Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Cytokinin Mutants and Regulation of Cytokinin Metabolic Genes Reveals Important Regulatory Roles of Cytokinins in Drought, Salt and Abscisic Acid Responses, and Abscisic Acid Biosynthesis[C][W]

Functional analyses of cytokinin (CK)-deficient plants provide direct evidence that CKs negatively regulate plant response to drought and salt stresses. CK-deficient plants exhibited a strong stress-tolerant phenotype associated with abscisic acid (ABA) hypersensitivity. This study suggests that mutual regulation mechanisms between CK and ABA affect the plant’s adaptation to stressors and plant growth and development. Cytokinins (CKs) regulate plant growth and development via a complex network of CK signaling. Here, we perform functional analyses with CK-deficient plants to provide direct evidence that CKs negatively regulate salt and drought stress signaling. All CK-deficient plants with reduced levels of various CKs exhibited a strong stress-tolerant phenotype that was associated with increased cell membrane integrity and abscisic acid (ABA) hypersensitivity rather than stomatal density and ABA-mediated stomatal closure. Expression of the Arabidopsis thaliana ISOPENTENYL-TRANSFERASE genes involved in the biosynthesis of bioactive CKs and the majority of the Arabidopsis CYTOKININ OXIDASES/DEHYDROGENASES genes was repressed by stress and ABA treatments, leading to a decrease in biologically active CK contents. These results demonstrate a novel mechanism for survival under abiotic stress conditions via the homeostatic regulation of steady state CK levels. Additionally, under normal conditions, although CK deficiency increased the sensitivity of plants to exogenous ABA, it caused a downregulation of key ABA biosynthetic genes, leading to a significant reduction in endogenous ABA levels in CK-deficient plants relative to the wild type. Taken together, this study provides direct evidence that mutual regulation mechanisms exist between the CK and ABA metabolism and signals underlying different processes regulating plant adaptation to stressors as well as plant growth and development.
Probabilistic multiple face detection and tracking using entropy measures

A joint probabilistic face detection and tracking algorithm, combining likelihood estimation and a prior probability, is proposed. The likelihood estimation scheme is based on the statistical training of sets of automatically generated feature points and a mutual information tracking cue, while the prior probability estimation is based on a Gaussian temporal model. The likelihood estimation process is the core of a multiple face detection scheme used to initialize the tracking process. The resulting system has been tested on real image sequences and is robust to significant partial occlusion and illumination changes.
Regression Tree Modeling For The Prediction Of Software Quality

This paper demonstrates the use of regression tree models to predict the number of faults in a software module based on the software complexity metrics(cid:0) prior to the testing phase(cid:0) which can help in channel(cid:1) ing the validation and testing e(cid:2)orts in a productive direction(cid:3) We also compare the regression tree model(cid:1) ing technique with the fault density technique which is a very commonlyused approach to predict the num(cid:1) ber of faults(cid:3)
Analysis on Factors Affecting Biodiesel Production Rate Based on Probability Theory

Biodiesel orthogonal experiments require large amount of experimental data collected and in order to save experimental time, referring to the correlation coefficients analysis in probability theory, the factors which affect the yield of biodiesel are analyzed. Under the same reaction temperature, the range order is as follows: the molar ration of alcohol to oil, the dosage of catalyst and reaction of time. At the same time, it provides theoretical guidance for obtaining optimum reaction conditions .
A motivation model for virtual characters

Motivation is an important psychology characteristic for a virtual character. An autonomous virtual characterpsilas behavior and emotion are controlled by motivation and outer stimuli, setting up the computer model of motivation of virtual characters is a hot topic in computer game and human interface. The current state of research on mental models of virtual characters is reviewed. Based on psychology theory, formalization concepts on Maslowpsilas theory are set up. A new motivation model of virtual character is proposed. The model can integrate stimuli, motivation, behavior, emotion and personality together.
Effect of Chain Morphology and Carbon-Nanotube Additives on the Glass Transition Temperature of Polyethylene

