Miracle-dz/UniFAR-FTUs huggingface dataset:
Autism as emergent and transactional

The current epistemology of autism as a phenotype derives from the consistency of historical accounts and decades of work within the tradition of descriptive epidemiology, culminating in current categorical descriptions within DSM and ICD nosologies and the concept of “prototypical autism. ” The demonstrated high heritability of this phenotype has led to an essentialist theory of autism as a biological entity and the concerted search within the developmental brain and genetic science for discrete biological markers. This search has not revealed simple markers explaining autistic outcomes and has led to moves towards a more dimensional account. This article proposes an alternative transactional approach. It proposes to understand autistic states as an emergent property within a complex developmental system; as the neurodivergent brain, and mind and body, encounter their social and physical environment within early development. Key evidence in support of this approach comes from random allocation intervention trials based on such transactional development theory, both in the infancy pre-diagnostic prodrome and the early post-diagnostic period. In replicated evidence, these intervention trials show that a targeted alteration in the quality of social transactional environment available for the child leads to significant, predictable, and sustained alterations in the outcome dimensional autistic phenotype over time; and further, in one prodromal trial, to a significant reduction in later categorical classification status. The inference from this evidence is that the prototypical autistic phenotype is to a degree malleable with a changed experienced social environment and that it is emergent from its constituent traits. Such a transactional approach enlarges our notion of the phenotype and brings the study of autism within mainstream individual difference developmental science. It challenges essentialist views, for instance as to intrinsic autistic “social avoidance” or theory of mind empathy deficits, integrates dimensional and categorical perspectives, and is consistent with the lived experience of autistic people and their advocacy for improved understanding within a social model.
Inert Doublet Model and LEP II Limits

The inert doublet model is a minimal extension of the standard model introducing an additional SU(2) doublet with new scalar particles that could be produced at accelerators. While there exists no LEP II analysis dedicated for these inert scalars, the absence of a signal within searches for supersymmetric neutralinos can be used to constrain the inert doublet model. This translation however requires some care because of the different properties of the inert scalars and the neutralinos. We investigate what restrictions an existing DELPHI Collaboration study of neutralino pair production can put on the inert scalars and discuss the result in connection with dark matter. We find that although an important part of the inert doublet model parameter space can be excluded by the LEP II data, the lightest inert particle still constitutes a valid dark matter candidate.
Resistance to innovation in low-income populations: The case of university students' resistance to using digital productivity applications

Innovation resistance research remains in its early stages. Efforts to define and comprehend consumer resistance to innovation necessitate in-depth studies that consider the contextual factors of resistance to innovation. To address this challenge, this research explored consumer resistance to innovation in a low-income population, namely, university students on financial support. The innovation under this study is the productivity applications provided for free by the University of Hail, Saudi Arabia, to all students. This study explores variables such as value barrier, risk barrier, tradition barrier, and image barrier and how they impact consumer resistance to innovation in a low-income population. We extend the theory by investigating the moderating roles of consumer characteristics (motivation, self-efficacy, emotion, and attitude toward existing products). The current study is based on an online survey of low-income students at a Saudi Arabian University; 258 cases were gathered. We found that all the direct effects of the variables (i.e., Value Barrier, Risk Barrier, Tradition Barrier, and Image Barrier) were positively related to consumer resistance to innovation. Importantly, consumer characteristics significantly moderate this relationship, as the relationship is stronger when the measurements for consumer characteristics are high.
How (not) to teach Lorentz covariance of the Dirac equation

In the textbook proofs of the Lorentz covariance of the Dirac equation, one treats the wave function as a spinor and gamma matrices as scalars, leading to a quite complicated formalism with several pedagogic drawbacks. As an alternative, I propose to teach the Dirac equation and its Lorentz covariance by using a much simpler, but physically equivalent formalism, in which these drawbacks do not appear. In this alternative formalism, the wave function transforms as a scalar and gamma matrices as components of a vector, such that the standard physically relevant bilinear combinations do not change their transformation properties. The alternative formalism allows also a natural construction of some additional non-standard bilinear combinations with well-defined transformation properties.
LIMITS ON PROMPT, DISPERSED RADIO PULSES FROM GAMMA-RAY BURSTS

