Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Effects of Hormonal Contraceptive Use on the Plasma Proteome

Background Hormonal contraceptive (HC) use may increase cardiometabolic risk; however, the effect of HC on emerging cardiometabolic and other disease risk factors is not clear. Objectives To determine the association between HC use and plasma proteins involved in established and emerging disease risk pathways. Method Concentrations of 54 high-abundance plasma proteins were measured simultaneously by LC-MRM/MS in 783 women from the Toronto Nutrigenomics and Health Study. C-reactive protein (CRP) was measured separately. ANCOVA was used to test differences in protein concentrations between users and non-users, and among HC users depending on total hormone dose. Linear regression was used to test the association between duration (years) of HC use and plasma protein concentrations. Principal components analysis (PCA) was used to identify plasma proteomic profiles in users and non-users. Results After Bonferroni correction, 19 proteins involved in inflammation, innate immunity, coagulation and blood pressure regulation were significantly different between users and non-users (P<0.0009). These differences were replicated across three distinct ethnocultural groups. Traditional markers of glucose and lipid metabolism were also significantly higher among HC users. Neither hormone dose nor duration of use affected protein concentrations. PCA identified 4 distinct proteomic profiles in users and 3 in non-users. Conclusion HC use was associated with different concentrations of plasma proteins along various disease-related pathways, and these differences were present across different ethnicities. Aside from the known effect of HC on traditional biomarkers of cardiometabolic risk, HC use also affects numerous proteins that may be biomarkers of dysregulation in inflammation, coagulation and blood pressure.
Hexagonal Multicarrier Modulation: A Robust Transmission Scheme for Time-Frequency Dispersive Channels

By regarding signal transmission as tiling of the time-frequency plane, we propose a multicarrier transmission scheme on hexagonal lattice, coined the term hexagonal multicarrier modulation. To optimally combat the impact of the propagation channels, the underlying lattice parameters and the pulse shape of modulation waveform are jointly optimized to adapt to the channel scattering function from a minimum energy perturbation point of view. It comes out that there exist two equivalent pulse and lattice matching criteria for each channel scattering function to achieve minimal interpulse interference (IPI). Robustness of the proposed system against the wireless channels is analyzed in terms of robustness factor. Numerical analysis and simulation results show that the hexagonal multicarrier transmission system outperforms conventional orthogonal-frequency-division multiplexing (OFDM) and lattice-OFDM (LOFDM) systems with regard to robustness against channel dispersion
A Novel very Compact Printed Antenna using Defected Ground Structure for 2 . 4 and 5 GHz Communication

In order to satisfy the requirement of dual frequency, a novel and simple dual-band microstrip antenna using defected ground structure for wireless local area networks (WLAN) wireless communication (at 2.4 and 5 GHz) is presented in this paper. The proposed antenna consists of a microstrip-fed line ended with two different rectangular patches on the front the side, and a modified rectangular ground with a parasitic pentagonal ground plane on the other side. The designed antenna is very compact, which has a total size of only 20×10×1 mm 3 and is printed on FR-4 epoxy substrate (ε r =4.4). Details of the proposed antenna design are presented and discussed, which can be a good candidate for the requirement of WLAN, operating in 2.4 and 5GHz. I. Introduction Recently, wireless communication is very attractive techniques for wireless Internet access and has gained a wider and wider popularity. There are several standards already for WLAN applications, such as IEEE 802.11a and IEEE 802.11b/g. The band ranges from 2.4GHz to 2.484GHz for IEEE 802.11b/g and the frequency bands of 5.15 to 5.35GHz and 5.725 to 5.825GHz for IEEE 802.11a have received wider attention. To meet these standards, there is a need for designing a multi-band antenna that can cover all these bands. Compact printed monopole antenna is essential candidates for the application in WLAN; UWB and RFID applications because it has wide impedance bandwidth, Omni-directional radiation pattern, compact size, low cost, light weight, less fragile, low profile and finally, the fabrication methodology are simple. So far, numerous monopole antennas have been reported in literature, by employing various the feeds such as the probe, the microstrip, and the coplanar waveguide (CPW), and various the designs for example, F-shaped and T-shaped slot planar antenna, fractal, loop and inverted-F antennas, etc [1-8]. In this letter, a novel compact microstrip-fed monopole antenna for WLAN applications is presented. The radiating element was improved by using two different rectangular patches and also the ground plane was modified by using a parasitic pentagonal ground plane. By changing related parameters of the introduced structure, dual-band characteristics can be adjusted easily and by properly selecting the dimensions of the proposed antenna, good dual-band impedance bandwidth and radiation characteristics suitable for the wireless local-area network (WLAN) 2.4/5.2/5.8 GHz operations can be achieved. Details of the proposed antenna configuration, simulated and experimental results will be carefully examined and discussed in the following two sections.
Risk Aversion and Intertemporal Substitution in the Capital Asset Pricing Model

