Miracle-dz/UniFAR-FTUs huggingface dataset:
Objective assessment of visual attention in toddlerhood

Visual attention is an important mechanism through which children learn about their environment, and individual differences could substantially shape later development. Eyetracking provides a sensitive and scalable tool for assessing visual attention that has potential for objective assessment of child development, but to date the majority of studies are small and replication attempts are rare. This study investigates the feasibility of a comprehensive eye-tracking assessment of visual attention and introduces a shared data resource for the scientific community. Data from eight eyetracking tasks were collected from 350 term-born (166 females) 18-month-olds recruited as neonates http://www.developingconnectome. org/). Analyses showed expected condition effects for seven of eight tasks (p-values from <.001 to .04), an important indication of replicability. Consistent with some theoretical models of visual attention, structural equation modelling indicated participants’ performance could be explained by two factors representing social and non-social attention. Comprehensive eye-tracking batteries can objectively measure individual differences in core components of visual attention in large-scale toddlerhood studies. This is the first large-scale comprehensive study to present high-quality normative eye-tracking data from a large task battery in toddlers and make them freely available to the scientific community.
ApTOLL, a new therapeutic aptamer for cytoprotection and (re)myelination after Multiple Sclerosis

ApTOLL is an aptamer specifically designed to antagonize Toll-Like Receptor 4 (TLR4), a relevant actor for innate immunity involved in inflammatory responses in multiple sclerosis (MS) and other diseases. MS is a primary demyelinating, chronic, inmune and neurodegenerative disease of the central nervous system that normally debuts in young adults. The currently available therapeutic arsenal to treat MS is composed of immunomodulators but, to date, there are no (re)myelinating drugs available in clinics. Our present study shows cells expressing TLR4 in demyelinating lesions of MS patients (postmortem samples from cerebral cortex) and, as a derivative, we studied the effect of TLR4 inhibition with ApTOLL in animal models of MS (experimental autoimmune encephalomyelitis -EAE- and the cuprizone). The treatment with ApTOLL positively impacted the clinical symptomatology, and this was associated with better preservation plus restoration of myelin and oligodendrocytes in the demyelinated lesions of these animals, which suggests not only an immunomodulatory but also a remyelinating effect of the treatment with ApTOLL. This latter was corroborated on purified cultures of rodent and adult human oligodendrocyte precursor cells (OPCs), confirming the expression of TLR4 in this cell type. Altogether, the molecular nature of ApTOLL and its mechanism/s of action strongly supports this compound as a novel candidate to treat MS and other demyelinating scenarios.
Asymptotic calculation of Laplace Inverse in analytical solutions of groundwater problems

The Laplace transform with respect to time, t, is normally used in finding analytical solutions for transient groundwater problems. The behavior of a function at large or small t is known to correspond to that of its Laplace transform counterpart at small or large p, respectively; p is the Laplace transform parameter of t. This condition is generally translated as t being inversely related to p and vice versa. By this relationship many asymptotic solutions for large or small t have been determined from the Laplace domain solutions valid only for small or large p. However, an example is given here which shows this kind of asymptotic calculation may fail to yield correct asymptotic solutions. Hence, the asymptotic calculation must be exercised with care. To deal with this possible failure, the Tauberian theorem is offered to evaluate the asymptotic behavior of functions from their Laplace transform counterparts.
Mechanics of kinking in fiber-reinforced composites under compressive loading

A novel approach to analyze kink banding failure in fiber reinforced composites is presented in this paper. By considering a single fiber–matrix unit cell and utilizing a fiber deformation representation that can simultaneously account for instability due to increasing fiber amplitude and fiber rotation, a sequence of events that lead to the formation of a kink band is elucidated. It is shown that peak compressive strength does not necessarily correspond to the onset of yielding (non-linearity) in the matrix and is dictated by the interaction between matrix non-linearity and initial fiber misalignment. Predictions of compressive strength and kink band formation, utilizing the new model, are found to be in good agreement with reported experimental data and associated higher-order finite element analysis.
Asymptotic behavior of Betti numbers of random geometric complexes

We establish the strong law of large numbers for Betti numbers of random \v{C}ech complexes built on $\mathbb R^N$-valued binomial point processes and related Poisson point processes in the thermodynamic regime. Here we consider both the case where the underlying distribution of the point processes is absolutely continuous with respect to the Lebesgue measure on $\mathbb R^N$ and the case where it is supported on a $C^1$ compact manifold of dimension strictly less than $N$. The strong law is proved under very mild assumption which only requires that the common probability density function belongs to $L^p$ spaces, for all $1\leq p < \infty$.
On the existence of C∞ solutions to the asymptotic characteristic initial value problem in general relativity