Glass transition temperature Tg is the most important parameter affecting the mechanical properties of amorphous and semi-crystalline polymers. However, the atomistic origin of glass transition is not yet well understood. Using Polyethylene (PE) as an example, this paper investigates the glass transition temperature Tg of PE with the aid of molecular dynamics (MD) simulation. The effects of PE chain branches, crystallinity and carbon-nanotube (CNT) additives on the glass transition temperature are analyzed. The MD simulations render a good agreement with the relevant experimental data of semi-crystalline PE and show the significant effects of crystallinity and addition of CNTs on Tg.
TWO NONEXCLUSIVE NEURO-FUZZY CLASSIFIERS FOR RECOGNITION OF MUSICAL INSTRUMENTS

The classification of single musical sources is an essential step in order to obtain the source separation and the automatic transcription of polyphonic music. In this paper, we present a first experience of recognition of five different musical instruments (clarinet, flute, oboe, saxophone and violin). For such task, a nonexclusive classifier capable of fuzzy decisions is especially suitable, due to the inevitable overlaps among data. We used two different neuro-fuzzy classifier for recognition of musical instruments and we compared the obtained results.
Evaluation of Schedule Managing Agent among Multiple Members with Representation of Background Negotiations

This paper proposes an interactive manager agent system that adjusts schedule among multiple persons through negotiations on behalf of a human organizer, such as a steward or team manager. In order to increase the users' cooperative decision-making, we implemented the manager agent that negotiates with each member on the schedule using 1) the suitable attitude depending on current situation and partner of negotiation and 2) the graphical representation of background negotiations between the agent and the other users: a) the other users' icons, b) the blinking balloons of both the other users and the agent, and c) the agent's looking-back actions for the other users' icons. The results of the evaluations showed that both the individual use and the combination of the proposed expressions could make the participants feel i) as though there were under-going negotiations between the agent and the other users and ii) as though the agent had both the effort and compassion to the user. Moreover, the user's cooperative decision-making was increased by the proposed method.
Calibration and validation of digital airborne cameras

With the growing use of digital airborne imagers in daily operational data acquisition and processing the need for the development of guidelines and procedures for quality assurance and quality control is clearly obvious. Several national and international organizations are dealing with those topics, where focus is laid on the calibration, validation and certification of the new sensors. As an example the activities from USGS (United States) and EuroSDR (Europe) are presented within this article. Since both projects are still under current processing, only an overview and snap-shot of the status and preliminary results are given.
A dispersion law for virtually imaged phased-array spectral dispersers based on paraxial wave theory

We derive the spectral dispersion law for the virtually imaged phased array (VIPA) based on paraxial wave theory using the Fresnel diffraction analysis. The validity of the dispersion law is verified by comparison with experiments. This spectral dispersion law is compared to a previous law based on plane wave theory. At small incident angles where the VIPA provides its largest spectral dispersion, the paraxial wave law provides a much better fit to the data than the plane wave law does.
From Boulez to ballads: Training IRCAM's Score follower

This paper describes our attempt to make the Hidden Markov Model (HMM) score following system developed at Ircam sensible to past experiences in order to obtain better audio to score real-time alignment for musical applications. A new observation modeling based on Gaussian Mixture Models is developed which is trainable using a learning algorithm we call automatic discriminative training. The novelty of this system lies in the fact that this method, unlike classical methods for HMM training, is not concerned with modeling the music signal but with correctly choosing the sequence of music events that was performed. Besides obtaining better alignment, new system’s parameters are controllable in a physical manner and the training algorithm learns different styles of music performance as discussed. Experience with the piece . explosante‐fixe. by Boulez, and with an advanced karaoke system that allows to sing ballads in free tempo with automatic accompaniment are given.
Early intravenous thrombolysis with recombinant tissue-type plasminogen activator in vertebrobasilar ischemic stroke.

