Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the source of near‐relativistic and relativistic electrons in Earth's inner radiation belt

Using observations from NASA's Van Allen Probes, we study the role of sudden particle enhancements at low L shells (SPELLS) as a source of inner radiation belt electrons. SPELLS events are characterized by electron intensity enhancements of approximately an order of magnitude or more in less than 1 day at L < 3. During quiet and average geomagnetic conditions, the phase space density radial distributions for fixed first and second adiabatic invariants are peaked at 2 < L < 3 for electrons ranging in energy from ~50 keV to ~1 MeV, indicating that slow inward radial diffusion is not the dominant source of inner belt electrons under quiet/average conditions. During SPELLS events, the evolution of electron distributions reveals an enhancement of phase space density that can exceed 3 orders of magnitude in the slot region and continues into the inner radiation belt, which is evidence that these events are an important—and potentially dominant—source of inner belt electrons. Electron fluxes from September 2012 through February 2016 reveal that SPELLS occur frequently (~2.5/month at 200 keV), but the number of observed events decreases exponentially with increasing electron energy for ≥100 keV. After SPELLS events, the slot region reforms due to slow energy‐dependent decay over several day time scales, consistent with losses due to interactions with plasmaspheric hiss. Combined, these results indicate that the peaked phase space density distributions in the inner electron radiation belt result from an “on/off,” geomagnetic‐activity‐dependent source from higher radial distances.
Immunogenicity of homologous low density lipoprotein after methylation, ethylation, acetylation, or carbamylation: generation of antibodies specific for derivatized lysine.

We previously showed that immunization of guinea pigs with reductively glucosylated guinea pig low density lipoprotein (LDL) or albumin resulted in the formation of antibodies specific for the glucosylated protein. The present studies were done to determine if modifications of homologous LDL or albumin, other than addition of carbohydrate, would also render these proteins immunogenic. We found that derivatization of lysine residues of guinea pig LDL or albumin by carbamylation, acetylation, ethylation, or even methylation rendered them immunogenic in guinea pigs. In addition, the specificity of the antibodies was strikingly influenced by whether modified homologous LDL or modified homologous albumin was used as the immunogen. Antibodies generated against modified LDL were directed almost exclusively against the derivatized lysine residues (i.e., carbamyllysine, acetyllysine, or methyllysine) and hence reacted equivalently with other modified proteins that contained the same lysine derivative. However, antibodies generated against guinea pig albumin (or fibrinogen) modified in the same ways reacted primarily with the modified protein used as immunogen, and not with the free lysine derivative, or with other similarly modified proteins. Each of the modifications referred to above could potentially occur in vivo. Therefore, the findings presented may be relevant to autoantibody formation and immunopathogenetic mechanisms in certain diseases.
Compact printed C-shaped monopole antenna with chip inductor

This paper presents one compact printed monopole antenna with one chip inductor embedded on the radiation elements. By introducing the chip inductor, the resonant frequency of the original antenna can be decreased by more than 37% while there is no significant influence on its radiation characteristics including radiation efficiency and antenna gain. Meanwhile, after adding the chip inductor, the higher mode of the original antenna can also be brought down to a lower frequency, which makes the proposed antenna resonate at the dual frequency band and simultaneously have a compact size. This antenna has a C-shaped geometry and its parameters including the location of the chip inductor are optimized by doing parametrical studies in Ansoft HFSS. The measurement and simulation results show that the proposed C-shaped monopole antenna can operate at 2.55–2.65GHz and 5.1–5.3GHz with peak gain of 2.2 and 4.7dB, respectively. Moreover, according to the simulation results, the radiation efficiency of this antenna at both bands is around 90%.
Bayesian estimation of predator diet composition from fatty acids and stable isotopes

Quantitative analysis of stable isotopes (SI) and, more recently, fatty acid profiles (FAP) are useful and complementary tools for estimating the relative contribution of different prey items in the diet of a predator. The combination of these two approaches, however, has thus far been limited and qualitative. We propose a mixing model for FAP that follows the Bayesian machinery employed in state-of-the-art mixing models for SI. This framework provides both point estimates and probability distributions for individual and population level diet proportions. Where fat content and conversion coefficients are available, they can be used to improve diet estimates. This model can be explicitly integrated with analogous models for SI to increase resolution and clarify predator–prey relationships. We apply our model to simulated data and an experimental dataset that allows us to illustrate modeling strategies and demonstrate model performance. Our methods are provided as an open source software package for the statistical computing environment R.
Crystal-Induced Neutrophil Activation: XI. Implication and Novel Roles of Classical Protein Kinase C1