When tastes are represented by a class of generalized preferences which -- unlike traditional Von-Neumann preferences -- do not confuse behavior towards risk with attitudes towards intertemporal substitution, the true beta of an asset is, in general, an average of its consumption and market betas. We show that the two parameters measuring risk aversion and intertemporal substitution affect consumption and portfolio allocation decisions in symmetrical ways. A unit elasticity of intertemporal substitution gives rise to myopia in consumption-savings decisions (the future does not affect the optimal consumption plan), while a unit coefficient of relative risk aversion gives rise to myopia in portfolio allocation (the future does not affect optimal portfolio allocation). The empirical evidence is consistent with the behavior of intertemporal maximizers who have a unit coefficient of relative risk aversion and an elasticity of intertemporal substitution different from 1.
Mechanism and Network Design with Private Negative Externalities

A revenue-maximizing monopolist is selling a single indivisible good to buyers who face a loss if any of its rival buyers obtain it. The rivalry is modeled through a network, an arc between a pair of buyers indicates that a buyer considers another buyer its rival, and the magnitude of the loss is the private information of each buyer. This loss-exposure due to competitive considerations can be viewed as a negative externality. First, using a Myersonian approach we derive the monopolist’s optimal mechanism for any given network. Second, we show that revenues depend on the network structure. Thus, in applications where it is possible, the monopolist might consider designing not only the mechanism but also the network (if not fully, at least partially). Third, we provide and fully describe the solution to the monopolist’s market design problem; that is, the joint network and mechanism design problem. Specifically, despite the nonmonotone impact of additional competition on the monopolist’s revenues, we deter.
Daily Ischemic Preconditioning Provides Sustained Protection From Ischemia–Reperfusion Induced Endothelial Dysfunction: A Human Study

Background It is well established that acute ischemic preconditioning (IPC) protects against ischemia–reperfusion (IR) injury; however, the effectiveness of repeated IPC exposure has not been extensively investigated. We aimed to determine whether daily IPC episodes provide continued protection from IR injury in a human forearm model, and the role of cyclooxygenase‐2 in these responses. Methods and Results Thirty healthy volunteers were randomized to participate in 2 of 3 protocols (IR alone, 1‐day IPC, 7‐day IPC) in an operator‐blinded, crossover design. Subjects in the IR alone protocol underwent flow‐mediated dilation (FMD) measurements pre‐ and post‐IR (15′ upper‐arm ischemia and 15′ reperfusion). The 1‐day IPC protocol involved FMD measurements before and after 1 episode of IPC (3 cycles of 5′ upper‐arm ischemia and 5′ reperfusion) and IR. Day 7 of the 7‐day IPC protocol was identical to the 1‐day IPC protocol but was preceded by single daily episodes of IPC for 6 days prior. During each protocol, subjects received a 7‐day treatment of either the cyclooxygenase‐2 inhibitor celecoxib or placebo. Pre‐IR FMD was similar between groups. IR alone reduced FMD post‐IR (placebo, ΔFMD: −4.4±0.7%; celecoxib, ΔFMD: −5.0±0.5%). One‐day IPC completely prevented this effect (placebo, ΔFMD: −1.1±0.6%; celecoxib, ΔFMD: 0.0±0.7%; P<0.0001). Similarly, 7‐day IPC demonstrated persistent endothelial protection post‐IR (placebo, ΔFMD: −0.9±0.9%; celecoxib, ΔFMD: 0.0±0.8%; P<0.0001, P<0.0001 for ANOVA effect of IPC protocol). Celecoxib did not alter responses to IR in any protocol. Conclusions Daily episodes of IPC provide sustained protection from IR‐induced endothelial dysfunction in humans through a mechanism that appears cyclooxygenase‐2‐independent.
In Vivo Evidence for Inverse Agonism of Agouti-Related Peptide in the Central Nervous System of Proopiomelanocortin-Deficient Mice