BACKGROUND The optimal therapy of vertebrobasilar ischemic stroke is under debate. In the case of underlying basilar artery occlusion, intra-arterial thrombolysis is recommended. Because this pathologic condition is rarely found and the procedure is time consuming and restricted to specialized centers, the question arises whether early intravenous thrombolysis could also effectively be applied in vertebrobasilar ischemic stroke. OBJECTIVE To determine if early intravenous thrombolysis could be used effectively in vertebrobasilar ischemic stroke. DESIGN A case series of 12 consecutive patients with acute vertebrobasilar ischemia were followed up 3 months after thrombolytic treatment at the Department of Neurology of the University Hospital of Cologne, Cologne, Germany, a primary care and referral center. METHODS Patients with clinically diagnosed moderate to severe vertebrobasilar ischemic stroke with clearly determined symptom onset were treated with intravenous recombinant tissue-type plasminogen activator within 3 hours after symptom onset following a protocol similar to that of the National Institute of Neurological Disorders and Stroke study. RESULTS On admission, 7 patients exhibited moderate to severe brainstem symptoms without impairment of consciousness and 5 patients had impairment of consciousness, of whom 2 were comatose. Of 12 patients, 10 had a favorable outcome after 3 months defined as full independence (Barthel index score of 100) or return to premorbid condition. One patient had a poor outcome with complete dependency due to reocclusion after primarily successful thrombolysis, and 1 patient died of severe brainstem infarction and additional space occupying parietal hemorrhage. CONCLUSION Favorable outcome could be achieved in the majority of 12 consecutive patients with moderate to severe vertebrobasilar ischemic stroke treated with intravenous recombinant tissue-type plasminogen activator within 3 hours after symptom onset.
Filling Holes in Triangular Meshes Using Digital Images by Curve Unfolding

We propose a novel approach to automatically fill holes in triangulated models. Each hole is filled using a minimum energy surface that is obtained in three steps. First, we unfold the hole boundary onto a plane using energy minimization. Second, we triangulate the unfolded hole using a constrained Delaunay triangulation. Third, we embed the triangular mesh as a minimum energy surface in ℝ3. When embedding the triangular mesh, any energy function can be used to estimate the missing data. We use a variational multi-view approach to estimate the missing data. The running time of the method depends primarily on the size of the hole boundary and not on the size of the model, thereby making the method applicable to large models. Our experiments demonstrate the applicability of the algorithm to the problem of filling holes bounded by highly curved boundaries in large models.
Correlation of CTGF gene promoter methylation with CTGF expression in type 2 diabetes mellitus with or without nephropathy

Increasing evidence shows that DNA methylation is involved in the development and progression of diabetes mellitus (DM) and its complications. Previous studies conducted by our group have indicated that high glucose levels may induce the demethylation process of the connective tissue growth factor (CTGF) gene promoter and increase the expression of CTGF in human glomerular mesangial cells. Based on these findings, the aim of the present study was to investigate the methylation level of genomic DNA and the CTGF promoter in patients with type 2 DM and to analyze its possible correlation with CTGF expression. Methylation levels of the whole genomic DNA were detected by high-performance liquid chromatography in a non-diabetes control (NDM) group (n=29), a diabetes without nephropathy (NDN) group (n=37) and a diabetes with nephropathy (DN) group (n=38). CTGF promoter methylation levels were detected by methylation-specific polymerase chain reaction and bisulfite sequencing. The levels of serum CTGF were assessed using the enzyme-linked immunosorbent assay. The methylation levels of the whole genomic DNA were not significantly different among the three groups. However, the CTGF methylation levels in the two diabetes groups were significantly lower than those in the NDM group (P<0.05), with the lowest methylation level in the DN group (P<0.05). The CTGF protein levels in the DN group were significantly higher than those in the NDM and NDN groups (P<0.05). Levels of CTGF were negatively correlated with the estimated glomerular filtration rate (eGFR) and the methylation level of the promoter, while they were positively correlated with age, urinary albumin-to-creatinine ratio (UACR), blood urea nitrogen, creatinine, fasting blood sugar and postprandial blood glucose. Multiple stepwise regression analysis showed that CTGF expression was associated with the UACR, CTGF methylation level and eGFR. DNA methylation is a regulatory mechanism of CTGF expression, which is decreased in patients with DM, particularly in those with DN, and may contribute to the pathogenesis of nephropathy.
Direct measurement of the lamellipodial protrusive force in a migrating cell

