Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsteady MHD Non-Newtonian Heat Transfer Nanofluids with Entropy Generation Analysis

Abstract A theoretical study of unsteady magnetohydrodynamic boundary layer stagnation point flow, heat and mass transfer of a second grade electrically-conducting nanofluid from a horizontal stretching sheet with thermal slip and second order slip velocity effects is presented. The Buongiorno formulation is employed for nanofluids and in addition the no-flux nanoparticle boundary condition is also considered. The appropriate similarity transformations are applied to convert the governing equations into the system of nonlinear partial differential equations, which is solved by using homotopy analysis method. Entropy generation and Bejan number have also been evaluated for the effects of magnetic parameter, Reynolds number and slip parameter in non-Newtonian (second-grade) time-dependent flow. The computations show that skin friction coefficient and entropy generation number increase with an increment in magnetic parameter whereas Bejan number decreases with it. Local Nusselt number decreases with an increase in the value of Eckert number (viscous dissipation) and thermal slip whereas the converse behaviour is captured for velocity parameter. The work is relevant to magnetohydrodynamic nanomaterials processing.
A Soft computing Optimization based Two Ware-House Inventory Model for Deteriorating Items with shortages using Genetic Algorithm

this paper a two warehouse inventory model for deteriorating items is considered under assumption that the Inventory cost (including holding cost and deterioration cost) in RW (Rented Warehouse) is higher than those in OW (Owned Warehouse) due to better preservation facilities in RW. The demand and holding cost, both are taken variable. Shortages are allowed in the OW and a fraction of shortages backlogged at the next replenishment cycle . This paper mainly dealt with deteriorating items with time dependent demand and variable holding cost which is constant for a definite time period and after that it increases according to length of ordering cycle in RW and remains constant in OW. Transportation cost is taken to be negligible and goods are transported on the basis of bulk release pattern. A genetic algorithm with varying population size is used to solve the model. In this GA a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. A numerical example is presented to illustrate the model and sensitivity is performed for a parameter keeping rest unchanged. Keywordswarehouses, Instantaneous deterioration, Time- dependent Demand, Variable holding cost, shortages and Genetic Algorithm
Human natural resistance-associated macrophage protein: cDNA cloning, chromosomal mapping, genomic organization, and tissue-specific expression

Natural resistance to infection with unrelated intracellular parasites such as Mycobacteria, Salmonella, and Leishmania is controlled in the mouse by a single gene on chromosome 1, designated Bcg, Ity, or Lsh. A candidate gene for Bcg, designated natural resistance-associated macrophage protein (Nramp), has been isolated and shown to encode a novel macrophage-specific membrane protein, which is altered in susceptible animals. We have cloned and characterized cDNA clones corresponding to the human NRAMP gene. Nucleotide and predicted amino acid sequence analyses indicate that the human NRAMP polypeptide encodes a 550-amino acid residue membrane protein with 10-12 putative transmembrane domains, two N-linked glycosylation sites, and an evolutionary conserved consensus transport motif. Identification of genomic clones corresponding to human NRAMP indicates that the gene maps to chromosome 2q35 within a group of syntenic loci conserved with proximal mouse 1. The gene is composed of at least 15 exons, with several exons encoding discrete predicted structural domains of the protein. These studies have also identified an alternatively spliced exon encoded by an Alu element present within intron 4. Although this novel exon was found expressed in vivo, it would introduce a termination codon in the downstream exon V, resulting in a severely truncated protein. Northern blot analyses indicate that NRAMP mRNA expression is tightly controlled in a tissue-specific fashion, with the highest sites of expression being peripheral blood leukocytes, lungs, and spleen. Additional RNA expression studies in cultured cells identified the macrophage as a site of expression of human NRAMP and indicated that increased expression was correlated with an advanced state of differentiation of this lineage.
Orthogonal vector field-based control for a multi-robot system circumnavigating a moving target in 3D

We address the problem of multiple networked robots circumnavigating a dynamic target in a three-dimensional setting. A distributed cooperative control strategy is proposed that guarantees convergence of the robots to a circular formation with prescribed radius and inter-agent distances around a moving target. The circular formation is constrained to evolve on a plane of motion that is fixed in orientation but translates along the target trajectory. The control design is carried out using three potential functions, each of which defines a control objective, with gradient fields that are orthogonal to each other. The novelty in this approach lies in the orthogonality of the vector fields, which decouples the control objectives and ensures asymptotic convergence to the desired formation, subject to some mild initial condition constraints. The convergence properties are analyzed using Lyapunov-based methods, and the control strategy is demonstrated through numerical simulations and experiments on a robotic test bed.
The scrambler attack: A robust physical layer attack on location privacy in vehicular networks

