Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixed Finite Element Methods for the Fully Nonlinear Monge-Ampère Equation Based on the Vanishing Moment Method

This paper studies mixed finite element approximations of the viscosity solution to the Dirichlet problem for the fully nonlinear Monge-Ampere equation $\det(D^2u^0)=f\,(>0)$ based on the vanishing moment method which was proposed recently by the authors in [X. Feng and M. Neilan, J. Scient. Comp., DOI 10.1007/s10915-008-9221-9, 2008]. In this approach, the second-order fully nonlinear Monge-Ampere equation is approximated by the fourth order quasilinear equation $-\varepsilon\Delta^2 u^\varepsilon + \det{D^2u^\varepsilon}=f$. It was proved in [X. Feng, Trans. AMS, submitted] that the solution $u^\varepsilon$ converges to the unique convex viscosity solution $u^0$ of the Dirichlet problem for the Monge-Ampere equation. This result then opens a door for constructing convergent finite element methods for the fully nonlinear second-order equations, a task which has been impracticable before. The goal of this paper is threefold. First, we develop a family of Hermann-Miyoshi-type mixed finite element methods for approximating the solution $u^\varepsilon$ of the regularized fourth-order problem, which computes simultaneously $u^\varepsilon$ and the moment tensor $\sigma^\varepsilon:=D^2u^\varepsilon$. Second, we derive error estimates, which track explicitly the dependence of the error constants on the parameter $\varepsilon$, for the errors $u^\varepsilon-u^\varepsilon_h$ and $\sigma^0-\sigma_h^\varepsilon$. Finally, we present a detailed numerical study on the rates of convergence in terms of powers of $\varepsilon$ for the error $u^0-u_h^\varepsilon$ and $\sigma^\varepsilon-\sigma_h^\varepsilon$, and numerically examine what is the “best” mesh size $h$ in relation to $\varepsilon$ in order to achieve these rates. Due to the strong nonlinearity of the underlying equation, the standard perturbation argument for error analysis of finite element approximations of nonlinear problems does not work for the problem. To overcome the difficulty, we employ a fixed point technique which strongly relies on the stability of the linearized problem and its mixed finite element approximations.
SOFT IP CUSTOMIZATION MODELS BASED ON HIGH-LEVEL ABSTRACTIONS

System-on-Chip (SoC) design raises an abstraction level in hardware (HW) design beyond a domain language specification. This requires the introduction and adoption of high-level analysis and specification methods that provide reusability, layericity, orthogonality, heterogeneity and customizability for HW design. HW design has many levels of abstraction. The transition between these levels can be described using a concept of design process. As there may be many representation and design methods for a designer to choose from, while implementing a certain design process, we describe several Design Flow Models aimed at implementing customization in soft IP-based HW design. These models apply several concepts taken from software engineering (object-oriented and pattern-based design, metaprogramming, parsing, and markup languages) to HW design.
Debugging multi-agent systems using design artifacts: the case of interaction protocols

Debugging multi-agent systems (which are concurrent, distributed, and consist of complex components) is difficult, yet crucial. We propose that the debugging process can be improved by following an agent-oriented design methodology, and then using the design artifacts in the debugging phase. We present an example of this scheme which uses interaction protocols to debug agent interaction. Interaction protocols are specified using AUML and are translated to Petri nets. The debugger uses the Petri nets to monitor conversations and to provide precise and informative error messages when protocols aren't correctly followed by the agents.
Identification and characterization of Streptomyces flavogriseus NJ-4 as a novel producer of actinomycin D and holomycin

