Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on the structure and properties of Poly(methylmethacrylate)/Polypyrrole-Graphene Oxide nanocomposites

ABSTRACT In this paper Poly(methylmethacrylate)/Polypyrrole-Graphene Oxide (PMMA/PPy-GO) nanocomposites were prepared using in-situ chemical polymerization method and its structure and properties were studied. Fourier transform infrared (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) analysis confirmed that PPy nanopraticles covered the GO nanosheets surface and PMMA/PPy-GO nanocomposite were prepared successfully. The mechanical, electrical and thermal stability of the PMMA nanocomposites were also investigated using Tensile, Impact, Thermogravimetric analysis (TGA) and four-point probe methods. Correlation between direct morphological observation and final properties demonstrated that network structure formed by PPy-GOs in PMMA matrix. Tensile analysis showed that the addition of 0.4 wt % PPy-GO hybrids lead to 24.4 % enhancement in the Young’s modulus of PMMA compared to 5.0 % improvement that achieved at the same loading level of GO. Electrical conductivity measurement showed that dispersion of PPy-GO in PMMA matrix increased AC conductivity in the range of 8 orders of magnitude compared to PMMA. TGA analysis showed that the thermal stability of the PMMA nanocomposites improved over 20 ̊C. Graphical Abstract
Obtaining Word Phrases with Stochastic Inversion Translation Grammars for Phrase-based Statistical Machine Translation

Phrase-based statistical translation systems are currently providing excellent results in real machine translation tasks. In phrase-based statistical translation systems, the basic translation units are word phrases. An important problem that is related to the estimation of phrase-based statistical models is the obtaining of word phrases from an aligned bilingual training corpus. In this work, we propose obtaining word phrases by means of a Stochastic Inversion Transduction Grammar. Preliminary experiments have been carried out on real tasks and promising results have been obtained.
Growth factor signaling alters the morphology of the zebrafish ethmoid plate

Craniofacial development relies on coordinated tissue interactions that allow for patterning and growth of the face. We know a priori that the Wingless, fibroblast growth factor, Hedgehog and transforming growth factor‐beta growth factor signaling pathways are required for the development of the face, but how they contribute to the shape of the face is largely untested. Here, we test how each signaling pathway contributes to the overall morphology of the zebrafish anterior neurocranium. We tested the contribution of each signaling pathway to the development of the ethmoid plate during three distinct time periods: the time of neural crest migration [10 hour post fertilization (hpf)]; once the neural crest is resident in the face (20 hpf); and finally at the time at which the cartilaginous condensations are being initiated (48 hpf). Using geometric morphometric analysis, we conclude that each signaling pathway contributes to the shape, size and morphology of the ethmoid plate in a dose‐, and time‐dependent fashion.
Parallelizing hot topic detection of microblog on spark

With the emergence of the big data age, how to get valuable hot topic from the vast amount of digitized textual materials quickly and accurately has attracted more and more attention. This paper proposes a parallel Two-phase Mic-mac Hot Topic Detection(TMHTD) method specially design for microblogging in “Big Data” environment, which is implemented based on Apache Spark cloud computing environment. TMHTD is a distributed clustering framework for documents sets with two phases, including micro-clustering and macro-clustering. In the first phase, TMHTD partitions original data sets into a group of smaller data sets, and these data subsets are clustered into many small topics, producing intermediate results. In the second phase, the intermediate results are integrated into one, further clustered, and achieve the final hot topic sets. To improve the accuracy of the hot topic detection, an optimization of TMHTD is proposed. To handle large databases, we deliberately design a group of MapReduce jobs to concretely accomplish the hot topic detection in a highly scalable way. Extensive experimental results indicate that the accuracy and performance of TMHTD algorithm can be improved significantly over existing approaches.
Multipathway Kinase Signatures of Multipotent Stromal Cells Are Predictive for Osteogenic Differentiation

