Miracle-dz/UniFAR-FTUs huggingface dataset:
Increased Toll-Like Receptor 2 Expression in Peptidoglycan-Treated Blood Monocytes Is Associated with Insulin Resistance in Patients with Nondiabetic Rheumatoid Arthritis

The close relationship between increased TLR-2 expression in blood monocytes and insulin resistance in RA patients is shown in this study. Traditional risk factors for metabolic disorders, including the waist circumstance, body mass index (BMI), triglyceride (TG), and ratio of TG to high density lipoprotein (HDL) cholesterol, were closely correlated with HOMA (homoeostasis model assessment) index in patients with nondiabetic RA. Expressions of TLR2 in peripheral blood monocytes, following stimulation with peptidoglycan which is known as a TLR2 agonist, were closely correlated with the HOMA index, TNF-α, and IL-6 concentrations. Accordingly, TLR-2 receptor and its related inflammatory cytokines could be potential therapeutic targets in managing insulin resistance in RA patients.
Refining the MOND Interpolating Function and TeVeS Lagrangian

The phenomena customarily described with dark matter or modified Newtonian dynamics (MOND) have been argued by Bekenstein to be the consequences of a covariant scalar field, controlled by a free function [related to the MOND interpolating function (g/a0)] in its Lagrangian density. In the context of this relativistic MOND theory (TeVeS), we examine critically the interpolating function in the transition zone between weak and strong gravity. Bekenstein's toy model produces a that varies too gradually, and it fits rotation curves less well than the standard MOND interpolating function (x) = x/(1 + x2)1/2. However, the latter varies too sharply and implies an implausible external field effect. These constraints on opposite sides have not yet excluded TeVeS, but they have made the zone of acceptable interpolating functions narrower. An acceptable "toy" Lagrangian density function with simple analytical properties is singled out for future studies of TeVeS in galaxies. We also suggest how to extend the model to solar system dynamics and cosmology.
BioMoby web services to support clustering of co-regulated genes based on similarity of promoter configurations

UNLABELLED Here we present a computational protocol to analyze the promoter regions of a given set of co-expressed genes, and its implementation through the use of Web services technologies. This protocol aims to cluster a set of co-regulated genes in subsets of genes showing similar configurations of transcription factor binding sites. All the steps of this protocol have been developed as web services that are compliant with BioMoby specifications. AVAILABILITY {http://genome.imim. es/cgi-bin/moby/GeneClustering_DataSubmission. cgi}. SUPPLEMENTARY INFORMATION Supplementary data are available at {http://genome.imim. es/webservices/}
Economic modeling of urban pollution and climate policy interactions

Economic Modeling of Urban Pollution and Climate Policy Interactions By Ardoin Valpergue de Masin Submitted to the Department of Civil and Environmental Engineering On January 17, 2003 In Partial Fulfillment of the Requirements for the Degrees of Master of Science in Civil and Environmental Engineering Climate change and urban air pollution are strongly connected since they are both partly originated by fossil fuel burning. Carbon policies certainly have impacts on air pollution since one of their consequences is a structural change in fuel consumption. Similarly, a policy aiming at reducing urban pollution certainly has impacts on climate change. This thesis utilizes the MIT Emission Prediction and Policy Analysis (EPPA) model to study the interrelationships between these two types of policies. By focusing on particulate matter (PM) as the main and most harmful urban pollutant, this thesis develops a methodology to account for end-of-pipe abatement opportunities for PM within the EPPA model, using engineering data for abatement costs. It then utilizes this new capability to account for climate change and air pollution policies interactions in two different ways. It first develops a methodology to estimate the gains that can be generated by jointly implementing policies on both greenhouse gases and particulate matter. The cost savings from such a joint policy can be measured by subtracting the welfare cost of the joint policy from the theoretical sum of the costs of the two separate policies. Taking the U.S. as an example, Kyoto with trading as a climate policy and maintaining PM at their current level as an urban policy, I find the savings to be less than 5% of the total costs of implementing the policies separately. This thesis then looks at the pollution impact of a climate policy on pollutants that have both climate and air pollution effects. Using both an analytical model and an empirical example, I show that the introduction of a trading system for one pollutant, while lowering costs, can worsen emissions of another pollutant in some cases. The empirical example involves a hypothetical policy where black carbon, one of the components of PM, is controlled for climate purposes. With a trading system introduced in BC between the sectors of the economy both for the U.S. and the E.U., I find that the total particulate matter emissions increases in the U.S. while it decreases in the E.U. Thesis Supervisor: John M. Reilly Title: Senior Research Scientist Thesis Reader: David H. Marks Title: Morton and Claire Goulder Family Professor of Engineering Systems & Civil and Environmental Engineering
Farkas-Type Results With Conjugate Functions

We present some new Farkas-type results for inequality systems involving a finite as well as an infinite number of convex constraints. For this, we use two kinds of conjugate dual problems, namely an extended Fenchel-type dual problem and the recently introduced Fenchel--Lagrange dual problem. For the latter, which is a "combination" of the classical Fenchel and Lagrange duals, the strong duality is established.
Stanford University Unstructured (SU 2 ): An open-source integrated computational environment for multi-physics simulation and design