This paper is the first public report that Streptomyces flavogriseus can produce both actinomycin D and holomycin. The actinomycete strain NJ-4 isolated from the soil of Nanjing Agricultural University was identified as S. flavogriseus. This S. flavogriseus strain was found for the first time to produce two antimicrobial compounds that were identified as actinomycin D and holomycin. GS medium, CS medium and GSS medium were used for the production experiments. All three media supported the production of actinomycin D, while holomycin was detected only in GS medium and was undetectable by HPLC in the CS and GSS media. The antimicrobial activity against B. pumilus, S. aureus, Escherichia coli, F. moniliforme, F. graminearum and A. niger was tested using the agar well diffusion method. Actinomycin D exhibited strong antagonistic activities against all the indicator strains. Holomycin exhibited strong antagonistic activities against B. pumilus, S. aureus and E. coli and had antifungal activity against F. moniliforme and F. graminearum but had no antifungal activity against A. niger. The cell viability was determined using an MTT assay. Holomycin exhibited cytotoxic activity against A549 lung cancer cells, BGC823 gastric cancer cells and HepG2 hepatocellular carcinoma cells. The yield of actinomycin D from S. flavogriseus NJ-4 was 960 mg/l. S. flavogriseus NJ-4 exhibits a distinct capability and has the industrial potential to produce considerable yields of actinomycin D under unoptimized conditions.
Effects of repetitive magnetic stimulation on the growth of primarily cultured hippocampus neurons in vitro and their expression of iron-containing enzymes

Background: The mechanism of action of repetitive transcranial magnetic stimulation (rTMS) involves the generation of neuronal and action potentials utilizing induced currents in time-varying magnetic fields. However, the long-lasting and effective biological impact of magnetic stimulation does not appear to be completely explained by the transient magnetic field pulses. In this context, we hypothesized magnetic stimulation may affect the expression of iron-containing enzymes in neurons, mediating the long-lasting biological effects associated with this stimulus. Methods: Primarily cultured hippocampus neurons from SD rats were used as the cell model in this study. These were randomly divided into control, sham, and magnetic stimulation groups to probe into the effect of the magnetic field directly. The latter group received 40%, 60%, and 100% maximal stimulator output Tesla (1.68, 2.52, and 4.2 T) with low-frequency rTMS (1 Hz). The expression of iron-containing enzymes (catalase and aconitase) and non-ferrous enzymes (protein kinase A) was measured with Western blotting and ELISA. Results: The survival rates of neurons in the 40%T and 60%T groups were significantly increased in comparison to the controls (P<0.05), while those in the 100%T group showed cell damage, with slightly disturbed neurite connections and decreased survival rate. Furthermore, catalase and aconitase expression was higher in all of the stimulated groups in comparison to controls (P<0.05). On the other hand, the expression of the iron-containing enzymes decreased in the 100%T group in comparison with the 40%T and 60%T groups (P<0.05). Meanwhile, the expression of protein kinase A was not significantly increased in the groups which underwent magnetic stimulation. Conclusion: rTMS may increase the expression of ferrous enzymes but does not have a strong effect on non-ferrous enzymes. Excessive intensity of magnetic stimulation may reduce neuronal survival rate and affect the expression of iron-containing enzymes. The mechanism underlying the lasting effect of rTMS may be related to the increase of ferriferous expression induced by magnetic stimulation, with a clear correlation with stimulation intensity.
INVHOGEN: a database of homologous invertebrate genes

Classification of proteins into families of homologous sequences constitutes the basis of functional analysis or of evolutionary studies. Here we present INVertebrate HOmologous GENes (INVHOGEN), a database combining the available invertebrate protein genes from UniProt (consisting of Swiss-Prot and TrEMBL) into gene families. For each family INVHOGEN provides a multiple protein alignment, a maximum likelihood based phylogenetic tree and taxonomic information about the sequences. It is possible to download the corresponding GenBank flatfiles, the alignment and the tree in Newick format. Sequences and related information have been structured in an ACNUC database under a client/server architecture. Thus, complex selections can be performed. An external graphical tool (FamFetch) allows access to the data to evaluate homology relationships between genes and distinguish orthologous from paralogous sequences. Thus, INVHOGEN complements the well-known HOVERGEN database. The databank is available at .
Current initiatives in proteomics research: the plant perspective