Monosodium urate (MSU) crystals are among the most potent proinflammatory stimuli, and an innate immune inflammatory response to the crystal surface is involved in the pathology of gouty arthritis. Furthermore, MSU crystals have recently been identified as danger signals able to induce the maturation of dendritic cells. Release of the crystals into the joint cavity promotes an acute inflammation characterized by a massive infiltration of neutrophils that leads to tissue damage. Protein kinase C (PKC) represents a family of serine/threonine kinases that play central signaling roles in multiple cellular responses. This family of kinases is divided into three subfamilies based on second messenger requirements: conventional (or classical), novel, and atypical. Despite their role in signal transduction, very little is known about the involvement of the PKC family in the inflammatory reaction induced by MSU crystals. In the present study, we show that MSU crystals activate conventional PKC isoforms, and that this activation is necessary for the MSU crystal-induced degranulation and generation of a chemotactic activity in the supernatants of MSU crystal-stimulated human neutrophils. Evidence is also obtained that the tyrosine kinase Syk is a substrate of PKC and that the PKC-mediated serine phosphorylation of Syk is necessary to its interaction with the regulatory subunit of PI3K kinases (p85) and thus to the subsequent activation of these lipid kinases. These results suggest novel means of modulating neutrophil responses (through the specific regulation of PKC) during the acute phase of MSU crystal-induced inflammation.
Fate of the Amazon River dissolved organic matter in the tropical Atlantic Ocean

Constraining the fate of dissolved organic matter (DOM) delivered by rivers is a key to understand the global carbon cycle, since DOM mineralization directly influences air‐sea CO2 exchange and multiple biogeochemical processes. The Amazon River exports large amounts of DOM, and yet the fate of this material in the ocean remains unclear. Here we investigate the molecular composition and transformations of DOM in the Amazon River‐ocean continuum using ultrahigh resolution mass spectrometry and geochemical and biological tracers. We show that there is a strong gradient in source and composition of DOM along the continuum, and that dilution of riverine DOM in the ocean is the dominant pattern of variability in the system. Alterations in DOM composition are observed in the plume associated with the addition of new organic compounds by phytoplankton and with bacterial and photochemical transformations. The relative importance of each of these drivers varies spatially and is modulated by seasonal variations in river discharge and ocean circulation. We further show that a large fraction (50–76%) of the Amazon River DOM is surprisingly stable in the coastal ocean. This results in a globally significant river plume with a strong terrigenous signature and in substantial export of terrestrially derived organic carbon from the continental margin, where it can be entrained in the large‐scale circulation and potentially contribute to the long‐term storage of terrigenous production and to the recalcitrant carbon pool found in the deep ocean.
V. Discriminating among normal infants by multivariate analysis of Brazelton scores: lumping and smoothing.

One of the aims of the Brazelton Neonatal Assessment procedure (NBAS) is to elicit the same kind of behavior in an infant that is likely to affect the parents as they handle the infant during the first few months of life. The procedure and ratings which Brazelton included in the exam were chosen less for correspondence to personality traits in later life than for their salience in the social environment of early infancy. Thus, NBAS scores provide an attractive possibility for assessing the infant's initial contribution to the mother-infant dyad. This particular task can only be successful, however, if the rating scales indeed distinguish reliably among normal infants. While we agree wholeheartedly with Horowitz, Sullivan, and Linn (Chap. III) about the folly of assuming behavioral stability in the newborn, the NBAS can only assess the infant's contribution to interaction with others if it is responsive to something "true" of the infant beyond the one examination session. A first step in our task, therefore, is to reduce the several dozen items of the NBAS to a set of dimensions showing a reasonable test-retest reliability, that is, some characterization of individual differences stable in newborn infants at least over the first few days or weeks of life. I shall show that such dimensions exist and that they can be measured by averaging normalized scores over related items and then averaging over several independent examinations of the infant in each age period.
Mapping the b-Value and its Correlation with the Fractal Dimension in the Northeast Region of India

The northeast region of India, one of the most tectonically complex and high seismicity prone regions in the world, is examined with the power law distribution and fractal dimension of seismicity. About 1250 earthquakes (M 2.0 - 5.0) recorded by the permanent stationsltelemetric networks in the region during the period 1993-96 are analysed in this study. The Gutenberg-Richter power law distribution, b-value, is estimated by least square fit and maximum likelihood methods in the five selected tectonic blocks of the region. The b-values (0.5 - 0.9) obtained for the earthquakes (2.5 ≤ M ≤ 5.0) by both the methods are comparable, and it varies with space and depth. The spatial variations of b-value and the activity level ('a' coostant in the power law relation) are mapped. The maps imaged the higher frequency of earthquake occurrence as well as the higher activity level of the seismogenic structures in the region. The fractal dimensions (D) of spatial distribution of earthquakes in the selected tectonic blocks are calculated using the correlation integral. The estimated D values vary from 1.20 to 1.80.
Anisotropy as a signature of transverse collective flow.

