Miracle-dz/UniFAR-FTUs huggingface dataset:
CELLULAR DYNAMICS IN NOISY ENVIRONMENT

Cells are continuously subjected to noisy internal and external environments. Though cellular functions are carried on quite reliably under such noise, they can also result in fluctuations of parameters of the various biochemical processes and cause the dynamics of the reaction pathway to change. To show the varied effects of noisy environment on cellular dynamics, we consider a model cell containing a minimal biochemical pathway that exhibits a wide array of dynamical behaviors – from equilibrium, simple limit cycles and higher periodics, birhythmicity, complex oscillations and chaos - that are observed in many cellular functions. We show that, even under constant parameters, small fluctuations in the variables (i.e., substrate concentrations) can facilitate switching of the dynamics between oscillatory states with very different amplitudes and frequencies. The final temporal behavior of the pathway is unpredictable for the range of parameters where birhythmicity is observed. Parametric noise can mask the original dynamics of the pathway in the birhythmic state, though considerable robustness in dynamics is seen in the presence of noise for other values of parameters. Thus we show that the cellular dynamics can exhibit both robust and non-robust behavior in noisy environment for different parameters in the same pathway.
POLARIMETRIC CALIBRATION OF MIMIR AND THE GALACTIC PLANE INFRARED POLARIZATION SURVEY (GPIPS)

Methods and observations are described for the full field of view (FOV) polarimetric calibration of the Mimir near-infrared imaging polarimeter in support of the Galactic Plane Infrared Polarization Survey and other applications. Polarimetric calibration consisted of three steps: (1) flat fielding using in-dome images obtained with the compound zero-order half-wave-plate (HWP) in the 16 position angles employed in polarimetric observations, (2) mapping and removing the remaining instrumental polarization via observations of globular cluster stars, and (3) using polarization standard stars to convert instrument-based polarization position angles to equatorial and to determine the linear polarimetric efficiency. For Mimir, the polarization flat fielding reduced systematic variations of the polarization efficiency across the FOV by a factor of 20. The 151 observations of eight globular clusters yielded 40,000 stars for measuring the remaining 0.05%–0.45% instrumental polarization to uncertainties of 0.02%–0.04%. After these corrections, the 444 observations of 23 polarized stars enabled equatorial polarization position angles to be determined to typical uncertainties of 0. °5, and the on-axis (corrected to full FOV) polarization efficiency of 91.1% ± 0.4% to be determined. Fully corrected standard star observations showed excellent agreement with published values of polarization percentage and position angle. Additionally, the observations of four sky fields containing Whittet et al. “primary” polarization standard stars were analyzed to yield 30 new “secondary” standards. These are fainter than the primaries, allowing use with larger telescope apertures. The secondary standards have polarization position angle uncertainties under 5° and range in degree of polarization from 0.4% to 8.5%.
Hα Polarization during a Well-observed Solar Flare: Proton Energetics and Implications for Particle Acceleration Processes

Observations of polarization of chromospheric lines in solar flares can constrain the energy flux in accelerated protons. In this paper we analyze recently reported observations of Hα linear polarization obtained during a rather well observed flare on 1989 June 20. Modeling of the magnitude and orientation of the Hα polarization provides a constraint on the flux of low energy (≳200 keV) protons, while simultaneous gamma-ray and hard X-ray observations provide constraints on the fluxes of ≳10 MeV protons and ≳50 keV electrons, respectively. These, plus information on the energetics of the low-temperature and high-temperature thermal emissions, permit evaluation of both the absolute and relative roles of electrons and protons in the flare energy budget. We find that accelerated protons with energies ≳200 keV can contain a significant portion of the total energy released during the flare, consistent with a steep extrapolation of the proton spectrum to such relatively low energies. We discuss these results in light of a unified electron/proton stochastic particle acceleration model and show that the energetics are indeed consistent with this large proton energy content.
Modeling and enhancing magnetic immunity of STT-MRAM