Vehicular networks provide the basis for a wide range of both safety and non-safety applications. One of the key challenges for wide acceptance is to which degree the drivers' privacy can be protected. The main technical privacy protection mechanism is the use of changing identifiers (from MAC to application layer), so called pseudonyms. The effectiveness of this approach, however, is clearly reduced if specific characteristics of the physical layer (e.g., in the transmitted signal) reveal the link between two messages with different pseudonyms. In this paper, we present such a fingerprinting technique: the scrambler attack. In contrast to other physical layer fingerprinting methods, it does not rely on potentially fragile features of the channel or the hardware, but exploits the transmitted scrambler state that each receiver has to derive in order to decode a packet, making this attack extremely robust. We show how the scrambler attack bypasses the privacy protection mechanism of state-of-the-art approaches and quantify the degradation of drivers' location privacy with an extensive simulation study. Based on our results, we identify additional technological requirements in order to enable privacy protection mechanisms on a large scale.
Chinese Named Entity Recognition with Graph-based Semi-supervised Learning Model

Named entity recognition (NER) plays an important role in the NLP literature. The traditional methods tend to employ large annotated corpus to achieve a high performance. Different with many semi-supervised learning models for NER task, in this paper, we employ the graph-based semi-supervised learning (GBSSL) method to utilize the freely available unlabeled data. The experiment shows that the unlabeled corpus can enhance the state-of-theart conditional random field (CRF) learning model and has potential to improve the tagging accuracy even though the margin is a little weak and not satisfying in current experiments.
Development of Self-Calibrating A\/D Converters

Until well after I thought of the self-calibration idea, I believed I was the first one to have recognized the property of the binary weighted capacitor array and exploited it to measure capacitor mismatch - nothing remotely similar had turned up in any of the circuit-type journal or conference publications. I discovered later, to my dismay, McCreary had thought of the same principle and had applied it to characterize capacitor mismatch characteristics [9]. This had been published in IEEE Transactions on Instrumentation and Measurements in 1979 - a journal I had not thought was relevant to data converters. Of course, McCreary used the principle for capacitor matching characterization, not for calibrating ADC's, but he recognized the important symmetry in a binary weighted capacitor array and used it to measure capacitor mismatch. Along with his pioneering work in charge-redistribution ADC's, his work laid the foundation for the self-calibrating ADC work presented here. The self-calibrating ADC improved its own accuracy without a factory calibration or a golden standard for the first time. Many other calibration methods followed for various different types of ADC's including successive-approximation, pipeline, and delta-sigma ADC's, ultimately finding applications in other analog circuits in the form of now popular digitally-assisted analog circuits.
Supersymmetric states of N=4 Yang-Mills from giant gravitons

Mikhailov has constructed an infinite family of 1 BPS D3-branes in AdS5 × S 5 . We regulate Mikhailov's solution space by focussing on finite dimensional submani- folds. Our submanifolds are topologically complex projective spaces with symplectic form cohomologically equal to 2πN times the Fubini-Study Kahler class. Upon quan- tization and removing the regulator we find the Hilbert Space of N noninteracting Bose particles in a 3d Harmonic oscillator, a result previously conjectured by Beasley. This Hilbert Space is isomorphic to the classical chiral ring of 1 BPS states in N = 4 Yang-Mills theory. We view our result as evidence that the spectrum of 1 BPS states in N = 4 Yang Mills theory, which is known to jump discontinuously from zero to infinitesimal coupling, receives no further renormalization at finite values of the 't Hooft coupling.
A Comparative Study into Architecture-Based Safety Evaluation Methodologies Using AADL's Error Annex and Failure Propagation Models

Early quality evaluation and support for decisions that affect quality characteristics are among the key incentives to formally specify the architecture of a software intensive system. The Architecture Analysis and Description Language (AADL) with its error annex is a new and promising architecture modeling language that supports analysis of safety and other dependability properties. This paper reviews the key concepts that are introduced by the error annex, and compares it to the existing safety evaluation techniques regarding its ability in providing modeling, process and tool support. Based on this review and the comparison, its strengths and weaknesses are identified and possible improvements for the model-driven safety evaluation methodology based on AADLpsilas error annex are highlighted.
A taxonomy for software change impact analysis

Most software is accompanied by frequent changes, whereas the implementation of a single change can affect many different parts of the system. Approaches for Impact Analysis have been developed to assist developers with changing software. However, there is no solid framework for classifying and comparing such approaches, and it is therefore hard to find a suitable technique with minimal effort. The contribution of this paper is a taxonomy for Impact Analysis, based on a literature review conducted on related studies, to overcome this limitation. The presented classification criteria are more detailed and precise than those proposed in previous work, and possible candidates for all criteria are derived from studied literature. We classify several approaches according to our taxonomy to illustrate its applicability and the usefulness of our criteria. The research presented in this paper prepares the ground for a comprehensive survey of Software Change Impact Analysis.
Developmental coronary maturation is disturbed by aberrant cardiac vascular endothelial growth factor expression and Notch signalling.