We show that anisotropies in transverse-momentum distributions provide an unambiguous signature of transverse collective flow in ultrarelativistic nucleus-nucleus collisions. We define a measure of the anisotropy from experimental observables. The anisotropy coming from collective effects is estimated quantitatively using a hydrodynamical model, and compared to the anisotropy originating from finite multiplicity fluctuations. We conclude that collective behavior could be seen in Pb-Pb collisions if a few hundred particle momenta were measured in a central event.
Parameter reduction in a text-independent speaker verification system

Different methods for reducing parameters in a Gaussian mixture model (GMM) for text-independent speaker verification are investigated in this paper. The number of parameters is directly related to the memory requirement. Reducing the parameters is important in environments with limited memory resources or limited bandwidth for data transmission. In contrast to standard approaches such as reducing the number of mixture components in the GMM or the dimension of the acoustic space, speaker specific parameters are selected from a global parameter set. Experiments reveal a small performance degradation when only a few parameters are chosen. Reducing the number of parameters to 25% of the original count gives a slightly better performance compared to a four times smaller global parameter set.
A structure-based protocol for learning the family-specific mechanisms of membrane-binding domains

Motivation: Peripheral membrane-targeting domain (MTD) families, such as C1-, C2- and PH domains, play a key role in signal transduction and membrane trafficking by dynamically translocating their parent proteins to specific plasma membranes when changes in lipid composition occur. It is, however, difficult to determine the subset of domains within families displaying this property, as sequence motifs signifying the membrane binding properties are not well defined. For this reason, procedures based on sequence similarity alone are often insufficient in computational identification of MTDs within families (yielding less than 65% accuracy even with a sequence identity of 70%). Results: We present a machine learning protocol for determining membrane-targeting properties achieving 85–90% accuracy in separating binding and non-binding domains within families. Our model is based on features from both sequence and structure, thereby incorporation statistics obtained from the entire domain family and domain-specific physical quantities such as surface electrostatics. In addition, by using the enriched rules in alternating decision tree classifiers, we are able to determine the meaning of the assigned function labels in terms of biological mechanisms. Conclusions: The high accuracy of the learned models and good agreement between the rules discovered using the ADtree classifier and mechanisms reported in the literature reflect the value of machine learning protocols in both prediction and biological knowledge discovery. Our protocol can thus potentially be used as a general function annotation and knowledge mining tool for other protein domains. Availability: metador.bioengr. uic.edu Contact: huilu@uic.edu
FACTORS THAT MAY CONTRIBUTE TO THE ESTABLISHMENT OF MOBILE LEARNING IN INSTITUTIONS RESULTS FROM A SURVEY Factors That May Contribute to the Establishment of Mobile Learning in Institutions – Results From a Survey

Context awareness is essential in mobile learning being a highly personalized environment with diverse capabilities. Major challenges of context awareness are to define the learning context, how to sense it, and how to react to changes. Our proposed system provides a general architecture that facilitates contextualization using current widely-used web standards. It provides a systematic approach to achieve contextualization defining major components and their functionalities without deepening into details. It uses web services to connect to resources making them reusable and distributable. In addition, all technologies and platforms proposed in our system are available under General Public License (GPL) hence facilitating immediate implementation. The paper ends with a real world scenario where m-Learning could be the only solution.
Optimal rate and delay performance in non-cooperative opportunistic spectrum access

We study transmission rate control and performance delay in cognitive radio (CR) links from a cross-layer perspective. We assume a hierarchical CR network where the secondary users (SU) access the spectrum band in an opportunistic and noncooperative way. The SU goal is to transmit a fixed-size file (fixed amount of data packets) during the sojourn time of the primary users (PU's) idle state. We assume that the SU's support frames retransmission through an automatic repeat request (ARQ) mechanism. By formulating the problem as a Markov decision process, we demonstrate that there is always an optimal stationary rate adaptation policy, and we propose a simple algorithm to obtain it. We derive an exact closed-form expression for the probability of successful transmission as a function of the PU's access probability and the signal-to-noise ratio at the link receiver. We also study the performance delay, understood as the time required to transmit the entire data file, taking into account frames retransmission. To do that, we analyze the Markov process associated with the optimal rate policy in the transform domain. Then, using probabilistic flow-graph techniques, we derive exact closed-form expressions for the statistical distribution of transmission delay.
Estimating vascular volume fraction in a network of small blood vessels with high-frequency power Doppler ultrasound

