Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling of COX-1 to mPGES1 for prostaglandin E2 biosynthesis in the murine mammary gland Published, JLR Papers in Press, October 3, 2005. DOI 10.1194/jlr.M500213-JLR200

The mammary gland, like most tissues, produces measurable amounts of prostaglandin E2 (PGE2), a metabolite of arachidonic acid produced by sequential actions of two cyclooxygenases (COX-1 and COX-2) and three terminal PGE synthases: microsomal prostaglandin E2 synthase-1 (mPGES1), mPGES2, and cytosolic prostaglandin E2 synthase (cPGES). High PGE2 levels and COX-2 overexpression are frequently detected in mammary tumors and cell lines. However, less is known about PGE2 metabolic enzymes in the context of normal mammary development. Additionally, the primary COX partnerships of terminal PGE synthases and their contribution to normal mammary PGE2 biosynthesis are poorly understood. We demonstrate that expression of COX-1, generally considered constitutive, increases dramatically with lactogenic differentiation of the murine mammary gland. Concordantly, total PGE2 levels increase throughout mammary development, with highest levels measured in lactating tissue and breast milk. In contrast, COX-2 expression is extremely low, with only a modest increase detected during mammary involution. Expression of the Gs-coupled PGE2 receptors, EP2 and EP4, is also temporally regulated, with highest levels detected at stages of maximal proliferation. PGE2 production is dependent on COX-1, as PGE2 levels are nearly undetectable in COX-1-deficient mammary glands. Interestingly, PGE2 levels are similarly reduced in lactating glands of mPGES1-deficient mice, indicating that PGE2 biosynthesis results from the coordinated activity of COX-1 and mPGES1. We thus provide evidence for the first time of functional coupling between COX-1 and mPGES1 in the murine mammary gland in vivo.
World Economic Outlook, April 2010 - Press points for Chapter 3: Unemployment Dynamics during Recessions and Recoveries: Okun’s Law and Beyond

 Unemployment responses differed markedly across advanced economies during the Great Recession. The sharp increases in Spain and the United States can be explained largely by the effect of output declines, as well as the impact of financial stress and house price busts. In other countries, the rise in unemployment was less than predicted, partly reflecting large short-time work programs (Germany, Italy, Japan, and Netherlands).
An analog motion field detection chip for image segmentation

We propose an analog integrated circuit to compute the motion field of a time-varying image by means of a multiple-constraint method. The chip converts optical input to an electrical form with an array of on-chip image sensors. A resistive network is used to smooth the input image. The spatial and temporal derivatives of the image are used to compute the optical-flow constraint. An array of motion cells enforce the optical-flow constraints, and two nonlinear resistive networks enforce the smoothness constraint over the optical-flow field. In order to preserve object boundaries, the smoothness constraint must be adjusted according to discontinuities in the optical-flow field and edges in the image. This is achieved by the nonlinear nature of the resistors and by adjusting the conductance of the resistors according to spatial gradients of image intensity. A 32/spl times/32 optical-flow based motion field detection chip is fabricated using a 0.5 /spl mu/m CMOS process. Measurement results show that the proposed IC can compute the optical-flow field in a scene efficiently and correctly so as to facilitate segmentation of moving objects in image sequences.
Monte-Carlo Valuation of Options Under Uncertain Volatility: A Local Quadratic Kernel Regression-Based Method

We present a non-parametric Monte-Carlo method for computing the price of an option in an uncertain volatility model. We use the link between second-order BSDE and non-linear second order parabolic PDEs to derive a numerical scheme that gives a fast and accurate estimation of the optimal volatilities and correlations. The scheme uses the local quadratic kernel regressors to estimate both the price and the gamma of the option.
Phase shift, coherence, BPV and HRV before and during self-terminating cardiac arrhythmia

The purpose of this work is to discuss the ability of wavelet analysis and cross-spectral algorithm to follow up the short-term cardiovascular function changes during cardiac arrhythmia. It was analyzed the (a) coherence between systolic blood pressure (SBP) and cardiac oscillations in low frequency (LF) and high frequency (HF) band; (b) fluctuations of phase; (c) heart rate variability (HRV) and blood pressure variability (BPV) as a LF power and HF power in frequency and time frequency domain. The analysis was performed on blood pressure and electrocardiogram signals from one rabbit anaesthetized, paralyzed and mechanically ventilated with self-terminating atrial and ventricular fibrillation after 7 minutes of cardiac arrhythmia. Arrhythmia was preceded by a) decreased coherence; b) increase in fluctuations of phase between signals; c) increased spectral energy associated with respiratory frequency in blood pressure signal; d) increased sympathetic outflow to the heart and e) decreased HRV. Cardiac arrhythmia was characterized mainly by increased LF power in blood pressure and cardiac signal. During self-termination of dysrhythmia a larger increased in total BPV and HRV was recorded. These results suggest that important information about both neuronal cardio-circulatory control and risk for spontaneous arrhythmia might be provided by combined analysis of frequency, phase, time-frequency analysis of blood pressure and cardiac oscillation.
Expressing Work–Family Tension Management in Memorable Messages with Coworkers