The recent upsurge in structural genomics is leading to the accumulation of a huge wealth of literature on nucleotide sequences. After the nucleotide sequence of a given stretch of DNA is obtained (by manual or robotic methods), the next step is to use some software program to distinguish the possible open reading frames in the thick of sequences. However, the acid test, whether the new sequence corresponds to any functionality in terms of transcription and translation is to identify the protein which it encodes. Functional genomics and proteomics are the buzzwords in modern-day genomics. The science of proteomics is a possible approach to relate the skeletal nucleotide sequence information to functional attributes of the cell. The identification and isolation of novel genes with potential biotechnological applications warrant that genomics and proteomics must go hand in hand. Three major steps in proteome analysis are the separation of complex protein mixtures by two-dimensional protein gel electrophoresis (2D), characterization of the separated proteins by mass spectrometer (MS) and database searching. The power of 2D is such that it allows even minor changes in gene expression caused by internal or external cues to be effectively scored. Most proteins resolved by 2D have high purity, which can facilitate their identification by MS. In recent years, methods for automated proteomics based on incorporation of new ideas in both hardware and software development have been optimized to a great deal. We discuss the progress and applications of the proteomics science, with special reference to plants.
A Role for the Rho-p160 Rho Coiled-Coil Kinase Axis in the Chemokine Stromal Cell-Derived Factor-1α-Induced Lymphocyte Actomyosin and Microtubular Organization and Chemotaxis1

The possible involvement of the Rho-p160ROCK (Rho coiled-coil kinase) pathway in the signaling induced by the chemokine Stromal cell-derived factor (SDF)-1α has been studied in human PBL. SDF-1α induced activation of RhoA, but not that of Rac. RhoA activation was followed by p160ROCK activation mediated by RhoA, which led to myosin light chain (MLC) phosphorylation, which was dependent on RhoA and p160ROCK activities. The kinetics of MLC activation was similar to that of RhoA and p160ROCK. The role of this cascade in overall cell morphology and functional responses to the chemokine was examined employing different chemical inhibitors. Inhibition of either RhoA or p160ROCK did not block SDF-1α-induced short-term actin polymerization, but induced the formation of long spikes arising from the cell body, which were found to be microtubule based. This morphological change was associated with an increase in microtubule instability, which argues for an active microtubule polymerization in the formation of these spikes. Inhibition of the Rho-p160ROCK-MLC kinase signaling cascade at different steps blocked lymphocyte migration and the chemotaxis induced by SDF-1α. Our results indicate that the Rho-p160ROCK axis plays a pivotal role in the control of the cell shape as a step before lymphocyte migration toward a chemotactic gradient.
A wide-angle view at iterated shrinkage algorithms

Sparse and redundant representations − an emerging and powerful model for signals − suggests that a data source could be described as a linear combination of few atoms from a pre-specified and over-complete dictionary. This model has drawn a considerable attention in the past decade, due to its appealing theoretical foundations, and promising practical results it leads to. Many of the applications that use this model are formulated as a mixture of l2-lp (p ≤ 1) optimization expressions. Iterated Shrinkage algorithms are a new family of highly effective numerical techniques for handling these optimization tasks, surpassing traditional optimization techniques. In this paper we aim to give a broad view of this group of methods, motivate their need, present their derivation, show their comparative performance, and most important of all, discuss their potential in various applications.
High-Performance Single-Crystal-Like Nanowire Poly-Si TFTs With Spacer Patterning Technique

In this letter, high-performance single-crystal-like nanowire poly-Si TFTs with simple spacer patterning technique were demonstrated and characterized. Due to the nanoscale dimension formed by spacer patterning technique, each nanowire is easily transformed within one crystalline grain of the standard sequential-lateral-solidification (SLS) poly-Si film with the regularly arranged grains and thus performed with a single-crystal like device channel. Due to the high-crystallinity channel, together with the tri-gated structure, the fabricated devices revealed good device integrity of high field-effect mobility of 477 cm2/V · s and good ON/OFF current ratio of 1.07 × 108.
Optimal and Suboptimal Power Allocation Schemes for OFDM-based Cognitive Radio Systems