We have searched for prompt radio emission from nine gamma-ray bursts (GRBs) with a 12 m telescope at 1.4 GHz, with a time resolution of 64 μs to 1 s. We detected single dispersed radio pulses with significances >6σ in the few minutes following two GRBs. The dispersion measures of both pulses are well in excess of the expected Galactic values, and the implied rate is incompatible with known sources of single dispersed pulses. The arrival times of both pulses also coincide with breaks in the GRB X-ray light curves. A null trial and statistical arguments rule out random fluctuations as the origin of these pulses with >95% and ∼97% confidence, respectively, although a simple population argument supports a GRB origin with confidence of only 2%. We caution that we cannot rule out radio frequency interference (RFI) as the origin of these pulses. If the single pulses are not related to the GRBs, we set an upper limit on the flux density of radio pulses emitted between 200 and 1800 s after a GRB of 1.27w−1/2 Jy, where 6.4 × 10−5 s < w < 32 × 10−3 s is the pulse width. We set a limit of less than 760 Jy for long timescale (>1 s) variations. These limits are some of the most constraining at high time resolution and GHz frequencies in the early stages of the GRB phenomenon.
Tunnel Magnetoresistance and Spin-Transfer-Torque Switching in Polycrystalline Co 2 FeAl Full-Heusler-Alloy Magnetic Tunnel Junctions on Amorphous Si /SiO 2 Substrates

We studied polycrystalline B2-type Co2FeAl (CFA) full-Heusler alloy based magnetic tunnel junctions (MTJs) fabricated on a Si/SiO2 amorphous substrate. Polycrystalline CFA films with a (001) orientation, a high B2 ordering, and a flat surface were achieved using a MgO buffer layer. A tunnel magnetoresistance (TMR) ratio up to 175% was obtained for an MTJ with a CFA/MgO/CoFe structure on a 7.5-nm-thick MgO buffer. Spin-transfer torque induced magnetization switching was achieved in the MTJs with a 2-nm-thick polycrystalline CFA film as a switching layer. Using a thermal activation model, the intrinsic critical current density (Jc0) was determined to be 8.2 x 10^6 A/cm^2, which is lower than 2.9 x 10^7 A/cm^2, the value for epitaxial CFA-MTJs [Appl. Phys. Lett. 100, 182403 (2012)]. We found that the Gilbert damping constant evaluated using ferromagnetic resonance measurements for the polycrystalline CFA film was ~0.015 and was almost independent of the CFA thickness (2~18 nm). The low Jc0 for the polycrystalline MTJ was mainly attributed to the low damping of the CFA layer compared with the value in the epitaxial one (~0.04).
THE METALLICITY DEPENDENCE OF THE CO → H2 CONVERSION FACTOR IN z ⩾ 1 STAR-FORMING GALAXIES

We use the first systematic samples of CO millimeter emission in z ⩾ 1 ‘‘main-sequence'' star-forming galaxies to study the metallicity dependence of the conversion factor αCO, from CO line luminosity to molecular gas mass. The molecular gas depletion rate inferred from the ratio of the star formation rate (SFR) to CO luminosity, is ∼1 Gyr−1 for near-solar metallicity galaxies with stellar masses above MS ∼ 1011 M☉. In this regime, the depletion rate does not vary more than a factor of two to three as a function of molecular gas surface density or redshift between z ∼ 0 and 2. Below MS the depletion rate increases rapidly with decreasing metallicity. We argue that this trend is not caused by starburst events, by changes in the physical parameters of the molecular clouds, or by the impact of the fundamental-metallicity–SFR–stellar mass relation. A more probable explanation is that the conversion factor is metallicity dependent and that star formation can occur in ‘‘CO-dark'' gas. The trend is also expected theoretically from the effect of enhanced photodissociation of CO by ultraviolet radiation at low metallicity. From the available z ∼ 0 and z ∼ 1–3 samples we constrain the slope of the log(αCO)–log (metallicity) relation to range between −1 and −2, fairly insensitive to the assumed slope of the gas–SFR relation. Because of the lower metallicities near the peak of the galaxy formation activity at z ∼ 1–2 compared to z ∼ 0, we suggest that molecular gas masses estimated from CO luminosities have to be substantially corrected upward for galaxies below MS.
Radio and spectroscopic properties of miniature radio galaxies: revealing the bulk of the radio-loud AGN population