This study complements existing research on responses to work–family tension by illuminating the constitutive role of communication in framing this tension at work. We used a memorable-messages format to investigate the most memorable message 892 participants shared with coworkers regarding work–family conflict. We used thematic analysis to code messages, resulting in a model of 20 themes. Themes varied in their focus on independence vs. interdependence and perceived efficacy vs. perceived inefficacy at work–family tension management. We concluded that messages coworkers craft about work–family tension could have implications for perceptions of self and others, as well as impacts on organizational communication.
Dynamics calibration using inverse dynamics and LS technique — An application to the human body

The human body is modeled as a humanoid robot with 34 dof and 15 links. The inverse dynamic model of the robot is linear in relation to 10 standard physical inertial parameters for each link which are the mass, the 6 inertia matrix coefficients and the 3 center of mass coordinates. For robotics control or simulation applications, a minimum number of b base parameters, b <; 150, can be identified by linear LS techniques using motion capture and foot/ground contact force/torque data measurements. But some base parameters are not well identified due to measuring errors and poor excitation. They have no statistical significant values and they can lose their physical meaning. Because these parameters have little contribution in the measured force/torque they can be eliminated from the model to calculate a subset of significant base parameters called the essential parameters [1], [2], [3]. For medical applications the physical anatomical meaningful values are needed for the 150 standard parameters of the 15 segments of the human body model, not only a minimal set of parameters. Based on the essential parameters we propose to calculate the LS solution with SVD factorization, which is the closest in 2 norm of a set of a priori anatomic values given by literature database. This solution keeps both the same minimum norm error given by the essential parameters and the physical anatomical meaning of the a priori values when the measuring noise and errors are small. Experimental results are presented and discussed.
Content-Based Image Retrieval Based on Scale-Space Theory

A content-based image retrieval scheme based on scale-space theory is proposed. Instead of considering all scales for image retrieval, the proposed algorithm utilizes a modified histogram intersection method to compute the relative scale between a query image and a candidate image. The proposed method has been applied to various images and the performance improvement has been verified. key words: content-based image retrieval, scale-space
Jcb Online Supplemental Material

FRET microscopy imaging FRET microscopy relies on the ability to capture weak and transient fluorescent signals efficiently and rapidly from the interactions of labeled molecules in single living or fixed cells. The occurrence of FRET signal (sensitized signal) can be verified by acquiring the two-emission signal bands of the double labeled cells excited with donor wavelength. If FRET occurs the donor channel signal will be quenched and the acceptor channel signal will be sensitized or increased (Herman et al., 2001). In principle, the measurement of FRET in a microscope can provide the same information that is available from the more common macroscopic solution measurements of FRET; however, FRET microscopy has the additional advantage that the spatial distribution of FRET efficiency can be visualized throughout the image, rather than registering only an average over the entire cell or population. Because energy transfer occurs over distances of 1–10 nm, a FRET signal corresponding to a particular location within a microscope image provides an additional magnification surpassing the optical resolution (‫ف‬ 0.25 ␮ m) of the light microscope (Kauzmann, 1957). Thus, within a voxel of microscopic resolution, FRET resolves average donor-acceptor distances beyond the microscopic limit down to the molecular scale. This is one of the principal and unique benefits of FRET for microscopic imaging: not only colocalization of the donor-and acceptor-labeled probes within ‫ف‬ 0.09 ␮ m 2 can be seen, but intimate interactions of molecules labeled with donor and acceptor can be demonstrated. Different intensity-based imaging techniques that apply the method of FRET include Wide-field, Confocal, and Multi-photon microscopy (Periasamy et al., 2001). All FRET microscopy systems require neutral density filters to control the excitation light intensity, a stable excitation light source (Hg or Xe or combination arc lamp; UV, Visible or Infrared lasers), a heated stage or a chamber to maintain the cell viability and appropriate filter sets (excitation, emission, and dichroic) for the selected fluorophore pair. It is important to carefully select filter combinations that reduce the spectral bleed through (SBT) to improve the signal-to-noise (S/N) ratio for the FRET signals. Some possible filter combinations for FRET imaging using several of the different fluorophore combinations are shown in Table SI (Chroma Technology Corp.; Omega Opticals, Inc.). Wide-field FRET microscopy. In addition to the above-mentioned features, the wide-field microscopy requires a tripartite system: a conventional fluorescence microscope equipped with a movable z-axis stage that permits imaging of the specimen at …
Commodity Derivative Pricing Under the Benchmark Approach