OBJECTIVE—Melanocyte-stimulating hormone (MSH) peptides processed from proopiomelanocortin (POMC) regulate energy homeostasis by activating neuronal melanocortin receptor (MC-R) signaling. Agouti-related peptide (AgRP) is a naturally occurring MC-R antagonist but also displays inverse agonism at constitutively active melanocortin-4 receptor (MC4-R) expressed on transfected cells. We investigated whether AgRP functions similarly in vivo using mouse models that lack all neuronal MSH, thereby precluding competitive antagonism of MC-R by AgRP. RESEARCH DESIGN AND METHODS—Feeding and metabolic effects of the MC-R agonist melanotan II (MTII), AgRP, and ghrelin were investigated after intracerebroventricular injection in neural-specific POMC-deficient (Pomc−/−Tg/+) and global POMC-deficient (Pomc−/−) mice. Gene expression was quantified by RT-PCR. RESULTS—Hyperphagic POMC-deficient mice were more sensitive than wild-type mice to the anorectic effects of MTII. Hypothalamic melanocortin-3 (MC3)/4-R mRNAs in POMC-deficient mice were unchanged, suggesting increased receptor sensitivity as a possible mechanism for the heightened anorexia. AgRP reversed MTII-induced anorexia in both mutant strains, demonstrating its ability to antagonize MSH agonists at central MC3/4-R, but did not produce an acute orexigenic response by itself. The action of ghrelin was attenuated in Pomc−/−Tg/+ mice, suggesting decreased sensitivity to additional orexigenic signals. However, AgRP induced delayed and long-lasting modifications of energy balance in Pomc−/−Tg/+, but not glucocorticoid-deficient Pomc−/− mice, by decreasing oxygen consumption, increasing the respiratory exchange ratio, and increasing food intake. CONCLUSIONS—These data demonstrate that AgRP can modulate energy balance via a mechanism independent of MSH and MC3/4-R competitive antagonism, consistent with either inverse agonist activity at MC-R or interaction with a distinct receptor.
A tool to support specification and evaluation of context-customized interfaces

Intelligent tools to support user interface building are being developed as a response to the difficulty of implementing interfaces of increasing complexity [1, 5, 6, 10, 7]. These tools provide expert assistance to insure that usable interfaces are developed correctly, by formalizing guidelines and criteria which are well known to experts. Less effort has been devoted so far to the objective of supporting the cooperative work of designers and final users in defining how the interface should look like and behave, in evaluating design alternatives and in assessing consequences of changes. This objective becomes relevant when the interface is built in strict cooperation with customers who are not familiar with computers, and by applying iterative design principles. At the same time, it is a common opinion that tools able to support formal evaluation of interfaces might be of help to avoid engaging into expensive empirical evaluations before trivial errors are eliminated from the prototype.A particular specification problem occurs when several categories of users, with distinct backgrounds and needs, are expected to use the system which is being designed: in this case, the interaction style is customized to the context in which the system operates, and the tool should enable simulating and evaluating the different behaviours in a unified way.This paper describes a tool which aims at responding to the mentioned objectives: XDM (Context-Sensitive Dialogue Modeling) extends Coloured Petri Nets to specify context-customized interfaces in a task-based way and to simulate their behaviour in defined contexts. By integrating this modeling approach with KLM theory [2], XDM also enables evaluating (in an automatic or semi-automatic way) whether the interface is correct and usable.First we will show how a designer can employ the tool in the stepwise building of the interface by extending Coloured Petri Nets with functions associated to places and transitions: this extension provides a logical and physical description of tasks performed, actions that enable performing them, information displayed and their layout. Then we describe how interface behaviour can be simulated in several contexts. We go on to show how designers can verify whether the interface is correct and usable. State of the art and future developments are discussed in the final section.
An Overview of the Thesis Chapter 2 Cache Review and Modeling Power Consumption 2.1 Cache Review 2.1.1 Review of Cache Organization

