Miracle-dz/UniFAR-FTUs huggingface dataset:
TLR2, TLR4 and the MyD88 Signaling Are Crucial For the In Vivo Generation and the Longevity of Long-Lived Antibody-Secreting Cells

This study was undertaken to gain better insights into the role of TLRs and MyD88 in the development and differentiation of memory B cells, especially of ASC, during the Th2 polarized memory response induced by Natterins. Our in vivo findings demonstrated that the anaphylactic IgG1 production is dependent on TLR2 and MyD88 signaling, and that TLR4 acts as adjuvant accelerating the synthesis of high affinity-IgE. Also, TLR4 (MyD88-independent) modulated the migration of innate-like B cells (B1a and B2) out of the peritoneal cavity, and the emigration from the spleen of B1b and B2 cells. TLR4 (MyD88-independent) modulated the emigration from the spleen of Bmem as well as ASC B220pos. TLR2 triggered to the egress from the peritoneum of Bmem (MyD88-dependent) and ASC B220pos (MyD88-independent). We showed that TLR4 regulates the degree of expansion of Bmem in the peritoneum (MyD88-dependent) and in BM (MyD88-independent) as well as of ASC B220neg in the spleen (MyD88-independent). TLR2 regulated the intensity of the expansion of Bmem (MyD88-independent) and ASC B220pos (MyD88-dependent) in BM. Finally, TLR4 signals sustained the longevity of ASC B220pos (MyD88-independent) and ASC B220neg into the peritoneum (MyD88-dependent) and TLR2 MyD88-dependent signaling supported the persistence of B2 cells in BM, Bmem in the spleen and ASC B220neg in peritoneum and BM. Terminally differentiated ASC B220neg required the cooperation of both signals through TLR2/TLR4 via MyD88 for longevity in peritoneum, whereas Bmem required only TLR2/MyD88 to stay in spleen, and ASC B220pos rested in peritoneum dependent on TLR4 signaling. Our data sustain that earlier events on memory B cells differentiation induced in secondary immune response against Natterins, after secondary lymph organs influx and egress, may be the key to determining peripheral localization of innate-like B cells and memory B cells as ASC B220pos and ASC B220neg.
Childhood studies and the challenge of ontology

Does ontology matter in childhood studies? In their thinking and their research, should childhood scholars be actively concerned about matters of ontology? Might such a concern even hold a promise of contributing to theoretical and methodological progress in the multidisciplinary field of childhood studies? Such questions are certain to come up to childhood scholars when observing how in recent years distinct novelties have surfaced in scientific vocabularies. Prominent among them is the term ‘ontology’, often appearing in the context of discussions on ‘an ontological turn’. Since at least the late 1990s, ‘ontology’ has emerged and quickly spread in the literature and discussions of the social sciences and humanities, and well beyond them, up to computer and information sciences, Artificial Intelligence (AI) and robotics. The quantitative growth in the use of the term has been spectacular, as is shown in a study based on a search of the Web of Science (Van Heur et al., 2013). For the 20-year period up to the year 2008, the study shows an increase by more than 770% in the number of scientific articles, review essays and other documents which contain the term ‘ontology’ or some of its variants. The authors of the study then ask whether such an ‘explosion’ can be taken to signify, effectively, a ‘turn to ontology’ as has been claimed.1 And if indeed there has been a ‘turn’, what kind of a turn are we witnessing? Has a fresh way of thinking been opened, perhaps even a new paradigm? Or alternatively, is the turn best considered as a case of introducing ‘ontology’ as another ‘buzzword’ – a ‘modern flowery phrase’ which is put into the place of some other concepts formerly used in academic research and discussion, as has also been argued? 2 A close look at the recent move to ontology makes it clear that whatever the move signifies, it is anything but a single, unitary endeavour. Taking stock of the so-called ‘ontological turn’ in the field of economics, Pratten (2007a, 2007b) notes that a range of individuals and groups in the field are dealing with ‘ontology’ but in fact pursue quite distinct projects with varied intellectual ambitions. The conceptions of ontology that they deploy are distinct, and the ontological projects also come to competing conclusions concerning what ontological theorizing can or will contribute to the discipline. Similar conclusions are drawn practically in any other discipline or research field: different notions of ontology are deployed, with the result that it is not easy to understand which field of research the subject of ontology belongs to and how the notion might be useful for research. How has childhood studies fared in relation to such a turn? A tentative overview of the main journals that publish childhood research would seem to suggest that matters of ontology have hardly surfaced within this field. In Childhood, for instance, even the term 704539 CHD0010.1177/0907568217704539ChildhoodAlanen research-article2017
Feedback stabilisation of switched systems via iterative approximate eigenvector assignment