This thesis models commodity prices and derivatives, written on commodity prices, under the benchmark approach. Under this approach, the commodity prices are modeled under the real world probability measure while the corresponding numeraire is the numeraire portfolio (NP), which is the growth optimal portfolio that maximizes expected logarithmic utility. The existence of an equivalent risk neutral probability measure is not required. Under the proposed new concept of benchmarked risk minimization, the minimal price for a nonhedgeable contingent claim is identi ed, and the uctuations of the benchmarked pro t and loss, when denominated in units of the NP, are minimized. The resulting real world pricing formula generalizes the classical risk neutral pricing formula. The NP will be approximated by a well-diversi ed stock index. New forward and futures price formulas will be derived, which generalize their classical counterparts. Stylized empirical facts for the dynamics of the NP in a selected commodity denomination will be identi ed. These lead to a model which falls outside classical no-arbitrage assumptions, but is covered by the benchmark approach. Under this model, some long dated derivatives will be shown to be less expensive than under the classical paradigm.
Implicit hierarchical boosting for multi-view object detection

Multi-view object detection is a fundamental problem in computer vision. Current approaches generally require an explicit partition between different views with or without sharing descriptors. We present a novel boosting based learning approach which automatically learns a multi-view detector without using intra-class sub-categorization based on prior knowledge. To avoid multiplying the false alarm rate by the number of classifiers, which happens on the classical approach where one classifier per view is considered, we build a single cascade of weak classifiers which contains an implicit hierarchical structure. In details, a partition of positive samples is automatically computed in order to build an adequate weak classifier based on one specific descriptor per subset. By adapting iteratively the number of descriptors at each stage, the so-defined hierarchical structure enables both a precise modelling and an efficient sharing of descriptors between views. Experimental results demonstrate the relevance and efficiency of this new approach.
A Message-Passing Algorithm for Graph Isomorphism

A message-passing procedure for solving the graph isomorphism problem is proposed. The procedure resembles the belief-propagation algorithm in the context of graphical models inference and LDPC decoding. To enable the algorithm, the input graphs are transformed into intermediate canonical representations of bipartite graphs. The matching procedure injects specially designed input patterns to the canonical graphs and runs a message-passing algorithm to generate two output fingerprints that are matched if and only if the input graphs are isomorphic.
The Impact of Japanese Deregulation on the Euro-yen Bond Market

The purpose of this paper is to examine the impact of three events on spreads on yen denominated bonds issued in the Euromarket by Japanese firms. The three events are: the entry of banks as underwriters in the Japanese corporate bond market; the actual entry of Japanese banks into the underwriting of corporate bonds in the Euromarket; and the relaxation of the three bureaus agreement. There is strong evidence that there is a significant reduction in spreads on Euro-yen bonds around the time of the relaxation of the three bureaus agreement. There is some evidence that the entry of banks as underwriters in the Japanese corporate bond market also coincides with a reduction in spreads in the Euro-yen market. In contrast, the actual entry of Japanese banks into the underwriting of corporate bonds in the Euro-yen market does not appear to have significantly affected spreads.
Global Tracking Control of Strict-Feedback Systems Using Neural Networks

Most existing adaptive neural controllers ensure semiglobally uniform ultimately bounded stability on the condition that the neural approximation remains valid for all time. However, such a condition is difficult to verify beforehand. As a result, deterioration of tracking performance or even instability may occur in real applications. A common recourse is to activate an extra robust controller outside the neural active region to pull back the transient. Such an approach, however, has been restricted to dynamic systems with matched uncertainty. We extend it to strict-feedback systems with mismatched uncertainties via multiswitching-based backstepping methodology. Each virtual and actual controller of the proposed design switches between an adaptive neural controller and a robust controller, with the switching algorithm being sufficiently smooth and, hence, able to be incorporated with the backstepping tool. The overall controller ensures globally uniform ultimate boundedness while simultaneously avoiding the possible control singularity. Simulation results demonstrate the validity of the proposed designs.
Flipped classroom learning in a first-year undergraduate engineering course

Flipped classrooms support student-centred learning and are increasingly being adopted in institutions of higher learning worldwide. This paper is a report on the findings of a two-year funded project conducted on the impact of adopting a flipped classroom approach on first-year undergraduate engineering students’ learning in a New Zealand university. A designbased methodology was adopted to allow for five iterative course refinements. Data collected through student achievement data, surveys, focus group interviews, observations and video analytics of student video-watching behaviour indicated a significant improvement in students’ learning and that they valued the flipped course components such as the lecturercreated instructional videos, in-class problem-solving exercises and continuous assessment in supporting their learning. However not all students prefer learning through this approach and more scaffolding is needed for first-year students to take up responsibility for their own learning. Implications for practice are offered.
A new meta-module for efficient reconfiguration of hinged-units modular robots