The asymptotic characteristic initial value problem for Einstein’s vacuum field equations is treated. It is shown that C∞ solutions exist and are unique for C∞ initial values. The proof is based on Friedrich’s regular conformal vacuum field equations and Rendall’s method of reducing the characteristic to an ordinary initial value problem.
Perturbation dynamics in unsteady pipe flows

This paper deals with perturbed unsteady laminar flows in a pipe. Three types of flows are considered: a flow accelerated from rest; a flow in a pipe generated by the controlled motion of a piston; and a water hammer flow where the transient is generated by the instantaneous closure of a valve. Methods of linear stability theory are used to analyse the behaviour of small perturbations in the flow. Since the base flow is unsteady, the linearized problem is formulated as an initial-value problem. This allows us to consider arbitrary initial conditions and describe both short-time and long-time evolution of the flow. The role of initial conditions on short-time transients is investigated. It is shown that the phenomenon of transient growth is not associated with a certain type of initial conditions. Perturbation dynamics is also studied for long times. In addition, optimal perturbations, i.e. initial perturbations that maximize the energy growth, are determined for all three types of flow discussed. Despite the fact that these optimal perturbations, most probably, will not occur in practice, they do provide an upper bound for energy growth and can be used as a point of reference. Results of numerical simulation are compared with previous experimental data. The comparison with data for accelerated flows shows that the instability cannot be explained by long-time asymptotics. In particular, the method of normal modes applied with the quasi-steady assumption will fail to predict the flow instability. In contrast, the transient growth mechanism may be used to explain transition since experimental transition time is found to be in the interval where the energy of perturbation experiences substantial growth. Instability of rapidly decelerated flows is found to be associated with asymptotic growth mechanism. Energy growth of perturbations is used in an attempt to explain previous experimental results. Numerical results show satisfactory agreement with the experimental features such as the wavelength of the most unstable mode and the structure of the most unstable disturbance. The validity of the quasi-steady assumption for stability studies of unsteady non-periodic laminar flows is discussed.
Reduction of Ranking to Classification

This paper describes an ecient reduction of the learning problem of ranking to binary classification. The reduction guarantees an average pairwise misranking regret of at most that of the binary classifier regret, improving a recent result of Balcan et al which only guarantees a factor of 2. Moreover, our reduction applies to a broader class of ranking loss functions, admits a simpler proof, and the expected running time complexity of our algorithm in terms of number of calls to a classifier or preference function is improved from (n 2 ) to O(nlogn). In addition, when the top k ranked elements only are required (k n), as in many applications in information extraction or search engines, the time complexity of our algorithm can be further reduced to O(k logk+n). Our reduction and algorithm are thus practical for realistic applications where the number of points to rank exceeds several thousands. Much of our results also extend beyond the bipartite case previously studied. Our rediction is a randomized one. To complement our result, we also derive lower bounds on any deterministic reduction from binary (pref- erence) classification to ranking, implying that our use of a randomized reduction is essentially necessary for the guarantees we provide.
Large‐eddy simulation of compressible flows using a spectral multidomain method

This paper discusses the development of a high‐order, multidomain‐based large‐eddy simulation (LES) methodology for compressible flows. The LES model equations are approximated on unstructured grids of non‐overlapping hexahedral sub‐domains providing geometric flexibility. In each domain a high‐order Chebyshev polynomial approximation represents the solution ensuring a highly accurate approximation with little numerical dispersion and diffusion. The sub‐grid scale stress in the filtered LES equations is modeled with a dynamic eddy‐viscosity model, while the heat flux is represented with an eddy diffusivity model, employing a turbulent Prandtl number. The model constants are evaluated through a flexible dynamic procedure that uses a high‐order domain level filtering for the discrete test filter. The LES methodology is tested in a decaying isotropic turbulence and a channel flow. The LES method improves the resolution of the turbulence spectrum as compared with a direct numerical simulation (DNS) with the same method at the same grid resolution. The averaged and second‐order statistics for LES computations are in close agreement with published results and resolved DNS. The high‐order LES methodology requires fewer degrees of freedom as compared with lower‐order LES methodologies to accurately resolve the turbulent flows. Copyright © 2008 John Wiley & Sons, Ltd.
Asteroid 243 Ida: Groundbased Photometry and a Pre-Galileo Physical Model