This paper presents and implements an iterative feedback design algorithm for stabilisation of discrete-time switched systems under arbitrary switching regimes. The algorithm seeks state feedback gains so that the closed-loop switching system admits a common quadratic Lyapunov function (CQLF) and hence is uniformly globally exponentially stable. Although the feedback design problem considered can be solved directly via linear matrix inequalities (LMIs), direct application of LMIs for feedback design does not provide information on closed-loop system structure. In contrast, the feedback matrices computed by the proposed algorithm assign closed-loop structure approximating that required to satisfy Lie-algebraic conditions that guarantee existence of a CQLF. The main contribution of the paper is to provide, for single-input systems, a numerical implementation of the algorithm based on iterative approximate common eigenvector assignment, and to establish cases where such algorithm is guaranteed to succeed. We include pseudocode and a few numerical examples to illustrate advantages and limitations of the proposed technique.
Test of two methods for faulting in finite-difference calculations

Abstract Tests of two fault boundary conditions show that each converges with second order accuracy as the finite-difference grid is refined. The first method uses split nodes so that there are disjoint grids that interact via surface traction. The 3D version described here is a generalization of a method I have used extensively in 2D; it is as accurate as the 2D version. The second method represents fault slip as inelastic strain in a fault zone. Offset of stress from its elastic value is seismic moment density. Implementation of this method is quite simple in a finite-difference scheme using velocity and stress as dependent variables.
THE GLOBULAR CLUSTER NGC 5286. I. A NEW CCD BV COLOR–MAGNITUDE DIAGRAM

We present BV photometry of the Galactic globular cluster NGC 5286, based on 128 V frames and 133 B frames, and covering the entire face of the cluster. Our photometry reaches almost two magnitudes below the turn-off level, and is accordingly suitable for age analysis. Field stars were removed statistically from the cluster's color–magnitude diagram (CMD), and a differential reddening correction applied, thus allowing a precise ridgeline to be calculated. Using the latter, a metallicity of [Fe/H] = −1.70 ± 0.05 in the Zinn & West scale, and [Fe/H] = −1.47 ± 0.02 in the Carretta & Gratton scale, was derived on the basis of several parameters measured from the red giant branch, in good agreement with the value provided in the Harris catalog. Comparing the NGC 5286 CMD with the latest photometry for M3 by P. B. Stetson, and using VandenBerg isochrones for a suitable chemical composition, we find evidence that NGC 5286 is around 1.7 ± 0.9 Gyr older than M3. This goes in the right sense to help account for the blue horizontal branch of NGC 5286, for which we provide a measurement of several morphological indicators. If NGC 5286 is a bona fide member of the Canis Major dwarf spheroidal galaxy, as previously suggested, our results imply that the latter's oldest components may be at least as old as the oldest Milky Way globular clusters.
Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system’s eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.
1,25-Dihydroxyvitamin D Modulates Antibacterial and Inflammatory Response in Human Cigarette Smoke-Exposed Macrophages

Cigarette smoking is associated with increased inflammation and defective antibacterial responses in the airways. Interestingly, vitamin D has been shown to suppress inflammation and to improve antibacterial defense. However, it is currently unknown whether vitamin D may modulate inflammation and antibacterial defects in human cigarette smoke (CS)-exposed airways. To explore these unresolved issues, alveolar macrophages obtained from non-smoking and smoking subjects as well as human cigarette smoke extract (CSE)-treated THP-1 macrophages were stimulated with 1,25-dihydroxyvitamin D (1,25(OH)2D) to address inflammatory and antibacterial responses. Although basal levels of inflammatory cytokines and chemokines did not differ between non-smoking and smoking subjects, 1,25(OH)2D did reduce levels of IL-6, TNF-α and MCP-1 in alveolar macrophages in response to LPS/IFN-γ, although not statistically significant for TNF-α and IL-6 in smokers. CSE did not significantly alter vitamin D metabolism (expression levels of CYP24A1 or CYP27B1) in THP-1 macrophages. Furthermore, stimulation with 1,25(OH)2D reduced mRNA expression levels and/or protein levels of IL-8, TNF-α and MCP-1 in CSE-treated THP-1 macrophages. 1,25(OH)2D did not improve defects in phagocytosis of E. coli bacteria or the oxidative burst response in CSE-treated THP-1 macrophages or alveolar macrophages from smokers. However, 1,25(OH)2D significantly enhanced mRNA expression and/or protein levels of the antimicrobial peptide cathelicidin in alveolar macrophages and THP-1 macrophages, independently of CS exposure. In conclusion, our results provide the first evidence that vitamin D could be a new strategy for attenuating airway inflammation and improving antibacterial defense in CS-exposed airways.
Hand gestures recognition based on lightweight evolving fuzzy clustering method