Bone marrow‐derived multipotent stromal cells (MSCs) offer great promise for regenerating tissue. Although certain transcription factors have been identified in association with tendency toward particular MSC differentiation phenotypes, the regulatory network of key receptor‐mediated signaling pathways activated by extracellular ligands that induce various differentiation responses remains poorly understood. Attempts to predict differentiation fate tendencies from individual pathways in isolation are problematic due to the complex pathway interactions inherent in signaling networks. Accordingly, we have undertaken a multivariate systems approach integrating experimental measurement of multiple kinase pathway activities and osteogenic differentiation in MSCs, together with computational analysis to elucidate quantitative combinations of kinase signals predictive of cell behavior across diverse contexts. In particular, for culture on polymeric biomaterial surfaces presenting tethered epidermal growth factor, type I collagen, neither, or both, we have found that a partial least‐squares regression model yields successful prediction of phenotypic behavior on the basis of two principal components comprising the weighted sums of eight intracellular phosphoproteins: phospho‐epidermal growth factor receptor, phospho‐Akt, phospho‐extracellular signal‐related kinase 1/2, phospho‐heat shock protein 27, phospho‐c‐Jun, phospho‐glycogen synthase kinase 3α/β, phospho‐p38, and phospho‐signal transducer and activator of transcription 3. This combination provides the strongest predictive capability for 21‐day differentiated phenotype status when calculated from day‐7 signal measurements; day‐4 and day‐14 signal measurements are also significantly predictive, indicating a broad time frame during MSC osteogenesis wherein multiple pathways and states of the kinase signaling network are quantitatively integrated to regulate gene expression, cell processes, and ultimately, cell fate. STEM CELLS 2009;27:2804–2814
MSPLS 2002 Proceedings of the Workshop of the Midwest Society for Programming Languages and Systems Bloomington , Indiana April 13 , 2002

Aspect-oriented technology is a programming paradigm that provides the user with the ability to modularize the representation of crosscutting concerns in order to maximize the reusability and ensure the flexibility of software system. In this position paper we present the Dynamic Weaver Framework (DWF), which is an aspect-oriented framework that supports the dynamic attachment of aspects to components at run-time and also the dynamic detachment of aspects from components. As well as the capability to add and remove aspects and pointcuts during runtime. This capability is the prime factor that enables us to support reconfigurability of software systems. The need to adapt to environmental changes and cope gracefully with the challenges that may have an impact on performance degradation, safety and liveness properties of the running system requires recongfigurability of both the functional and aspectual properties of the system software.
Review on Oxide Formation and Aluminum Recovery Mechanism during Secondary Smelting

The remelting, refining, and casting process of aluminum alloys often generate aluminum dross containing primarily oxides and nitrides of aluminum and entrapped metallic aluminum at the surface of the molten metal as a result of reactions within the furnace atmosphere at elevated temperatures. The handling of dross is an expensive but necessary activity during aluminum smelting. Furthermore, the amorphous Al2O3 oxide film formed on the pure molten aluminum surface due to the liquid metal randomly distributed atoms is impermeable to the diffusion of aluminum metal and oxygen. In amorphous materials, there is a low mobility of the charge carriers and an absence of preferred diffusion paths. This film can transform to crystalline Al2O3 by nucleation and grows with time and opportunity. This review discusses the mechanism of oxide formation and the aluminum metal recovery processes.
Functional protection of learning and memory abilities in rats with vascular dementia.

PURPOSE The present study clarified the effects of repetitive transcranial magnetic stimulation (rTMS) in rats with vascular dementia (VaD) and explored the underlying mechanisms. METHODS Two-vessel occlusion was used as a VaD model. Two weeks after carotid artery occlusion, high (5 Hz) or low (1 Hz) frequency rTMS were applied for 10 days. Spatial learning and memory abilities were tested with a Morris water maze. Hippocampal CA1 neurons were histologically examined. The expressions of mammalian target of rapamycin (mTOR) and eukaryotic initiation factor 4E (eIF-4E) in CA1 were detected by western blot, and immunohistochemistry. RESULTS Unlike unlesioned control animals, VaD rats had an impaired morphology of CA1 neurons and a reduced ability of spatial memory. rTMS significantly improved both, the morphology and the learning and memory abilities of VaD rats compared to untreated lesioned rats. Protein expressions of mTOR and eIF-4E in CA1 of VaD rats were lower than in control rats but rTMS significantly increased the expression compared to untreated VaD rats. CONCLUSIONS rTMS promotes recovery of learning and memory abilities of VaD rats. Molecular analysis suggests that the beneficial effect of rTMS may be partly induced by upregulation of protein expressions of mTOR and eIF-4E in CA1.
Label-guided snake for bone segmentation and its application on Medical Rapid Prototyping