Abstract Groundbased photometric observations of asteroid 243 Ida over seven apparitions from 1980 to 1993 allow us to derive a model for its spin vector and shape prior to the August 1993 encounter by the Galileo spacecraft. Two equally likely solutions for the spin vector are at ecliptic coordinates (1950) λp1 = 73, βp1 = -53 or λp2 = 254, βp2 = -55 with an uncertainty of ± 10° in each coordinate. Ida's low orbital inclination restricts the available aspect angles for Earth-based observers so that the spin vector ambiguity cannot be resolved. We offer predictions for the flyby geometry for both solutions, where the Galileo spacecraft images will resolve this ambiguity easily. Ida's rotation is retrograde with a sidereal period of 4.633632 ± 0.000007 hr. Assuming a triaxial ellipsoid model, we estimate axial ratios of a/b = 1.82 ± 0.10 and b/c = 1.15 ± 0.10. The morphology of the observed lightcurves suggest that Ida has a nonuniform albedo distribution, but we cannot completely rule out observational uncertainties or simplifying model assumptions (e.g., convex shape, geometric scattering) as sources for this suggestion. It is not possible to predict uniquely the distribution of any such albedo variegation.
Bubble dynamics in time-periodic straining flows

The dynamics and breakup of a bubble in an axisymmetric, time-periodic straining flow has been investigated via analysis of an approximate dynamic model and also by time-dependent numerical solutions of the full fluid mechanics problem. The analyses reveal that in the neighbourhood of a stable steady solution, an $O(\epsilon^{\frac{1}{3}})$ time-dependent change of bubble shape can be obtained from an O(ε) resonant forcing. Furthermore, the probability of bubble breakup at subcritical Weber numbers can be maximized by choosing an optimal forcing frequency for a fixed forcing amplitude.
Pre-rut behavioural changes in farmed red deer with reference to atmospheric conditions

Red deer (Cervus elaphus) exhibit specific behaviour during the rutting season, which may have an impact on the safety on cervid farms, both due to aggressive interactions between animals and the safety of people staying there, such as staff and tourists. This issue applies especially to stags whose behaviour changes radically, and the correct interpretation of the observed changes is very important. Therefore, the aim of the study was to analyse the pre-rut behaviour of stags and to show the influence of atmospheric conditions on vocalization and other elements of their behaviour, which facilitate determination of the onset of the rutting season. The observations were conducted in August and September of 2017 and 2018. It was shown that lower temperatures, declines in air humidity, increasing atmospheric pressure, and transition of the moon phase towards the full moon resulted in intensification of the vocalization activity in the red deer in the pre-rutting season, which may accelerate the rutting period in the deer males. The number of vocalizations varied between the years and depended on the mean temperature, air humidity, atmospheric pressure, and moon phase in the prerutting and rutting seasons. Through observation of the changing weather conditions, it is possible to predict the time of increased activity of stags and the onset of the rutting period. Predicting the date of mating season in farm breeding, based on daily observations of changes in the behaviour of stags, can be helpful in planning veterinary treatments or selecting the composition of the hinds to be covered by specific stags, which can also contribute to the improvement of their welfare.
Sternal Displacement During Activities

Purpose: The purpose of this study was to determine whether sternal displacement occurs, decreases over time, and varies with adherence to sternal precautions during functional activities after median sternotomy. Methods: Seventeen subjects had ultrasound images taken at two and then six to eight weeks after median sternotomy to measure the sternal gap and displacement during five activities commonly limited by sternal precautions. The subjects were divided into two groups based on self-reported compliance with sternal precautions. Results: At the upper sternal site, displacement occurred with all activities in both sessions and decreased over time. At the lower sternal site, displacement only occurred during dynamic activities and decreased over time. Subjects who fully complied with sternal precautions had less upper sternal displacement during stand-to-sit (P = .043; ES = −1.076) and trend toward reduced displacement during sit-to-stand and horizontal abduction with large effect sizes, −. 893 and −. 975, respectively. Conclusion: Sternal displacement may vary with the task performed and between sternal sites. Reduced sternal displacement identified over time indicates sternal healing. Pectoralis major tension seems to be a primary mechanism of sternal displacement during common functional activities. Our findings suggest that full compliance with sternal precautions may promote sternal healing.
Multidimensional Scientometric Analysis for the Gig Economy