Introduction Nowadays, portable devices such as laptop and notebook computers are very popular. These devices require energy efficient design in order to maximize battery lifetime. Reducing the power consumption of microprocessors has become increasingly important. Many studies have shown that memory accesses account for a noticeably large percentage of the total power consumption in microprocessors, making the power consumption of caches and main memory an important concern [13]. Caches are a significant part of the processor due to the increasing disparity between processor cycle time and memory access time. High performance microprocessors normally have one or two levels of on-chip cache in order to reduce the off-chip traffic as much as possible. Off-chip accesses are not only at least a magnitude slower but also dissipate a large amount of power via highly capacitive I/O pads. Thus, caches are important not only for high performance, but also for low power to help reduce the amount of off-chip communication. The power dissipated by the on-chip cache itself is often a significant part of the power dissipated by the entire microprocessor. For example, in the StrongARM 110 from DEC and the Power PC from IBM, cache power consumption is either the largest or second largest power-consuming block [13]. In the StrongARM CPU which has the current best SPECmarks/ watt rating, 43% of total power is dissipated in the on-chip caches [11]. Another example is the 2 DEC 21164 microprocessor, whose on-chip cache dissipates 25% of the total power [11]. Hence, to achieve an energy efficient design, it is necessary to reduce the power dissipation in the on-chip caches. In a typical processor with a split cache architecture, the instruction cache (I-cache) consumes more power than the data cache (D-cache) because the I-cache is accessed for each instruction while the D-cache is accessed only for loads and stores. Since around 25-30% of the executed instructions are loads and stores, the activity of the D-cache is around 25-30% of the activity of the I-cache. Clearly, the I-cache is an attractive target to reduce power consumption. This thesis, therefore, focuses on reducing the power consumption of the level-1 I-cache by using an in-cache instruction compression technique that uses gated wordlines to reduce the number of bits read for compressed instructions. To accurately estimate cache power, we have developed a cache power consumption model as well as a cache simulator. The analytical model for estimating cache power …
Multi sensor map building based on sparse linear equations solver

This paper proposes fast map building algorithm for multiple modal exteroceptive(external) sensors based on trajectory optimization. To realize localization using multiple modal exteroceptive sensors needs consistent environment maps (landmark maps). Multiple sensor SLAM (simultaneous localization and mapping) is one of solutions to build maps consistently. In implementation of SLAM, approximations of sensor model contribute to get speeded up the algorithm. However in several case, these approximations deteriorate quality of the map. This paper proposes fast and accurate map building algorithm using multiple modal sensors based on sparse linear equations solver. This algorithm needs less approximations-but computation speed is fast. In addition, application of measured data from multiple sensors to this algorithm is described.
Detecting offensive user video blogs: An adaptive keyword spotting approach

This paper proposes a speaker independent keyword spotting (KWS) approach applied to the audio track of user video blogs that can help in their automatic analysis, indexing, search and retrieval. The approach, which relies on matching of keyword templates to speech segments using an adaptive similarity threshold that is estimated automatically for each utterance, does not require training data or language model as required in existing approaches such as those based on the Hidden Markov Model (HMM). This is a particular advantage for user video blogs since they usually contain words of interest that have not been adequately represented in a training database. Experiments conducted to detect offensive words in video blogs achieved much higher accuracy than existing speech-to-text based approaches.
Multiresolution registration of remote sensing images using stochastic gradient