Reconstruction of a 3D model from biomedical images is an intensively and extensively demanded technology for a broad variety of medical health care purposes. One of the major issues in these applications is the correctness of tissue segmentation. This paper presents a method for automatic bone segmentation and reconstruction from knee joint CT images. After the potential bone regions are detected by an initial threshold and binary images are labeled, the proposed Label-Guided Snake (L-Snake) based bone segmentation is performed to reconstruct a precise, smooth surface of bone. The experiments show that the proposed method produces robust results in cases where bones are cancellous or very close to each other. The final 3D model is rendered and validated in software and demonstrates its suitability for future Medical Rapid Prototyping and related applications.
Steel Factor Enhances Supraoptimal Antigen-Induced IL-6 Production from Mast Cells via Activation of Protein Kinase C-β1

Ag-triggered mast cell (MC) activation follows a bell-shaped dose-response curve. Reduced activation in response to supraoptimal Ag concentrations is thought to be due to preferential engagement of inhibitory-acting proteins like SHIP1, Lyn, and protein kinase C (PKC)-δ. We show in this study that short-term prestimulation with Steel factor (SF) prevents supraoptimal Ag inhibition, resulting in synergistic MC degranulation and IL-6 secretion. These events are preceded by synergistic phosphorylation/activation of numerous signaling proteins, e.g., Erk, p38, and LAT. However, these effects of prestimulation with SF appear not to be due to reduced engagement of the attenuator SHIP1. Pharmacological analyses suggest that the activation of conventional PKCs is important for this synergy. Specifically, although we found that the conventional PKC inhibitor, Gö6976, likely has some PKC-independent targets in MCs, it led us to further studies that established SF plus Ag-induced IL-6 secretion was severely impaired in PKC-β−/− MCs, but not PKC-α−/− MCs. Thus, PKC-β joins PI3K and Btk as important players in this synergistic MC activation.
Exact renormalization group flow equations for free energies and N-point functions in uniform external fields

We project the Wilson/Polchinski renormalization group equation onto its uniform external field dependent effective free energy and connected Green's functions. The result is a hierarchy of equations which admits a choice of "natural" truncation and closure schemes for nonperturbative approximate solution. In this way approximation schemes can be generated which avoid power series expansions in either fields or momenta. When following one closure scheme the lowest order equation is the mean field approximation, while another closure scheme gives the "local potential approximation. " Extension of these closure schemes to higher orders leads to interesting new questions regarding truncation schemes and the convergence of nonperturbative approximations. One scheme, based on a novel "momentum cluster decomposition" of the connected Green's functions, seems to offer new possibilities for accurate nonperturbative successive approximation.
Modeling and design of antennas for implantable telemetry applications

This paper examines some of the challenges in antenna design and characterization for a device implanted inside the human body. Implantable devices found in Wireless Body Area Networks (WBAN) for healthcare applications such as disease prevention, diagnosis and therapy rely on RF and microwave antennas to transmit reliable information from inside the human body to an external base station. Due to the EM interaction between the implanted antenna and human tissue, these devices experience high energy consumption during transmission with as much as 99% of the radiated energy being lost inside the body leading to higher power consumption by the wireless device, irregularly distributed signals and possible failure to meet minimum range requirements. Modeling of the human body and its impact on antenna design with a concern for occupying minimal volume while providing reliable and efficient energy transfer within a complex and dynamic medium (human body) to ensure a reliable communication link and prolonged battery life will be presented.
T-wave morphology depends on transmural heterogeneity in a high-resolution human left-ventricular wedge model