In this paper, we investigate an optimal power loading algorithm for an OFDM-based cognitive radio (CR) system. The downlink transmission capacity of the CR user is thereby maximized, while the interference introduced to the primary user (PU) remains within a tolerable range. We also propose two suboptimal loading algorithms that are less complex. We also study the effect of a subcarrier nulling mechanism on the performance of the different algorithms under consideration. The performance of the optimal and suboptimal schemes is compared with the performance of the classical power loading algorithms, e.g., water-filling and uniform power but variable rate loading schemes that are used for conventional OFDM-based systems. Presented numerical results show that for a given interference threshold, the proposed optimal scheme allows CR base station (BS) to transmit more power in order to achieve a higher transmission rate than the classical loading algorithms. These results also show that although the proposed suboptimal schemes have certain degradation in performance compared to the optimal scheme, they outperform the classical loading algorithms. We also present numerical results for nulling mechanism. Finally, we investigate the effect of imperfect channel gain information at the transmitter.
Tied Normal Variance–Mean Mixtures for Linear Score Calibration

A speaker verification system decides whether two voice segments belong to the same speaker based on a threshold. An optimal threshold can be set if the recognition scores are well calibrated, i.e., they represent Log–Likelihood Ratios. Logistic Regression (LogReg) is a standard approach for score calibration. While training this discriminative model requires labeled scores, Gaussian and non–Gaussian generative calibration models have been recently proposed. They not only have similar or better performance with respect to LogReg, but also allow for unsupervised or semi–supervised training of the models.The goal of this work is to extend these models. In particular, we show that normal variance–mean mixture distributions are able to model well–calibrated non–Gaussian distributed scores, provided that their parameters for the target and non–target score distributions are properly tied. As for the Gaussian case, a linear calibration model can then be estimated by computing Maximum Likelihood estimates of the distributions parameters and of the score transformation. The quality of all these approaches has been compared on a dataset of segments of variable duration obtained by cutting the NIST 2010 evaluation test data.
Ribosomal Mutations in Arcanobacterium pyogenes Confer a Unique Spectrum of Macrolide Resistance

ABSTRACT Four macrolide-resistant Arcanobacterium pyogenes isolates contained A2058T, A2058G, or C2611G (Escherichia coli numbering) mutations in their 23S rRNA genes. While these mutations conferred resistance to erythromycin, oleandomycin, and spiramycin, they did not confer resistance to tylosin.
A Leakage-Based Beamforming Algorithm for Cognitive MIMO Systems via Game Theory

Cognitive radio has been recently proposed as a promising technology to achieve efficient use of spectrum resources. In this paper, we consider spectrum sharing in a MIMO system where several secondary users (SUs) share spectrum with a primary user (PU). A leakage-based beamforming algorithm is proposed via game theory. The objective is to maximize the sum throughput of SUs subject to the signal-to-leakage-and-noise ratio (SLNR) constraint of SUs and PU interference constraint. The sum-throughput maximization problem is formulated as a non-cooperative game, where the SUs compete with each other over the resources offered by the PU. Nash equilibrium is considered as the solution of this game. Simulation results show that the proposed algorithm can achieve a high sum throughput and converge to a locally optimal beamforming vector.
Solving Controlled Markov Set-Chains With Discounting via Multipolicy Improvement

We consider Markov decision processes (MDPs) where the state transition probability distributions are not uniquely known, but are known to belong to some intervals-so called "controlled Markov set-chains"-with infinite-horizon discounted reward criteria. We present formal methods to improve multiple policies for solving such controlled Markov set-chains. Our multipolicy improvement methods follow the spirit of parallel rollout and policy switching for solving MDPs. In particular, these methods are useful for online control of Markov set-chains and for designing policy iteration (PI) type algorithms. We develop a PI-type algorithm and prove that it converges to an optimal policy
Carrier Interferometry based Channel State Information Estimation Technique for MIMO-OFDM Systems