Robots of the future will socialize with humans. Human-robot interaction (HRI) by a vision-based gesture interface helps to personalize the communication with humans in various contexts - from support of their daily life to social skills training of children with developmental problems. We are especially interested in vision-based hand gesture HRI and propose a hand gesture recognition system based on a novel online extraction and classification scheme, which is lightweight and can be used in a mobile robot. An online Lightweight Evolving Fuzzy Clustering Method is used to categorize the positional and HSV model of pixels for the edges of the gesture image. The result clusters consist of (x, y) coordinates and the averaged grayscale level at these locations. Then these clusters are processed to identify typical for the hand features brighter and darker pixel information. The database consists of averaged grayscale levels in HSV format for neighbor pixels that characterize different features. For feature recognition we use Tanimoto similarity measure for matching the current grayscale patterns to those in the database. Then the feature location is encoded in a binary format. For gesture recognition we use a formalism of Symbol Relation Grammars to describe a gesture, as well as simple and fast bitwise operations to find the position and orientation of the features in the gesture.
Max-Margin Deep Generative Models

Deep generative models (DGMs) are effective on learning multilayered representations of complex data and performing inference of input data by exploring the generative ability. However, little work has been done on examining or empowering the discriminative ability of DGMs on making accurate predictions. This paper presents max-margin deep generative models (mmDGMs), which explore the strongly discriminative principle of max-margin learning to improve the discriminative power of DGMs, while retaining the generative capability. We develop an efficient doubly stochastic subgradient algorithm for the piecewise linear objective. Empirical results on MNIST and SVHN datasets demonstrate that (1) max-margin learning can significantly improve the prediction performance of DGMs and meanwhile retain the generative ability; and (2) mmDGMs are competitive to the state-of-the-art fully discriminative networks by employing deep convolutional neural networks (CNNs) as both recognition and generative models.
Assessment of binding forms of some elements in soil profiles using different extractants

In a study of trace elements in soil profile development in the Romanian Carpathians different approaches involving the use of extraction agents were used in order to distinguish between separate chemical binding forms of major and trace elements in the forest soils studied. In the present paper an attempt is made to derive some general conclusions about the relative binding of selected elements in forest soils by comparing the data obtained in the above study by using different extractants. The extracting solutions employed in this study were the following: HCl, 0.05 M, to mimic the plant-available pool of elements in soil, sodium pyrophosphate, 0.1 M, the classical reagent used to separate soil organic matter from the inorganic constituents of the soil, and HNO3 14 M, which extracts what may be defined as the “total reactive pool” of the elements, leaving behind only the fraction of elements strongly bound in the matrix. Samples from three different series of soil profiles collected in forested mountain areas of the northern part of the Eastern Carpathians, Romania, 126 samples in total, are the subject of the present work. To reveal the systematic trends in the extraction data and possibly explain these trends, ratios were calculated between concentrations of each element extracted with different agents. Generally less than 10% of the HNO3-extractable fraction is released by 0.05 M HCl, but the amount shows considerable variation among the elements studied. The relative amount extracted by pyrophosphate increases with organic matter content of the soil for Cu, Zn, Pb, Al, Fe, and Cr, stays more or less constant for Mn, K, and Mg, and decreases for Ca. These findings are discussed with respect to the different binding forms of the metals in the soil and the processes affecting their mobility. From the present results the metals may be ranked as follows with respect to their ability to form organic complexes in natural soils: Cu>Cr, Pb>Ca>Al>Fe, Zn, Mn, K>Mg.
Minimization method for relativistic electrons in a mean-field approximation of quantum electrodynamics

We study a mean-field relativistic model which is able to describe both the behavior of finitely many spin-1/2 particles like electrons and of the Dirac sea which is self-consistently polarized in the presence of the real particles. The model is derived from the QED Hamiltonian in Coulomb gauge neglecting the photon field. All our results are non-perturbative and mathematically rigorous.
Domain Splitting Algorithm for Mixed Finite Element Approximations to Parabolic Problems

In this paper we fromulate and study a domain decomposition algorithm for solving mixed nite element approximations to parabolic initial boundary value problems In contrast to the usual overlapping domain decomposition method this technique leads to noniterative algorithms i e the subdomain problems are solved independently and the solution in the whole domain is obtained from the local solutions by restriction and simple averaging The algorithm exploits the fact that the time discretization leads to an elliptic problem with a large positive coe cient in front of the zero order term The solutions of such problems exhibit a boundary layer with thickness proportional to the square root of the time discretization parameter Thus any error in the boundary conditions will decay exponentially and a reasonable overlap will produce a su ciently accurate method We prove that the proposed algorithm is stable in L norm and has the same accuracy as the implicit method
Short-term plasticity in hindlimb motoneurons of decerebrate cats.