Quantitative images of high-frequency (> 20 MHz) power Doppler ultrasound can be difficult to obtain in the presence of flow artifacts due to power Doppler's sensitivity to operator-dependent acquisition settings. To improve flow quantification, color pixel density (CPD) can be plotted as a function of wall filter cut-off velocity to produce a wall-filter selection curve that can be used to estimate vascular volume fraction by locating the plateau along the curve. The behavior of the wall-filter selection curve in a multiple-vessel region of interest is studied using a custom-designed multiple-vessel flow phantom. The flow phantom is capable of mimicking a range of blood vessel sizes (200–300 µm), blood flow velocities (1–10 mm/s), and blood vessel orientations (long-axis and transverse). At high flow rates, single-vessel wall-filter selection curves superimpose to produce a multiple-vessel curve where the CPD at the left-most plateau corresponds with the actual vascular volume fraction. However, interpretation of the multiple-vessel wall-filter selection curve is not straightforward when the flow rate in the vascular network is low.
Using meta‐analysis to understand the impacts of dietary protein and fat content on the composition of fecal microbiota of domestic dogs (Canis lupus familiaris): A pilot study

Abstract The interplay between diet and fecal microbiota composition is garnering increased interest across various host species, including domestic dogs. While the influence of dietary macronutrients and their associated microbial communities have been extensively reviewed, these reviews are descriptive and do not account for differences in microbial community analysis, nor do they standardize macronutrient content across studies. To address this, a meta‐analysis was performed to assess the impact of dietary crude protein (“protein”) and dietary crude fat (“fat”) on the fecal microbiota composition in healthy dogs. Sixteen publications met the eligibility criteria for the meta‐analysis, yielding a final data set of 314 dogs. Diets were classed as low, moderate, high, or supra in terms of protein or fat content. Sequence data from each publication were retrieved from public databases and reanalyzed using consistent bioinformatic pipelines. Analysis of community diversity indices and unsupervised clustering of the data with principal coordinate analysis revealed a small effect size and complete overlap between protein and fat levels at the overall community level. Supervised clustering through random forest analysis and partial least squares‐discriminant analysis indicated alterations in the fecal microbiota composition at a more individual taxonomic level, corresponding to the levels of protein or fat. The Prevotellaceae Ga6A1 group and Enterococcus were associated with increasing levels of protein, while Allobaculum and Clostridium sensu stricto 13 were associated with increasing levels of fat. Interestingly, the random forest analyses revealed that Sharpea, despite its low relative abundance in the dog's fecal microbiome, was primarily responsible for the separation of the microbiome for both protein and fat. Future research should focus on validating and understanding the functional roles of these relatively low‐abundant genera.
The Measurement of Phonetic Similarity

There are many reasc~s for wanting to measure the degree of phoae-tic similarity between members of a group of languages or dialects. The present study grew out of a research project which was designed to get data that might have a bearing on some of the practical problems which exist in Uganda. In the Southern part of Uganda, where two thirds of the nine million people live, there are numerous closely related Bantu languages or dialects. The official Ugandan census data lists 15 Bantu languages. The current study uses data on these and six others. We wanted to assess their phonetic similarity so that there would be data on which to base decisions on which languages to use for broadcasting (the government currently broadcasts in 8 or 9 of these languages, as well as in i0 non-Bantu languages), which to use in schools (3 are used officially and a further 5 unofficially, but with the connivance of the local education authorities), and which for other purposes. One method of obtaining a measure might have been by devising a metric that could be applied to formal comparisons of phonological descriptions of each of these languages. This method was not attempted, largely because of time limitations. The data had to be collected and first analyses made within a period of one year. Furthermore, it soon appeared that the sound patterns of nearly all of these languages were very similar, and the phonological descriptions would have to be eXtremely detailed before systematic differences became apparent. Finally,
Box-particle PHD filter for multi-target tracking

This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable to deal with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small particle number makes this approach attractive for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes methods from the field of interval analysis. The theoretical derivation of the box-PHD filter is presented followed by a comparative analysis with a standard sequential Monte Carlo (SMC) version of the PHD filter. To measure the performance objectively three measures are used: inclusion, volume and the optimum subpattern assignment metric. Our studies suggest that the box-PHD filter reaches similar accuracy results, like a SMC-PHD filter but with much considerably less computational costs. Furthermore, we can show that in the presence of strongly biased measurement the box-PHD filter even outperforms the classical SMC-PHD filter.