We explore radio and spectroscopic properties of a sample of 14 miniature radio galaxies, i.e. early-type core galaxies hosting radioloud AGN of extremely low radio power, 10 27−29 erg s −1 Hz −1 at 1.4 GHz. Miniature radio galaxies smoothly extend the relationships found for the more powerful FR I radio galaxies between emission line, optical and radio nuclear luminosities to lower levels. However, they have a deficit of a factor of ∼100 in extended radio emission with respect to that of the classical example of 3CR/FR I. This is not due to their low luminosity, since we found radio galaxies of higher radio core power, similar to those of 3CR/FR I, showing the same behavior, i.e. lacking significant extended radio emission. Such sources form the bulk of the population of radio-loud AGN in the Sloan Digital Sky Survey. At a given level of nuclear emission, one can find radio sources with an extremely wide range, a factor of >100, of radio power. We argue that the prevalence of sources with luminous extended radio structures in flux limited samples is due to a selection bias, since the inclusion of such objects is highly favored. The most studied catalogues of radio galaxies are thus composed by the minority of radio-loud AGN that meet the physical conditions required to form extended radio sources, while the bulk of the population is virtually unexplored.
CENTRAL ENGINE OF LATE-TIME X-RAY FLARES WITH INTERNAL ORIGIN

This work focuses on a sample of seven extremely late-time X-ray flares with peak time , among which two flares can be confirmed as the late-time activity of central engine. The main purpose is to investigate the mechanism of such late-time flares based on the internal origin assumption. In the hyper-accreting black hole (BH) scenario, we study the possibility of two well-known mechanisms acting as the central engine to power such X-ray flares, i.e., the neutrino–antineutrino annihilation and the Blandford–Znajek (BZ) process. Our results show that the annihilation luminosity is far below the observational data. Thus, the annihilation mechanism cannot account for such late-time flares. For the BZ process, if the role of outflows is taken into consideration, the inflow mass rate near the horizon will be quite low such that the magnetic field will probably be too weak to power the observed X-ray flares. We therefore argue that, for the late-time flares with internal origin, the central engine is unlikely to be associated with BHs. On the contrary, a fast rotating neutron star with strong bipolar magnetic fields may be responsible for such flares.
A FOURIER-TRANSFORMED BREMSSTRAHLUNG FLASH MODEL FOR THE PRODUCTION OF X-RAY TIME LAGS IN ACCRETING BLACK HOLE SOURCES

Accreting black hole sources show a wide variety of rapid time variability, including the manifestation of time lags during X-ray transients, in which a delay (phase shift) is observed between the Fourier components of the hard and soft spectra. Despite a large body of observational evidence for time lags, no fundamental physical explanation for the origin of this phenomenon has been presented. We develop a new theoretical model for the production of X-ray time lags based on an exact analytical solution for the Fourier transform describing the diffusion and Comptonization of seed photons propagating through a spherical corona. The resulting Green's function can be convolved with any source distribution to compute the associated Fourier transform and time lags, hence allowing us to explore a wide variety of injection scenarios. We show that thermal Comptonization is able to self-consistently explain both the X-ray time lags and the steady-state (quiescent) X-ray spectrum observed in the low–hard state of Cyg X-1. The reprocessing of bremsstrahlung seed photons produces X-ray time lags that diminish with increasing Fourier frequency, in agreement with the observations for a wide range of sources.
Quantum noise and entanglement generated by a local quantum quench