We present a robust and compact meta-module for edge-hinged modular robot units such as M-TRAN, SuperBot, SMORES, UBot, PolyBot and CKBot, as well as for central-point-hinged ones such as Molecubes and Roombots. Thanks to the rotational degrees of freedom of these units, the novel meta-module is able to expand and contract, as to double/halve its length in each dimension. Moreover, for a large class of edge-hinged robots the proposed meta-module also performs the scrunch/relax and transfer operations required by any tunneling-based reconfiguration strategy, such as those designed for Crystalline and Telecube robots. These results make it possible to apply efficient geometric reconfiguration algorithms to this type of robots. We prove the size of this new meta-module to be optimal. Its robustness and performance substantially improve over previous results.
Brachypodium sylvaticum, a Model for Perennial Grasses: Transformation and Inbred Line Development

Perennial species offer significant advantages as crops including reduced soil erosion, lower energy inputs after the first year, deeper root systems that access more soil moisture, and decreased fertilizer inputs due to the remobilization of nutrients at the end of the growing season. These advantages are particularly relevant for emerging biomass crops and it is projected that perennial grasses will be among the most important dedicated biomass crops. The advantages offered by perennial crops could also prove favorable for incorporation into annual grain crops like wheat, rice, sorghum and barley, especially under the dryer and more variable climate conditions projected for many grain-producing regions. Thus, it would be useful to have a perennial model system to test biotechnological approaches to crop improvement and for fundamental research. The perennial grass Brachypodium sylvaticum is a candidate for such a model because it is diploid, has a small genome, is self-fertile, has a modest stature, and short generation time. Its close relationship to the annual model Brachypodium distachyon will facilitate comparative studies and allow researchers to leverage the resources developed for B . distachyon . Here we report on the development of two keystone resources that are essential for a model plant: high-efficiency transformation and inbred lines. Using Agrobacterium tumefaciens-mediated transformation we achieved an average transformation efficiency of 67%. We also surveyed the genetic diversity of 19 accessions from the National Plant Germplasm System using SSR markers and created 15 inbred lines.
Residual Dizziness after Successful Repositioning Treatment in Patients with Benign Paroxysmal Positional Vertigo

Background and purpose Benign paroxysmal positional vertigo (BPPV) is the most common form of vertigo. Although the repositioning maneuver dramatically improves the vertigo, some patients complain of residual dizziness. We evaluated the incidence and characteristics of persistent dizziness after successful particle repositioning and the clinical factors associated with the residual dizziness. Methods We performed a prospective investigation in 49 consecutive patients with confirmed BPPV. The patients were treated with a repositioning maneuver appropriate for the type of BPPV. Success was defined by the resolution of nystagmus and positional vertigo. All patients were followed up until complete resolution of all dizziness, for a maximum of 3 months. We collected data on the characteristics and duration of any residual dizziness and analyzed the clinical factors associated with the residual dizziness. Results Of the 49 patients, 11 were men and 38 were women aged 60.4±13.0 years (mean ±SD), and 30 (61%) of them complained of residual dizziness after successful repositioning treatment. There were two types of residual dizziness: continuous lightheadedness and short-lasting unsteadiness occurring during head movement, standing, or walking. The dizziness lasted for 16.4±17.6 days (range=2-80 days, median=10 days). A longer duration of BPPV before treatment was significantly associated with residual dizziness (p=0.04). Conclusions Residual dizziness after successful repositioning was observed in two-thirds of the patients with BPPV and disappeared within 3 months without specific treatment in all cases. The results indicate that early successful repositioning can reduce the incidence of residual dizziness.
A concurrent approach to clustering algorithm with applications to VLSI domain

Circuit partitioning plays an important role in physical design automation of very large scale integration (VLSI) chips. In this brief we present a new connectivity based top down as well as bottom up approach to clustering algorithm for VLSI circuit partitioning. The proposed clustering algorithm partitions the circuit by focusing on highly interconnected cell groups. This clustering algorithm leads to a parallel implementation in which multiple processors are used to identify clusters simultaneously. The process starts with forming clusters by grouping the cells that are tightly connected and as well as the cells that are loosely connected. Considering both types of groups has the advantage that clusters formed from this technique will be highly connected and compact too. Therefore the proposed clustering method can reduce the size and also speed-up the large-scale partitioning problem without loosing partitioning solution qualities. The performance of the proposed clustering algorithm is evaluated on a standard set of partitioning benchmark-ISPD98 benchmark suite.