In this paper, the magnetic immunity model of STT-MRAM is established. The influence of the external magnetic field on the effective energy barrier of STT-MRAM is investigated, which is the crucial issue to influence the reliability of STT-MRAM cells in the standby, active read and active write modes. The influence factors on the magnetic immunity of STT-MRAM array are also discussed in the paper, such as the electrode, package material, insert layer and array spacing, etc. Moreover, the magnetic shield models in the BGA and QFP packages are designed and analyzed for the enhancement of the magnetic immunity of STT-MRAM, whose shielding efficiency is up to 98.2%.
ADL based Framework For Multimodal Data Fusion in Traffic Jam prediction

Recently, intelligent transportation system (ITS) is considered as one of the most important issues in smart city applications. Its supports urban and regional development and promotes economic growth, social development, and enhances human well-being. ITS integrates new technologies of information and communication including sensors, social media IoT devices which can generate a massive amount of heterogeneous and multimodal data known as big data term. In this context, Data Fusion techniques (DF) seem promising and have emerged from transportation applications and hold a promising opportunity to deal with imperfect raw data for capturing reliable, valuable and accurate information. In literature many DF techniques based on machine learning remarkably renovates fusion techniques by offering the strong ability of computing and predicting. In this paper, we propose new Hybrid method based on Deep Learning combine two independent model such as CNN, LSTM models to fuse multimodal and spatial temporal data. The proposed model uses Extended Kalman Filter (EKF) to combine result of the proposed DL classifiers. In the other side, the proposed approach uses CBOA algorithm for feature selection in order to provide effective exploration of significant features with faster convergence
A novel self-learning framework for fault identification of wind turbine drive bearings

The drive train is one of the core structures of a wind turbine, and its working condition seriously affects the performance quality. It is important to identify the fault pattern of the drive bearings in time to ensure the safety and reliability of the wind turbine. However, in traditional methods, offline modeling and online identification are often fragmented, and such a mechanism limits the adaptive updating of the model. To realize real-time updating and self-learning of the identification model, we proposed a novel self-learning framework for the intelligent fault identification of wind turbine drive bearings. First, a complete ensemble empirical mode decomposition with adaptive noise analysis–based quantification scheme for intrinsic mode function values is proposed. Then, based on the intrinsic mode function values, we offer an attention mechanism for fault feature identification and construct an initial fault pattern database using unsupervised clustering techniques. Second, abnormal data are identified by the proposed artificial immunity–based outlier detection algorithm to determine the type of immune response. Third, we design an automatic update strategy based on incremental learning to realize adaptive creation, deletion, and modification of fault patterns. The proposed intelligent framework is applied to the fault diagnosis of a real offshore wind turbine drive train, showing its advantages in intelligent fault identification and model updating.
Evidence of Insulin-Sensitizing and Mimetic Activity of the Sesquiterpene Quinone Avarone, a Protein Tyrosine Phosphatase 1B and Aldose Reductase Dual Targeting Agent from the Marine Sponge Dysidea avara

Type 2 diabetes mellitus (T2DM) is a complex disease characterized by impaired glucose homeostasis and serious long-term complications. First-line therapeutic options for T2DM treatment are monodrug therapies, often replaced by multidrug therapies to ensure that non-responding patients maintain target glycemia levels. The use of multitarget drugs instead of mono- or multidrug therapies has been emerging as a main strategy to treat multifactorial diseases, including T2DM. Therefore, modern drug discovery in its early stages aims to identify potential modulators for multiple targets; for this purpose, exploration of the chemical space of natural products represents a powerful tool. Our study demonstrates that avarone, a sesquiterpene quinone obtained from the sponge Dysidea avara, is capable of inhibiting in vitro PTP1B, the main negative regulator of the insulin receptor, while it improves insulin sensitivity, and mitochondria activity in C2C12 cells. We observe that when avarone is administered alone, it acts as an insulin-mimetic agent. In addition, we show that avarone acts as a tight binding inhibitor of aldose reductase (AKR1B1), the enzyme involved in the development of diabetic complications. Overall, avarone could be proposed as a novel natural hit to be developed as a multitarget drug for diabetes and its pathological complications.
Platooning Control of Vehicular Systems by Using Sampled Positions