We examine the growth of entanglement under a quantum quench at point contacts of simple fractional quantum Hall fluids and its relation with the measurement of local observables. Recently Klich and Levitov proposed that the noise generated from a local quantum quench provides a measure of the entanglement entropy. Their methods were specific to noninteracting electrons and the generalization to interacting systems was left as an open question. In this work, we generalize their result to the Laughlin states. We investigate the noise generated in the current along the edge of a fractional quantum Hall state at filling factors $\ensuremath{\nu}=1/m$, when a quantum point contact, initially closed, is fully opened at some initial time ${t}_{0}=0$. We find that local quenching in these systems gives time dependent correlation functions that have universal behavior on sufficiently long time and length scales. We calculate the noise and full counting statistics for $\ensuremath{\nu}=1/m$ and find that in general, the entanglement entropy and noise generated are unrelated quantities. We also discuss a generalization of this problem to the critical quantum Ising spin chain.
Topological Data Analysis Helps to Improve Accuracy of Deep Learning Models for Fake News Detection Trained on Very Small Training Sets

: Topological data analysis has recently found applications in various areas of science, such as computer vision and understanding of protein folding. However, applications of topological data analysis to natural language processing remain under-researched. This study applies topological data analysis to a particular natural language processing task: fake news detection. We have found that deep learning models are more accurate in this task than topological data analysis. However, assembling a deep learning model with topological data analysis signiﬁcantly improves the model’s accuracy if the available training set is very small.
Optimization for Robustness Evaluation Beyond ℓp Metrics

Empirical evaluation of the adversarial robustness of deep learning models involves solving non-trivial constrained optimization problems. Popular numerical algorithms to solve these constrained problems rely predominantly on projected gradient descent (PGD) and mostly handle adversarial perturbations modeled by the ℓ1, ℓ2, and ℓ∞ metrics. In this paper, we introduce a novel algorithmic framework that blends a general-purpose constrained-optimization solver PyGRANSO, With Constraint-Folding (PWCF), to add reliability and generality to robustness evaluation. PWCF 1) finds good-quality solutions without the need of delicate hyperparameter tuning and 2) can handle more general perturbation types, e.g., modeled by general ℓp (where p > 0) and perceptual (nonℓp) distances, which are inaccessible to existing PGD-based algorithms.
Adversarial consistent training guided omnidirectional scanpath prediction

Emerging concepts like the Metaverse introduced a revolution in research related 1 to virtual reality. Most actors in technology are paying more attention to the study 2 of visual attention which has seen quite the development since the explosive advent 3 of deep learning in the last decade. In this paper, we introduce a simple neural 4 architecture and use a conditional adversarial consistent training approach to guide 5 our neural network. The approach anchors one ground truth scanpath and varies 6 another to improve the consistency of the discriminative network, and thus the 7 predicted scanpath by extension. we also introduce partial connections for the 8 multi-layer perceptron to implement an ordinality inductive bias for the sequences. 9 Our method achieved great quantitative and qualitative results when compared to 10 other state-of-the-art methods. 11
Estimating the Impact of Coordinated Inauthentic Behavior on Content Recommendations in Social Networks

Online disinformation is a dynamic and pervasive problem on social networks as evidenced by a spate of public disasters in light of active efforts to combat it. Since the massive amounts of content generated each day on these platforms is impossible to manually curate, ranking and recommendation algorithms are a key apparatus that drive user interactions. However, the vulnerability of ranking and recommendation algorithms to attack from coordinated campaigns spreading misleading information has been established both theoretically and anecdotally. Unfortunately it is unclear how effective countermeasures to disinfor-mation are in practice due to the limited view we have into the operation of such platforms. In such settings, simulations have emerged as a popular technique to study the long-term effects of content ranking and recommendation systems. We develop a multiagent simulation of a popular social network, Reddit, that aligns with the state-action space available to real users based on the platform’s affordances. We collect millions of real-world interactions from Reddit to estimate the network for each user in our dataset and utilise Reddit’s self-described content ranking strategies to compare the impact of coordinated activity on content spread by each strategy. We expect that this will inform the design of robust content distribution systems that are resilient against targeted attacks by groups of malicious actors.
TOWARD A SPECTROSCOPIC CENSUS OF WHITE DWARFS WITHIN 40 pc OF THE SUN