In this study, we used a in-silico cardiac wedge model with high spatial resolution to evaluate the role of transmural heterogeneity on T-wave morphology. Computer simulations were performed with transmural electrograms recorded with a pacing rate of 60 bpm. QT and TpTe intervals were extracted. The model consisted of i) a human left-ventricular wedge mesh (~4 millions cells); and ii) modified version of the ten Tuscher 2006 cardiac cell model with an added late sodium current. Heterogeneity was generated by changing the spatial distribution of cell types, i.e., M-cells and Epi-cells, across the wedge. Three different cell distribution were used in the simulations: i) random; ii) layers; and iii) layered then gradient. The wedge was stimulated to produce a normal activation propagating from endocardium to epicardium. Our simulations showed that a positive T-wave required the repolarization wave to predominately propagate in opposite direction to the depolarization wave with longer APDs in the endocardial region compared to epicardium. Moreover, QT intervals increased with the amount of M-cells in the wedge model while TpTe intervals were dependent on the transmural heterogeneity. In summary, we showed that cell distributions highly affect both repolarization and T-wave morphology parameters in a high-resolution human wedge model.
Fourteen-Member Macrolides Promote the Phosphatidylserine Receptor-Dependent Phagocytosis of Apoptotic Neutrophils by Alveolar Macrophages

ABSTRACT An inflammation of the airway of patients with diffuse panbronchiolitis (DPB), is characterized by dense neutrophil infiltration. Resolution of the inflammation can be achieved by the removal of apoptotic neutrophils by human alveolar macrophages (AM) without liberating neutrophil proteases in the airway. To understand clinical efficacy for the treatment of DPB by 14- or 15-member macrolides, their effects on the phagocytosis of apoptotic neutrophils by AM were examined. Treatment of AM with erythromycin (ERY) or clarithromycin at clinically achievable levels significantly increased the levels of phagocytosis of apoptotic neutrophils. A serum factor was not essential for the enhancement by these 14-member macrolides. Of the antibiotics tested, these effects were specific for the 14-member macrolides and a 15-member macrolide, azithromycin, but not for the 16-member macrolides, clindamycin or β-lactam antibiotics. The enhanced phagocytosis of apoptotic neutrophils by ERY had no effect on the levels of interleukin-8 or tumor necrosis factor alpha production by lipopolysaccharide-stimulated AM after phagocytosis of the apoptotic neutrophils. The increased phagocytosis of apoptotic neutrophils by ERY was also found to be phosphatidylserine receptor-dependent for AM. These data indicate a novel anti-inflammatory action of 14-member and 15-member macrolides, and suggest that such antibiotics achieve clinical efficacy for patients with DPB, in part, through enhancing the nonphlogistic phagocytosis of apoptotic neutrophils by AM.
Mutational Profile of GNAQ Q209 in Human Tumors

Background Frequent somatic mutations have recently been identified in the ras-like domain of the heterotrimeric G protein α-subunit (GNAQ) in blue naevi 83%, malignant blue naevi (50%) and ocular melanoma of the uvea (46%). The mutations exclusively affect codon 209 and result in GNAQ constitutive activation which, in turn, acts as a dominant oncogene. Methodology To assess if the mutations are present in other tumor types we performed a systematic mutational profile of the GNAQ exon 5 in a panel of 922 neoplasms, including glioblastoma, gastrointestinal stromal tumors (GIST), acute myeloid leukemia (AML), blue naevi, skin melanoma, bladder, breast, colorectal, lung, ovarian, pancreas, and thyroid carcinomas. Principal Findings We detected the previously reported mutations in 6/13 (46%) blue naevi. Changes affecting Q209 were not found in any of the other tumors. Our data indicate that the occurrence of GNAQ mutations display a unique pattern being present in a subset of melanocytic tumors but not in malignancies of glial, epithelial and stromal origin analyzed in this study.
Stability Analysis of Time Stepping for Prolonged Plasma Fluid Simulations