In image registration, we determine the most accurate match between two images, which may have been taken at the same or different times by different or identical sensors. In the past, correlation and mutual information have been used as similarity measures for determining the best match for remote sensing images. Mutual information or relative entropy is a concept from information theory that measures the statistical dependence between two random variables, or equivalently it measures the amount of information that one variable contains about another. This concept has been successfully applied to automatically register remote sensing images based on the assumption that the mutual information of the image intensity pairs is maximized when the images are geometrically aligned. The transformation which maximizes a given similarity measure has been previously determined using exhaustive search, but this has been found to be inefficient and computationally expensive. In this paper we utilize a new simple, yet powerful technique based on stochastic gradient, for the maximization of both similarity measures with remote-sensing images, and we compare its performance to that of the exhaustive search. We initially consider images, which are misaligned by a rotation and/or translation only, and we compare the accuracy and efficiency of a registration scheme based on optimization for this data. In addition, the effect of wavelet pre-processing on the efficiency of a multi- resolution registration scheme is determined, using Daubechies wavelets. Finally we evaluate this optimization scheme for the registration of satellite images obtained at different times, and from different sensors. It is noted that once a correct optimization result is obtained at one of the coarser levels in the multi-resolution scheme, then the registration process is much faster in achieving subpixel accuracy, and is more robust when compared to a single level optimization. Mutual information was generally found to optimize in about one third the time required by correlation.
Robust genetic algorithm approach to modelling and control

The paper deals with robust intelligent control of linear dynamical systems using algebraic polynomial theory in combination with the genetic algorithms (GA). It shows that the conventional robust polynomial synthesis approach can be successfully modified so as to improve performance by applying genetic algorithms for tuning controller parameters. A general algorithm has been developed for optimal polynomial controller tuning that enables to generate optimal and robust control actions for both SISO and MIMO systems. Moreover, the proposed methodology guarantees finding global optimum and enables achieving a higher performance compared with the conventional approaches. The proposed robust intelligent algorithm involving the intelligent searching procedure has been tested on a case study (control of a servo system with a changing momentum of inertia). Obtained results verify the possibility to improve the performance using combination of a polynomial algebraic controller and a genetic algorithm.
A Review of Computer Vision Using Ant Colony Optimization

—Reliable feature recognition is necessary in broad fields of computer vision and image processing. Edges often act as primary artifacts of visual data. Edge detection is to mark sharp changes of the intensity or brightness of digital images. Canny edge detection and ant colony optimization detection are two essential edge detection approaches. The former is susceptible to noises presented on source images. The information loss occurs when Gaussian smoothing is used to improve connectivity of Canny edge detection. Edges can be also detected via other approaches. To avoid edge suppression and feature deformity, ACO has been proposed for edge and contour detection against false detection, by which more intrinsic information will be extracted. The evolutionary computation oriented ACO scheme is a promising approach for feature capturing without the necessity of smoothing filters. It is among the most effective approaches for edge detection. However, it may give rise to broken pieces of numerous true edges occasionally. To further improve accuracy, contour tracking schemes are needed to achieve stable feature recognition. Some intelligent schemes are too complex to handle in real time, so a simple adaptive contour tracking scheme has been proposed which is combined with enhanced ACO schemes. This technology integration will result in the sufficient true edge representation together with well connected linkage, which can be easily extended to contour detection of binary, grayscale and true color images. Using quantitative metrics, an objective study is made to evaluate performance outcomes based on integration of the ACO schemes and adaptive contour tracking.
Development of TITAN XI: a quadruped walking robot to work on slopes

There are many dangerous and time-consuming construction works performed on steep slopes. In order to improve the conditions in which these works are done, the authors propose a new construction machine that is a quadruped walking robot called TITAN XI. The main objective of remote-controlled TITAN XI system is to drill the deep holes for insertion of anchor bolts or rock bolts. In this paper, we report the system and design of TITAN XI.