There has been a great deal of interest in the mechanism of lamellipodial protrusion (Pollard, T., and G. Borisy. 2003. Cell. 112:453–465). However, one of this mechanism's endpoints, the force of protrusion, has never been directly measured. We place an atomic force microscopy cantilever in the path of a migrating keratocyte. The deflection of the cantilever, which occurs over a period of ∼10 s, provides a direct measure of the force exerted by the lamellipodial leading edge. Stall forces are consistent with ∼100 polymerizing actin filaments per micrometer of the leading edge, each working as an elastic Brownian ratchet and generating a force of several piconewtons. However, the force-velocity curves obtained from this measurement, in which velocity drops sharply under very small loads, is not sensitive to low loading forces, and finally stalls rapidly at large loads, are not consistent with current theoretical models for the actin polymerization force. Rather, the curves indicate that the protrusive force generation is a complex multiphase process involving actin and adhesion dynamics.
PUTTING THINGS IN EVEN BETTER ORDER: THE ADVANTAGES OF CANONICAL CORRESPONDENCE ANALYSIS'

Canonical Correspondence Analysis (CCA) is quickly becoming the most widely used gradient analysis technique in ecology. The CCA algorithm is based upon Correspondence Analysis (CA), an indirect gradient analysis (ordination) technique. CA and a related ordination technique, Detrended Correspondence Analysis, have been crit- icized for a number of reasons. To test whether CCA suffers from the same defects, I simulated data sets with properties that usually cause problems for DCA. Results indicate that CCA performs quite well with skewed species distributions, with quantitative noise in species abundance data, with samples taken from unusual sampling designs, with highly intercorrelated environmental variables, and with situations where not all of the factors determining species composition are known. CCA is immune to most of the problems of DCA.
Directional Harmonic Theory: A Computational Gestalt Model to Account for Illusory Contour and Vertex Formation

Visual illusions and perceptual grouping phenomena offer an invaluable tool for probing the computational mechanism of low-level visual processing. Some illusions, like the Kanizsa figure, reveal illusory contours that form edges collinear with the inducing stimulus. This kind of illusory contour has been modeled by neural network models by way of cells equipped with elongated spatial receptive fields designed to detect and complete the collinear alignment. There are, however, other illusory groupings which are not so easy to account for in neural network terms. The Ehrenstein illusion exhibits an illusory contour that forms a contour orthogonal to the stimulus instead of collinear with it. Other perceptual grouping effects reveal illusory contours that exhibit a sharp corner or vertex, and still others take the form of vertices defined by the intersection of three, four, or more illusory contours that meet at a point. A direct extension of the collinear completion models to account for these phenomena tends towards a combinatorial explosion, because it would suggest cells with specialized receptive fields configured to perform each of those completion types, each of which would have to be replicated at every location and every orientation across the visual field. These phenomena therefore challenge the adequacy of the neural network approach to account for these diverse perceptual phenomena. I have proposed elsewhere an alternative paradigm of neurocomputation in the harmonic resonance theory (Lehar 1999, see website), whereby pattern recognition and completion are performed by spatial standing waves across the neural substrate. The standing waves perform a computational function analogous to that of the spatial receptive fields of the neural network approach, except that, unlike that paradigm, a single resonance mechanism performs a function equivalent to a whole array of spatial receptive fields of different spatial configurations and of different orientations, and thereby avoids the combinatorial explosion inherent in the older paradigm. The present paper presents the directional harmonic model, a more specific development of the harmonic resonance theory, designed to account for specific perceptual grouping phenomena. Computer simulations of the directional harmonic model show that it can account for collinear contours as observed in the Kanizsa figure, orthogonal contours as seen in the Ehrenstein illusion, and a number of illusory vertex percepts composed of two, three, or more illusory contours that meet in a variety of configurations.
Power gain estimation of an event-driven wake-up controller dedicated to WSN's microcontroller