We present the preliminary results of a survey aimed at significantly increasing the range and completeness of the local census of spectroscopically confirmed white dwarfs. The current census of nearby white dwarfs is reasonably complete only to about 20 pc of the Sun, a volume that includes around 130 white dwarfs, a sample too small for detailed statistical analyses. This census is largely based on follow-up investigations of stars with very large proper motions. We describe here the basis of a method that will lead to a catalog of white dwarfs within 40 pc of the Sun and north of the celestial equator, thus increasing by a factor of eight the extent of the northern sky census. White dwarf candidates are identified from the SUPERBLINK proper motion database, allowing us to investigate stars down to a proper motion limit μ > 40 mas yr−1, while minimizing the kinematic bias for nearby objects. The selection criteria and distance estimates are based on a combination of color–magnitude and reduced proper motion diagrams. Our follow-up spectroscopic observation campaign has so far uncovered 193 new white dwarfs, among which we identify 127 DA (including 9 DA+dM and 4 magnetic), 1 DB, 56 DC, 3 DQ, and 6 DZ stars. We perform a spectroscopic analysis on a subsample of 84 DAs, and provide their atmospheric parameters. In particular, we identify 11 new white dwarfs with spectroscopic distances within 25 pc of the Sun, including five candidates to the D < 20 pc subset.
Pharmacokinetics and Pharmacodynamics of TAK-164 Antibody Drug Conjugate Coadministered with Unconjugated Antibody

The development of new antibody–drug conjugates (ADCs) has led to the approval of 7 ADCs by the FDA in 4 years. Given the impact of intratumoral distribution on efficacy of these therapeutics, coadministration of unconjugated antibody with ADC has been shown to improve distribution and efficacy of several ADCs in high and moderately expressed tumor target systems by increasing tissue penetration. However, the benefit of coadministration in low expression systems is less clear. TAK-164, an ADC composed of an anti-GCC antibody (5F9) conjugated to a DGN549 payload, has demonstrated heterogeneous distribution and bystander killing. Here, we evaluated the impact of 5F9 coadministration on distribution and efficacy of TAK-164 in a primary human tumor xenograft mouse model. Coadministration was found to improve the distribution of TAK-164 within the tumor, but it had no significant impact (increase or decrease) on efficacy. Experimental and computational evidence indicates that this was not a result of tumor saturation, increased binding to perivascular cells, or compensatory bystander effects. Rather, the cellular potency of DGN549 was matched with the single-cell uptake of TAK-164 making its IC50 close to its equilibrium binding affinity (KD), and as such, coadministration dilutes total DGN549 in cells below the maximum cytotoxic concentration, thereby offsetting an increased number of targeted cells with decreased ability to kill each cell. These results provide new insights on matching payload potency to ADC delivery to help identify when increasing tumor penetration is beneficial for improving ADC efficacy and demonstrate how mechanistic simulations can be leveraged to design clinically effective ADCs.
Melodic perception skills predict Catalan speakers’ speech imitation abilities of unfamiliar languages

Musical perception skills have been shown to influence second language speech production. Likewise, working memory may also affect nonnative speech production abilities. However, very few studies have assessed their respective role in speech imitation abilities. The present study thus investigates the predictive role of musical perception skills and working memory on speech imitation abilities of unfamiliar languages. Sixty-one adult Catalan speakers imitated twelve sentences in six languages that were unfamiliar to them. Participants’ music perception skills were tested by four PROMS-S subsets, namely accent, melody, pitch, and rhythm, and their working memory was measured by a forward digit span test. A linear regression analysis revealed that melodic perception skills were the unique predictor among all four musical perception subtests and that working memory was not a significant predictor. Our findings show that melodic perception skills are key in predicting the capability in imitating unfamiliar speech, and thus may be important for learning foreign language pronunciation.