Cat hindlimb motoneurons possess noninactivating voltage-gated inward currents that can, under appropriate conditions, regeneratively produce sustained increments in depolarization and firing of the cell (i.e., plateau potentials). Recent studies in turtle dorsal horn neurons and motoneurons indicate that facilitation of plateaus occurs with repeated plateau activation (decreased threshold and increased duration; this phenomenon is referred to as warm-up). The purpose of the present study was to study warm-up in cat motoneurons. Initially, cells were studied by injecting a slow triangular current ramp intracellularly to determine the threshold for activation of the plateau. In cells where the sodium spikes were blocked with intracellular QX314, plateau activation was readily seen as a sudden jump in membrane potential, which was not directly reversed as the current was decreased (cf. hysteresis). With normal spiking, the plateau activation (the noninactivating inward current) was reflected by a steep and sustained jump in firing rate, which was not directly reversed as the current was decreased (hysteresis). Repetitive plateau activation significantly lowered the plateau activation threshold in 83% of cells (by on average 5 mV and 11 Hz with and without QX314, respectively). This interaction between successive plateaus (warm-up) occurred when tested with 3- to 6-s intervals; no interaction occurred at times >20 s. Plateaus initiated by synaptic activation from muscle stretch were also facilitated by repetition. Repeated slow muscle stretches that produced small phasic responses when a cell was hyperpolarized with intracellular current bias produced a larger and more prolonged responses (plateau) when the bias was removed, and the amplitude and duration of this response grew with repetition. The effects of warm-up seen with intracellular recordings during muscle stretch could also be recorded extracellularly with gross electromyographic (EMG) recordings. That is, the same repetitive stretch as above produced a progressively larger and more prolonged EMG response. Warm-up may be a functionally important form of short-term plasticity in motoneurons that secures efficient motor output once a threshold level is reached for a significant period. Finally, the finding that warm-up can be readily observed with gross EMG recordings will be useful in future studies of plateaus in awake animals and humans.
Are abstract action words embodied? An fMRI investigation at the interface between language and motor cognition

The cognitive and neural representation of abstract words is still an open question for theories of embodied cognition. Generally, it is proposed that abstract words are grounded in the activation of sensorimotor or at least experiential properties, exactly as concrete words. Further behavioral theories propose multiple representations evoked by abstract and concrete words. We conducted a functional magnetic resonance imaging (fMRI) study to investigate the neural correlates of concrete and abstract multi-word expressions in an action context. Participants were required to read simple sentences which combined each concrete noun with an adequate concrete verb and an adequate abstract verb, as well as an adequate abstract noun with either kind of verbs previously used. Thus, our experimental design included a continuum from pure concreteness to mere abstractness. As expected, comprehension of both concrete and abstract language content activated the core areas of the sensorimotor neural network namely the left lateral (precentral gyrus) and medial (supplementary motor area) premotor cortex. While the purely concrete multi-word expressions elicited activations within the left inferior frontal gyrus (pars triangularis) and two foci within the left inferior parietal cortex, the purely abstract multi-word expressions were represented in the anterior part of left middle temporal gyrus that is part of the language processing system. Although the sensorimotor neural network is engaged in both concrete and abstract language contents, the present findings show that concrete multi-word processing relies more on the sensorimotor system, and abstract multi-word processing relies more on the linguistic system.
The Highs and Lows of a Cultural Transition: A Longitudinal Analysis of Sojourner Stress and Adaptation Across 50 Countries

The impact of living abroad is a topic that has intrigued researchers for almost a century, if not longer. While many acculturation phenomena have been studied over this time, the development of new research methods and statistical software in recent years means that these can be revisited and examined in a more rigorous manner. In the present study we were able to follow approximately 2,500 intercultural exchange students situated in over 50 different countries worldwide, over time both before and during their travel using online surveys. Advanced statistical analyses were employed to examine the course of sojourners stress and adjustment over time, its antecedents and consequences. By comparing a sojourner sample with a control group of nonsojourning peers we were able to highlight the uniqueness of the sojourn experience in terms of stress variability over time. Using Latent Class Growth Analysis to examine the nature of this variability revealed 5 distinct patterns of change in stress experienced by sojourners over the course of their exchange: a reverse J-curve, inverse U-curve, mild stress, minor relief, and resilience pattern. Antecedent explanatory variables for stress variability were examined using both variable-centered and person-centered analyses and evidence for the role of personality, empathy, cultural adaptation, and coping strategies was found in each case. Lastly, we examined the relationship between stress abroad with behavioral indicators of (mal)adjustment: number of family changes and early termination of the exchange program.