This paper proposes a carrier interferometry (CI) based channel state information (CSI) estimation technique for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems based on the dynamic parameter controlled orthogonal frequency and time division multiple access (DPC-OF/TDMA) systems. In the proposed scheme, in order to estimate CSI with small number of subcarriers of 64, channel impulse responses for all the transmit antenna elements are multiplexed in the time domain using a CI technique, which is equivalent to an impulse signal, and each impulse response is discriminated using a time window with its length of the longest delay time of the multipaths. Computer simulation confirms that the proposed scheme is effective even in 64 subcarriers usage case.
An Efficient Approach for Preprocessing Data from a Large-Scale Chemical Sensor Array

In this paper, an artificial olfactory system (Electronic Nose) that mimics the biological olfactory system is introduced. The device consists of a Large-Scale Chemical Sensor Array (16, 384 sensors, made of 24 different kinds of conducting polymer materials) that supplies data to software modules, which perform advanced data processing. In particular, the paper concentrates on the software components consisting, at first, of a crucial step that normalizes the heterogeneous sensor data and reduces their inherent noise. Cleaned data are then supplied as input to a data reduction procedure that extracts the most informative and discriminant directions in order to get an efficient representation in a lower dimensional space where it is possible to more easily find a robust mapping between the observed outputs and the characteristics of the odors in input to the device. Experimental qualitative proofs of the validity of the procedure are given by analyzing data acquired for two different pure analytes and their binary mixtures. Moreover, a classification task is performed in order to explore the possibility of automatically recognizing pure compounds and to predict binary mixture concentrations.
Monitoring Diabetic Wound Healing by NIR Spectroscopy

Chronic wounds represent one of the most serious complications of diabetes. Lack of quantitative assessment of healing progress makes diabetic wound management a clinical challenge. We constructed an optical device based on near infrared diffuse optical spectroscopy and monitored the change in wound optical properties during healing. A single source, four detector frequency domain instrument with multiple wavelengths was employed in a streptozotocin induced diabetic rat animal model. Optical properties including absorption and reduced scattering coefficients were measured. Our results show that there is significant difference in the absorption and reduced scattering coefficient of the wounds between diabetic and controls rats, and such difference persists throughout the healing period. Our technique would be highly useful in monitoring and quantifying the wound healing process
Urinary tract pathogens-sensitivity to trimethoprim/sulphamethoxazole.

Abstract The sensitivity to sulphamethizole, sulphamethoxazole (SM), trimethoprim (TMP) and the combination SM/TMP of freshly isolated urinary tract pathogens from hospital patients was studied. Out of 798 strains tested primarily, 47% were found to be fully sensitive to sulphamethizole (tablet method), and 81% fully sensitive to the SM/TMP combination (disk method). Out of 423 strains with reduced sensitivity to sulphamethizole, 65% were fully sensitive to SM/TMP. Out of 391 strains tested secondarily (disk method), 39% were fully sensitive to SM, 68% fully sensitive to TMP, and 91% to SM/TMP. Of 283 strains presenting a reduced sensitivity to SM, 85% were fully sensitive to SM/TMP. In both series the isolated Streptococcus faecalis strains were highly resistant to sulphamethizole and SM, but presented a very high degree of sensitivity to TMP and SM/TMP. In contrast, nearly all isolated Pseudomonas aeruginosa strains were found to be resistant both to sulphonamides, TMP and SM/TMP. Of the 18 Staphylococcus aureus strains tested secondarily, 10 out of 12 multiresistant strains were fully sensitive to TMP. Synergy between SM and TMP could be demonstrated in 61% of the 391 strains tested secondarily. The synergic effect depended on the degree of sensitivity to SM.