The phenomenon of globalization, which gained momentum after the 1980s, became widespread in all parts of the society and research of working life has become a normal situation. The phenomenon of globalization has been included in the socio-economic structure of the society through internet networks. It is considered necessary for individuals to turn into an online business structure that emerges through digital platforms in order to continue their lives, to maintain welfare and peace. Thus, an increase in the trends of research on the structure of working life in terms of social sustainability in the changing world order has been observed. The aim of the study is to obtain a holistic perspective in the multidimensional areas of the Gig economy, which is the counterpart of the online working platform. For this purpose, all data (820/732) obtained from the Web of Science database specific to the gig economy were included in the research. Multiple data were analyzed using the CiteSpace application. Trends in the Gig economy within the framework of social network theory, analysis in the context of the country, author analysis, cluster analysis and representative document analysis are presented. In this context, it is important to be able to make scientometric analyzes within the scope of the literature on the gig economy in order to obtain systematic findings for future research on the current labor market. With the research, literature trends, country analyzes and relationship networks, author productivity and the interpretative equivalent of keywords in the literature are revealed. According to the analysis findings; For the gig economy phenomenon, researches have been carried out in different fields in the socio-economic structure, and it can be stated that the studies may increase cumulatively in the future in terms of its social importance and prevalence.
Impact of Vegetation Gradient and Land Cover Conditions on Soil Moisture Retrievals From Different Frequencies and Acquisition Times of AMSR2

Spaceborne remote sensing provides great potential for soil moisture (SM) retrieval and emerged as a significant data source for research in land surface dynamics and associated applications. This study compared the error characteristics of SM estimates retrieved from the Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument on board National Aeronautics and Space Administration (NASA)’s Aqua satellite across different vegetation gradients and land cover conditions, at different overpass times and frequencies, to demonstrate their strengths and limitations. The results demonstrate that AMSR2 C-band products outperform AMSR2 X-band products over moderately and densely vegetated conditions due to lower attenuation by the vegetation canopy. Conversely, X-band products performed better than C-band products in barren lands possibly due to uneven sensing depth and microwave emissions from subsurface in C-band. The daytime products have a higher signal-to-noise ratio (SNR) in sparsely and moderately vegetated areas, whereas nighttime products have a higher SNR in densely vegetated areas. When these products are used selectively based on their error characteristics, the probability of obtaining SM with stronger signal than noise can be significantly improved (95%) at the expense of impaired spatial coverage (70% pixel loss).
BSCS Programs: Just How Effective Were They?

Public support for science education decreased progressively during the '70s and hit rock bottom in the early months of 1982 when the Science Education Directorate of the National Science Foundation came perilously close to extinction. Contributing to this demise of science education was the perceived ineffectiveness of the science programs developed with public monies in the '60s and early '70s. The general sentiment was that the new science programs were a waste of money and were the cause of declines in student scores in science and math throughout the '70s. But were the new programs ineffective? On what evidence were these conclusions based? We recently completed a quantitative synthesis, or meta-analysis, of 25 years of research comparing student performance in the new science programs to that in the more traditional courses. We found the new science programs to be consistently more effective than their traditional counterparts. Moreover, we found Biological Sciences Curriculum Study (BSCS) biology to be the most effective of all the new high school programs. In this report we will present the details of the BSCS research synthesis, showing how the BSCS programs compare to each other and to other science programs and how various student groups performed. We think these data are especially valuable in view of the recent swing in support of science education precipitated by the documented shortage of qualified science and math teachers for our elementary and secondary schools. Though huge investments in another round of curriculum development are not anticipated, policymakers and science educators will be looking at the interaction of teacher materials in an effort to come up with a working model for improved science instruction. We feel elements of programs such as BSCS should be considered in this search.
K-FL: Kalman Filter-Based Clustering Federated Learning Method

Federated learning is a distributed machine learning framework that enables a large number of devices to cooperatively train a model without data sharing. However, because federated learning trains a model using non-independent and identically distributed (non-IID) data stored at local devices, the weight divergence causes a performance loss. This paper focuses on solving the non-IID problems and proposes Kalman filter-based clustering federated learning method called K-FL to get performance gain by providing a specific model with low variance to the device. To the best of our knowledge, it is the first clustering federated learning method that can train a model requiring fewer communication rounds under the premise that non-IID environment without any prior knowledge and an initial value set by the user. From simulations, we demonstrate that the proposed K-FL can train a model much faster, requiring fewer communication rounds than FedAvg and LG-FedAvg when testing neural networks using the MNIST, FMNIST, and CIFAR-10 datasets. As a numerical result, it is shown that the accuracy is improved in all datasets while the computational time cost is reduced by <inline-formula> <tex-math notation="LaTeX">$1.43\times $ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$1.67\times $ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$1.63\times $ </tex-math></inline-formula> compared to FedAvg, respectively.