have predicate focus, but sentence focus (Lambrecht 1994). The data under discussion are given in the following examples:
Maintaining Performance with Less Data

We propose a novel method for training a neural network for image classification to reduce input data dynamically, in order to reduce the costs of training a neural network model. As Deep Learning tasks become more popular, their computational complexity increases, leading to more intricate algorithms and models which have longer runtimes and require more input data. The result is a greater cost on time, hardware, and environmental resources. By using data reduction techniques, we reduce the amount of work performed, and therefore the environmental impact of AI techniques, and with dynamic data reduction we show that accuracy may be maintained while reducing runtime by up to 50%, and reducing carbon emission proportionally.