This brief studies the platooning control problem of vehicular systems, where the leader control input is non-zero. In contrast to the existing results with full knowledge of the vehicle state (i.e., position, velocity, and acceleration) for feedback, a new platoon control law is designed, which depends on the currently and most recently sampled positions only. To explore the input-to-state stability (ISS) of the resulting platoon control system, sufficient conditions are presented in the form of linear matrix inequalities (LMIs) by using appropriate Lyapunov functionals. Then a design criterion for the existence of the sampled-position-based controller is derived. Finally, an example illustrates the efficiency of the method.
Traveling Wave Solutions for the Generalized Zakharov Equations

We use the bifurcation method of dynamical systems to study the traveling wave solutions for the generalized Zakharov equations. A number of traveling wave solutions are obtained. Those solutions contain explicit periodic wave solutions, periodic blow-up wave solutions, unbounded wave solutions, kink profile solitary wave solutions, and solitary wave solutions. Relations of the traveling wave solutions are given. Some previous results are extended.
A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

This article presents a novel methodology dedicated to retrieving the optical and microphysical properties of ice and liquid water clouds simultaneously. An optimal estimation method is used to retrieve the ice water path of one ice‐cloud layer and the optical thickness and droplet effective radius of up to two liquid‐water cloud layers, along with rigorous uncertainties. In order to perform the retrievals, radiometric measurements in five channels ranging from the visible to the thermal infrared are utilized. The position of cloud layers is currently provided by lidar information, which narrows the retrievals to its track. In the first part of this article, theoretical information content analyses are performed under different atmospheric conditions, over an oceanic surface. This type of analysis quantifies prior to the retrievals the amount of information that should be available regarding each parameter to be retrieved and helps to identify which set of channels provides this information. It is observed that strong information can be expected for retrieving each parameter in double‐layer cases, while yet stronger limitations appear in triple‐layer cases. In the second part of this article, our methodology is applied to a case study. In agreement with a priori expectations, accurate retrievals of ice and liquid cloud properties are obtained. These results are later compared with the products of a single‐layer retrieval method, Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) operational products and in situ estimates. We show that a much better consistency with the latter two is found when retrieving the properties of each layer simultaneously. However, further statistical analyses and comparisons with various operational products should be undertaken for validation of the methodology. Such results will be presented in the second part of this study.
Recovery of lithium from coal gangue utilizing acid baking followed by water leaching

ABSTRACT With the rapid development of the lithium (Li)-ion battery industry in electric vehicles (EVs) and electronic devices, coal-based Li ore is expected to be a new-type Li resource to meet the rapidly growing demand for Li. However, the traditional Li extraction process involves high temperature to activate minerals. Herein, a low-temperature sulfuric acid baking followed by water leaching was investigated in this study. The influences of baking and leaching conditions on Li leaching rate were explored in detail. Under the optimal conditions of 70 wt% H2SO4, baking temperature 180°C, baking time 1 h, leaching temperature 25°C, and leaching time 1 h, the Li leaching rate reached 84.42%. In addition, the sequential chemical extraction, XRD, and SEM-EDS results indicated that Al-Li-containing minerals were converted to soluble minerals during the baking process with sulfuric acid and then were extracted through water leaching into the solution.
Banach Algebras and Their Applications

Given a metrizable topological vector space, we can also use its von Neumann bornology or its bornology of precompact subsets to do analysis. We show that the bornological and topological approaches are equivalent for many problems. For instance, they yield the same concepts of convergence for sequences of points or linear operators, of continuity of functions, of completeness and completion. We also show that the bornological and topological versions of Grothendieck's approximation property are equivalent for Frechet spaces. These results are important for applications in noncommutative geometry. Finally, we investigate the class of ``smooth'' subalgebras appropriate for local cyclic homology and apply some of our results in this context.
Current-driven parametric resonance in magnetic multilayers