AIMS Currently, many potential cardiac revascularization therapies target the vascular endothelial growth factor (VEGF) pathway, with variable success. Knowledge regarding the role of the VEGF/Notch/ephrinB2 cascade in (ab)normal coronary development will provide information on the subtle balance of VEGF signalling in coronary maturation and might enhance our therapeutic possibilities. METHODS AND RESULTS The effect of VEGF isoforms on coronary development was explored in vivo using immunohistochemistry and RT-qPCR on Vegf120/120 mouse embryos solely expressing VEGF120. In vitro, human arterial coronary endothelial cells were treated with VEGF121 or VEGF165 upon which RT-qPCR was performed. In vivo, mutant coronary arterial endothelium showed a decrease in protein expression of arterial markers such as cleaved Notch1, Delta-like4, and ephrinB2 concomitant with an increase of venous markers such as chicken ovalbumin upstream promoter transcription factor II. The venous endothelium showed the opposite effect, which was confirmed on the mRNA level. In vitro, mRNA expression of arterial markers highly depended on the VEGF isoform used, with VEGF165 having the strongest effect. Also, coronary arteriogenesis was anomalous in the mouse embryos with decreased arterial and increased venous medial development as shown by staining for smooth muscle alpha-actin, Delta-like1, and Notch3. CONCLUSION We demonstrate that VEGF isoform-related spatiotemporal cardiac alterations in the VEGF/Notch/ephrinB2 cascade lead to disturbed coronary development. This knowledge can contribute to optimizing therapies targeting VEGF signalling by enabling balancing between angiogenesis and vascular maturation.
Identification and Structural Characterization of I84C and I84A Mutations That Are Associated with High-Level Resistance to Human Immunodeficiency Virus Protease Inhibitors and Impair Viral Replication

ABSTRACT Two novel human immunodeficiency virus protease mutations, I84C and I84A, were identified in patient isolates. The mutants with I84C displayed high-level resistance (median, at least 56-fold) to nelfinavir and saquinavir, but the majority remained susceptible to lopinavir. In contrast, isolates with the I84A mutation exhibited ≥33-fold median increased levels of resistance to nelfinavir, indinavir, amprenavir, ritonavir, lopinavir, saquinavir, and atazanavir. Isolates with the I84A or I84C mutation tended to be more resistant than the isolates with the I84V mutation. Modeling of the structure of the mutant proteases indicated that the I84V, I84C, and I84A mutations all create unoccupied volume in the active site, with I84A introducing the greatest change in the accessible surface area from that of the wild-type structure.
Evaluating Salience Representations for Cross-modal Retrieval of Western Classical Music Recordings

In this paper, we consider a cross-modal retrieval scenario of Western classical music. Given a short monophonic musical theme in symbolic notation as query, the objective is to find relevant audio recordings in a database. A major challenge of this retrieval task is the possible difference in the degree of polyphony between the monophonic query and the music recordings. Previous studies for popular music addressed this issue by performing the cross-modal comparison based on predominant melodies extracted from the recordings. For Western classical music, however, this approach is problematic since the underlying assumption of a single predominant melody is often violated. Instead of extracting the melody explicitly, another strategy is to perform the cross-modal comparison directly on the basis of melody-enhanced salience representations. As the main contribution of this paper, we evaluate several conceptually different salience representations for our cross-modal retrieval scenario. Our extensive experimental results, which have been made available on a website, comprise more than 2000 musical themes and 100 hours of audio recordings.
Developmentally Essential Protein Flightless I Is a Nuclear Receptor Coactivator with Actin Binding Activity