To deal with Wireless Sensor Node's energy constraints, new architectural solutions have to be found. This paper proposes to analyze a WSN microcontroller sub-system power consumption to extract the main power contributors according to different applicative execution phases. The objective is to come out with the energy reduction potentiality offered by an additional module called Wake-Up Controller. This block is able to substitute to the main CPU for current tasks like data transfers between sensors, memories or radio and fine grain power/frequency management of the entire node's sub-modules. Power simulations of a microcontroller sub-system based on FDSOI28 technology, with and without the Wake-Up Controller use, are proposed. Results are presented for applicative scenarios ranging from very low to high activity rates. This study exhibits power gains from 14.5% to 76% in the full range attesting the future design of this new module.
Platinum based Catalysts for Methanol Fuel Cells: Metal Clusters and Carbon Supports

In this thesis two objectives are pursued in parallel. The first is to reduce the Pt loading and thereby reducing the cost of the catalysts for anode application in direct methanol fuel cell. The second is to tune the surface properties of Pt and thereby enhance the activity in the methanol oxidation reaction. The former is achieved by reducing the Pt cluster size and thus increase the Pt surface area, or by using Ru@Pt core-shell structures to reduce the Pt loading but achieve similar Pt surface area. The surface properties of Pt are tuned through the Ptgraphite edge interface and by tailoring of the RuPt architecture in the shell of the Ru@Pt core-shell NCs. To achieve the above goals, a ex-situ polyol synthesis method was adopted. In this method, monometallic Pt cluster size as well as Ru@Pt cluster size are controlled in the colloid solution before deposition on the corresponding supports. One advantage of this method is that it is possible to study the influence of oxygen groups present on the carbon support surface on the Pt dispersion. It was found that the Pt dispersion was highly dependent on the amount of surface oxygen groups. The methanol oxidation reaction was investigated on Pt clusters with various sizes on carbon nanofibers and carbon black supports with different surface oxygen concentration, aiming at gaining a better understanding of the relationship between the catalyst properties and the electrochemical performance. It was found that CNF-supported Pt clusters showed better performance than carbon black-supported Pt clusters for all the Pt particle sizes. Furthermore, Pt supported on oxygen depleted CNF has better performance than the Pt supported on oxygen rich CNF. Due to the combined advantages of optimum Pt particle size, oxygen free surface and the unique properties of CNF, Pt supported on heat-treated CNF exhibited a mass activity about 2 times higher than for the commercial E-TEK catalyst. Another advantage of the ex-situ polyol method is that the RuPt shell composition in the Ru@Pt core-shell NCs can be tailored simply by controlling the pH of the synthesis medium during Pt deposition. The structural and surface properties of the catalysts were characterized with X-ray diffraction, transmission electron microscopy, CO stripping, and energy dispersive X-ray spectroscopy. It was found that a coreshell catalyst with alloyed shell was obtained at a pH of 5.8, whereas a monometallic Pt shell was obtained at a pH of 10. The methanol oxidation reaction was investigated for the carbon black supported Ru@Pt catalysts with different shell compositions. It was shown that the core-shell catalysts gave the highest steady-state current for methanol oxidation by a factor of 10 for alloyed shell and by a factor of 5 for the Pt shell compared to the pure Pt catalyst. It can be concluded that the improved catalytic performance of the core-shell catalysts can be attributed to the ligand effect in the Pt-rich shell and to a combination of the ligand effect and bi-functional character in the alloyed shell.