Current-induced parametric excitations were observed in point-contact spin-valve nanodevices. Point contacts were used to inject high densities of direct and microwave currents into spin valves, thus producing oscillating spin-transfer and Oersted-field torques on magnetic moments. The resulting magnetodynamics were observed electrically by measuring rectified voltage signals across the contact. In addition to the spin-torque-driven ferromagnetic resonance we observe doubled-frequency signals which correspond to the parametric excitation of magnetic moments. Numerical simulations suggest that while both spin-transfer torque and ac Oersted field contribute to the parametrically excited dynamics, the ac spin torque dominates, and dc spin torque can switch it on and off. The dc bias dependence of the parametric resonance signal enabled the mapping of instability regions characterizing the nonlinearity of the oscillation.
The nature of the galaxy around 3C 48

New images are presented of the QSO 3C 48 in line-free bands centered at 0.58, 0.77, and 2.1 microns and in a narrowband centered on the forbidden O III5007 line. Careful profile subtraction of the continuum images shows an apparent luminosity peak centered about 1 arcsec northeast of the QSO position, which is tentatively identified as the nucleus of a galaxy in the process of merging with the host galaxy of 3C 48. The arclike structure extending to the northwest appears to be a tidal tail associated with the companion galaxy. While the confirmation that the host galaxy of 3C 48 is interacting is consistent with the inference that 3C 48 and similar objects are transitional between ultraluminous starburst galaxies and classical QSOs, an apparent correlation between far-infrared spectral properties and optical morphology suggests that the supposed 'transitional' characteristics may persist for at least 10 to the 8th yr, so the place of objects like 3C 48 in an evolutionary scenario depends on the typical lifetime of QSO activity. 38 refs.
Coarse-to-Fine Crater Matching From Heterogeneous Surfaces of LROC NAC and Chang’e-2 DOM Images

The centers of matching craters can be beneficial additions to the control point database. Crater matching on heterogeneous surfaces is helpful in testing its applicability to the entire moon. Therefore, we propose a coarse-to-fine crater matching method for heterogenous surfaces on images acquired from the narrow angle camera (NAC) of the lunar reconnaissance orbiter camera (LROC) and the Chang’e-2 (CE-2) digital orthophoto map (DOM). First, we perform coarse matching based on the Hausdorff distance using the area and coordinates of the crater. Then, the mismatched craters are removed by using the affine transform (AT) model fitted by corresponding points of mutual information (MI) matching. Finally, we use the retained matched crater centers to fit the affine transformation model between the images, predict the corresponding position, and obtain the corresponding crater around it to achieve fine matching. The results show that the proposed method obtains numerous crater matches on images covering different terrains and solar altitude angles compared to the Hausdorff distance-based crater matching method. For the five experimental scenes registered using matched craters, the mean values of the checkpoints are approximately two and three pixels for scenes with small and large differences from CE-2 solar altitude angles, respectively, and the standard deviations (STDs) for both are approximately one pixel. In addition, the highlands have lower accuracy than the maria, with a variance of less than one pixel. Furthermore, the registration accuracy is related to the diameter and number of craters.
Development of a Novel Low-Calorie Lime Juice-Based Prebiotic Beverage Using a Combined Design Optimization Methodology