ABSTRACT Hormone-activated nuclear receptors (NR) activate transcription by recruiting multiple coactivator complexes to the promoters of target genes. One important coactivator complex includes a p160 coactivator (e.g., GRIP1, SRC-1, or ACTR) that binds directly to activated NR, the histone acetyltransferase p300 or CBP, and the arginine-specific histone methyltransferase CARM1. We previously demonstrated that the coactivator function of CARM1 depends both on the methyltransferase activity and on additional unknown proteins that bind to CARM1. In this study a yeast two-hybrid screen for proteins that bind CARM1 identified the protein Flightless I (Fli-I), which has essential roles in Drosophila and mouse development. Fli-I bound to CARM1, GRIP1, and NRs and cooperated synergistically with CARM1 and GRIP1 to enhance NR function. Fli-I bound poorly to and did not cooperate with PRMT1, a CARM1-related protein arginine methyltransferase that also functions as an NR coactivator. The synergy between GRIP1, CARM1, and Fli-I required the methyltransferase activity of CARM1. The C-terminal AD1 (binding site for p300/CBP) and AD2 (binding site for CARM1) activation domains of GRIP1 contributed to the synergy but were less stringently required than the N-terminal region of GRIP1, which is the binding site for Fli-I. Endogenous Fli-I was recruited to the estrogen-regulated pS2 gene promoter of MCF-7 cells in response to the hormone, and reduction of endogenous Fli-I levels by small interfering RNA reduced hormone-stimulated gene expression by the endogenous estrogen receptor. A fragment of Fli-I that is related to the actin binding protein gelsolin enhanced estrogen receptor activity, and mutations that reduced actin binding also reduced the coactivator function of this Fli-I fragment. These data suggest that Fli-I may facilitate interaction of the p160 coactivator complex with other coactivators or coactivator complexes containing actin or actin-like proteins.
Detection of SINR Interference in MIMO Transmission Using Power Allocation

Low-complexity and reduced SINR interference cancellation of MIMO systems has attracted recent research attention. Under the bit error rate minimization criterion, an efficient detection ordering scheme for ordered successive interference cancellation detector is achieved for multiple antenna (MIMO) systems using power allocation (PA) scheme. In this paper, we derive a relation that makes the channel gains converge to their geometric mean from the convexity of the Q-function. Based on this approach, first, we design the fixed ordering algorithm, for which the geometric mean is used for a constant threshold. Further, the performance can be improved by modifying the scheme employing adaptive thresholds is developed using the correlation among the ordering results. In the proposed method, theoretical analysis and simulation results show that the ordering schemes using QR-decomposition reduce the computational complexity compared to the conventional method, and also bit-error-rate (BER) performance can be improved.
Isoprene and acetone concentration profiles during exercise on an ergometer

A real-time recording setup combining exhaled breath volatile organic compound (VOC) measurements by proton transfer reaction-mass spectrometry (PTR-MS) with hemodynamic and respiratory data is presented. Continuous automatic sampling of exhaled breath is implemented on the basis of measured respiratory flow: a flow-controlled shutter mechanism guarantees that only end-tidal exhalation segments are drawn into the mass spectrometer for analysis. Exhaled breath concentration profiles of two prototypic compounds, isoprene and acetone, during several exercise regimes were acquired, reaffirming and complementing earlier experimental findings regarding the dynamic response of these compounds reported by Senthilmohan et al (2000 Redox Rep. 5 151–3) and Karl et al (2001 J. Appl. Physiol. 91 762–70). While isoprene tends to react very sensitively to changes in pulmonary ventilation and perfusion due to its lipophilic behavior and low Henry constant, hydrophilic acetone shows a rather stable behavior. Characteristic (median) values for breath isoprene concentration and molar flow, i.e., the amount of isoprene exhaled per minute are 100 ppb and 29 nmol min−1, respectively, with some intra-individual day-to-day variation. At the onset of exercise breath isoprene concentration increases drastically, usually by a factor of ∼3–4 within about 1 min. Due to a simultaneous increase in ventilation, the associated rise in molar flow is even more pronounced, leading to a ratio between peak molar flow and molar flow at rest of ∼11. Our setup holds great potential in capturing continuous dynamics of non-polar, low-soluble VOCs over a wide measurement range with simultaneous appraisal of decisive physiological factors affecting exhalation kinetics. In particular, data appear to favor the hypothesis that short-term effects visible in breath isoprene levels are mainly caused by changes in pulmonary gas exchange patterns rather than fluctuations in endogenous synthesis.
Multi-Value Rule Sets

We present the Multi-vAlue Rule Set (MARS) model for interpretable classification with feature efficient presentations. MARS introduces a more generalized form of association rules that allows multiple values in a condition. Rules of this form are more concise than traditional single-valued rules in capturing and describing patterns in data. MARS mitigates the problem of dealing with continuous features and high-cardinality categorical features faced by rule-based models. Our formulation also pursues a higher efficiency of feature utilization, which reduces the cognitive load to understand the decision process. We propose an efficient inference method for learning a maximum a posteriori model, incorporating theoretically grounded bounds to iteratively reduce the search space to improve search efficiency. Experiments with synthetic and real-world data demonstrate that MARS models have significantly smaller complexity and fewer features, providing better interpretability while being competitive in predictive accuracy. We conducted a usability study with human subjects and results show that MARS is the easiest to use compared with other competing rule-based models, in terms of the correct rate and response time. Overall, MARS introduces a new approach to rule-based models that balance accuracy and interpretability with feature-efficient representations.