The Hasegawa-Wakatani system of equations may be used to predict and study the behavior of plasma flow. Stability analysis of the flow requires results over prolonged time series, which places a great strain on computational resources. Results can only be achieved for a wide choice of parameters by using numerical methods that allow long time steps and do not pollute the results with numerical instabilities. The report presents an analysis of several linear multistep methods and concludes that much of the understanding of the stability of linear systems also applies to the study of nonlinear problems such as the Hasegawa-Wakatani system of equations. In particular, methods such as the backward differentiation formulas should be used with the stiff systems generated by the discrete formulation of the Hasegawa-Wakatani system of equations.
A Constant Factor Approximation Algorithm for Generalized Min-Sum Set Cover

Consider the following generalized min-sum set cover or multiple intents re-ranking problem proposed by Azar et al. (STOC 2009). We are given a universe of elements and a collection of subsets, with each set S having a covering requirement of K(S). The objective is to pick one element at a time such that the average covering time of the sets is minimized, where the covering time of a set S is the first time at which K(S) elements from it have been selected. There are two well-studied extreme cases of this problem: (i) when K(S) = 1 for all sets, we get the min-sum set cover problem, and (ii) when K(S) = |S| for all sets, we get the minimum-latency set cover problem. Constant factor approximations are known for both these problems. In their paper, Azar et al. considered the general problem and gave a logarithmic approximation algorithm for it. In this paper, we improve their result and give a simple randomized constant factor approximation algorithm for the generalized min-sum set cover problem.
Co-Located Collaborative Decision Making with Access Control on Large Single Display

When porting single user applications to a co-located collaborative large single display environment for a group of users, access control becomes an important issue. By taking a simple, single user game, Reversi, and extending it to become a collaborative applicaiton on a single large display, we examine two methods of access control when a group of individuals attempt to defeat the computer as a team. The first scenario allows only the leader of the team to make moves, while the second allows all participating users to make moves. Analyzing two factors, speed and score, the study shows that when all members of the team have access to make decisions, the collaborative effort will perform better with respects to time and better decisions made. Author
Multi-ontology matchmaker

The rapid development and the large number of existing web services have led to a demand for a discovery mechanism. Researchers have developed Matchmakers to match web service requesters and providers. Current Matchmakers are adequate when locating web services that use the same ontology but they do not support the matching of semantic web services that use different ontologies. This paper introduces a Matchmaker which locates web services that use different ontologies. The Matchmaker algorithm, which incorporates a means of distinguishing different ontologies, is presented, together with the overall architecture of the Matchmaker engine.
Explaining Prolog Based Expert Systems Using a Layered Meta-Interpreter

This paper presents an improved method of explaining Prolog-based expert systems. The key idea is to make explicit failures during the computation. This allows the integrated explanation in a single interpreter of both successful and failed computations. It also allows rules containing cuts to be effectively explained. Furthermore, the explanation system is interactive, and allows full explanation of both successful and failed partial computations. We discuss in some detail a two-layer meta-interpreter which is at the heart of the system.
A highly collimated, extremely high velocity outflow in Taurus

We present the first case of a highly collimated, extremely high velocity bipolar outflow in Taurus. It is powered by the low-luminosity (0.4 $L_\odot$) source IRAS 04166+2706 and contains gas accelerated up to 50 km s -1 with respect to the ambient cloud both toward the blue and the red (uncorrected for projection). At the highest velocities, the outflow collimation factor exceeds 20, and the gas displays a very high degree of spatial symmetry. This very fast gas presents multiple maxima, and most likely arises from the acceleration of ambient material by a time-variable jet-like stellar wind. When scaled for luminosity, the outflow parameters of IRAS 04166 are comparable to those of other extremely high velocity outflows like L1448, indicating that even the very quiescent star-formation mode of Taurus can produce objects powering very high energy flows ($L_{\rm mec}/L_* > 0.15$).