A novel lime-juice based low-calorie functional beverage was developed by using D-optimal combined design optimization. For the preparation of the beverage, the following functional ingredients were used: lime juice, lime peel essential oil (LEO) as a flavoring agent and bioactive component, sucralose as a low-calorie sweetener, an inulin/polydextrose (I/P) mixture as prebiotic fibers, pectin as a thickening agent and soluble dietary fiber, lutein as a carotenoid colorant and antioxidant, and peppermint extract (ME) as a flavoring agent and bioactive component. A combined design consisting of one mixture factor (LEO/ME ratio), one numeric factor (lutein concentration), and one categoric factor (presence or absence of prebiotics) was used for optimizing the functional beverage based on the sensory quality. Regression models were adequately fitted to the data of sensory acceptance with a determination coefficient >90%. The sample containing a mixture of prebiotics, 2:3 (v/v) ratio of LEO: ME, and 3 mg/100 mL lutein was selected as the best formulation among the six optimal beverages which was suggested by Design-Expert software. This final optimum sample showed the highest total phenolic (44.22 mg gallic acid equivalents/L) and flavonoid (25.49 mg quercetin equivalents/L) contents, and its antioxidant activity (as 2,2-diphenyl-1-picrylhydrazyl radical (DPPH•) scavenging) was 38.30%. The newly designed beverage has the potential to promote health benefits and in therapeutic applications.
DIRECTIONAL OPERATORS AND MIXED NORMS

We present a survey of mixed norm inequalities for several directional operators, namely, directional Hardy-Littlewood maximal functions and Hilbert transforms (both appearing in the method of rotations of Calder´on and Zygmund), X-ray transforms, and directional fractional operators related to Riesz type potentials with variable kernel. In dimensions higher than two several interesting questions remain unanswered.
Waterton-Mauro Description and Configurational Relaxativity of Relaxor Ferroelectrics

Dielectric relaxation of relaxor ferroelectrics can be described by Vogel-Fulcher equation including a frozen temperature. For avoiding the problem, Waterton-Mauro equation is introduced to express the phenomenon based on the temperature dependent configurational entropy. Waterton-Mauro type relaxativity is derived to describe the degree of relaxation. By comparing the results of dielectric data of BaTiO3-SrZrO3(65/35), PMN-PT(90/10) and PMN-PT(100/0) ceramics a concept of “configuration relaxativity” is proposed to explain influence of change of configurations on relaxation, more exactly than the temperature interval between two dielectric peaks.
On Use of the EM Algorithm for Penalized Likelihood Estimation

SUMMARY The EM algorithm is a popular approach to maximum likelihood estimation but has not been much used for penalized likelihood or maximum a posteriori estimation. This paper discusses properties of the EM algorithm in such contexts, concentrating on rates of conver- gence, and presents an alternative that is usually more practical and converges at least as quickly. The EM algorithm is a general approach to maximum likelihood estimation, rather than a specific algorithm. Dempster et al. (1977) discussed the method and derived basic properties, demonstrating that a variety of procedures previously developed rather informally could be unified. The common strand to problems where the approach is applicable is a notion of 'incomplete data'; this includes the conventional sense of 'missing data' but is much broader than that. The EM algorithm demon- strates its strength in situations where some hypothetical experiment yields data from which estimation is particularly convenient and economical: the 'incomplete' data actually at hand are regarded as observable functions of these 'complete' data. The resulting algorithms, while usually slow to converge, are often extremely simple and remain practical in large problems where no other approaches may be feasible. Dempster et al. (1977) briefly refer to the use of the same approach to the problem of finding the posterior mode (maximum a posteriori estimate) in a Bayesian estima-
Evolutionary Dynamics of Avian Influenza Viruses Isolated from Wild Birds in Moscow

Forty-five strains of AIVs were isolated from wild aquatic birds during their autumn migration through Moscow (Russia). The aim of this work is to study the dynamics of AIV genomes in their natural habitat. Viruses were isolated from fecal sample in embryonated chicken eggs; their complete genomes were sequenced, and a phylogenetic analysis was performed. The gene segments of the same lineage persisted over the years in the absence of persistence of complete viral genomes. The genes for internal proteins of the same lineage were often maintained by the viruses over few years; however, they were typically associated with the genes of novel HA and NA subtypes. Although frequent reassortment events were observed for any pair of internal genes, there was no reassortment between HA and NA segments. The differences in the persistence of phylogenetic lineages of surface and internal proteins and the different evolutionary strategy for these two types of genes of AIVs in primary hosts are discussed.