This paper describes the history, objectives, structure, and current capabilities of the Stanford University Unstructured (SU 2 ) tool suite. This computational analysis and design software collection is being developed to solve complex, multi-physics analysis and optimization tasks using arbitrary unstructured meshes, and it has been designed so that it is easily extensible for the solution of Partial Differential Equation-based (PDE) problems not directly envisioned by the authors. At its core, SU 2 is an open-source collection of C++ software tools to discretize and solve problems described by PDEs and is able to solve PDE-constrained optimization problems, including optimal shape design. Although the toolset has been designed with Computational Fluid Dynamics (CFD) and aerodynamic shape optimization in mind, it has also been extended to treat other sets of governing equations including potential flow, electrodynamics, chemically reacting flows, and several others. In our experience, capabilities for computational analysis and optimization have improved considerably over the past two decades. However, the ability to integrate the resulting software packages into coupled multi-physics analysis and design optimization solvers has remained a challenge: the variety of approaches chosen for the independent components of the overall problem (flow solvers, adjoint solvers, optimizers, shape parameterization, shape deformation, mesh adaption, mesh deformation, etc) make it difficult to (a) expand the range of applicability to situations not originally envisioned, and (b) to reduce the overall burden of creating integrated applications. By leveraging well-established object-oriented software architectures (using C++) and by enabling a common interface for all the necessary components, SU 2 is able to remove these barriers for both the beginner and the seasoned analyst. In this paper we attempt to describe our efforts to develop SU 2 as an integrated platform. In some senses, the paper can also be used as a software reference manual for those who might be interested in modifying it to suit their own needs. We carefully describe the C++ framework and object hierarchy, the sets of equations that can be currently modeled by SU 2 , the available choices for numerical discretization, and conclude with a set of relevant validation and verification test cases that are included with the SU 2 distribution. We intend for SU 2 to remain open source and to serve as a starting point for new capabilities not included in SU 2 today, that will hopefully be contributed by users in both academic and industrial environments.
An integral version of Shor's factoring algorithm

We consider a version of Shor's quantum factoring algorithm such that the quantum Fourier transform is replaced by an extremely simple one where decomposition coefficients take only the values of $1,i,-1,-i$. In numerous calculations which have been carried out so far, our algorithm has been surprisingly stable and never failed. There are numerical indications that the probability of period finding given by the algorithm is a slowly decreasing function of the number to be factorized and is typically less than in Shor's algorithm. On the other hand, quantum computer (QC), capable of implementing our algorithm, will require a much less amount of resources and will be much less error-sensitive than standard QC. We also propose a modification of Coppersmith' Approximate Fast Fourier Transform. The numerical results show that the probability is signifacantly amplified even in the first post integral approximation. Our algorithm can be very useful at early stages of development of quantum computer.
The effects of ventromedial hypothalamic lesions on food intake and alimentary instrumental conditioned reflexes in dogs.

There is considerable evidence that the ventromedial part of hypotha-lamus is an important part of the alimentary system playing the role of the satiety center. Several experiments have shown that bilateral lesions of the ventromedial hypothalamic nucleus produce marked overeating and lead to obesity. Conversely electrical stimulation of this area by means of chronically implanted electrodes inhibits eating (Hoebel and Teitelbaum 1962, Krasne 1962). Although dogs were the first experimental objects in which the observations concerning the role of the hypothalamus in obesity were made (Bailey and Bremer 1921, Heinbecker et al. 1944, and others), further experiments were carried out almost exclusively on other species such as rats, rabbits, sheep, goats and monkeys. In our previous reports (Roi-kowska and Fonberg 1970, Glavcheva et al. 1970) it was demonstrated that the lateral hypothalamus plays the role of a feeding center also in dogs. Besides supporting the studies of other authors on different species, the experiments on dogs furnished some new data. For example, the vomiting symptom, which as a rule accompanied the aphagia or hypo-phagia syndrom in our experiments, was not described by other authors. We also found various changes in instrumental performances to the conditioned stimuli which were not observed in other species. Therefore, it was interesting to study the role of the ventromedial nucleus of hypo-thalamus on dogs and to ascertain whether it is really a satiation center. As the dog is a perfect subject for instrumental training, we were also interested in studying the motivational changes following hypothalamic
What aspects of body fat are particularly hazardous and how do we measure them?

Numerous techniques are available to estimate body composition and fat distribution, and the method to use will depend on the aim of the study, economic resources, availability, time, and sample size. 6–8 Multi-compartment models, such as underwater weighing, dilution techniques and dual-energy X-ray absorptiometry (DXA) are all reliable methods to obtain accurate measures of total body fat. However, because of their costs in terms of time andmoney, thesemethods are not practical in large epidemiological studies and for routine clinical use. In these situations, body mass index (BMI) is often used and assumed to represent the degree of body fat. BMI, however, does not distinguish between fat mass and lean (non-fat) mass. For example, well-trained body builders have a very low percentage of body fat, but their BMI may be in the overweight range because of their large lean (muscle) mass. In addition, in the elderly and non-Caucasian populations, the relationship between BMI and body fatness may be different as compared with younger Caucasian populations. 9–14 Another potential limitation of the BMI is that the distribution of fat over the body is not captured. Many studies have shown that an abdominal fat distribution, independent of overall obesity, is associated with metabolic disturbances and increased disease risk. 15–23 An increased abdominal fat accumulation is largely caused by the accumulation of visceral (or intraabdominal) fat (for distinction of these fat depots, see Figure 1). Owing tometabolic differences between different fat depots, they differ in their role of predicting metabolic disturbances and diseases. Table 1 summarizes the capability of the most commonly used methods to assess total adiposity and fat distribution. Abdominal obesity is usually assessed by the easily measured waist circumference, the waist-to-hip circumference ratio (WHR), or the less-commonly used sagittal abdominal diameter (SAD). By the use of sophisticated imaging techniques, such as magnetic resonance imaging (MRI) and computed tomography (CT), different fat depots can be distinguished at the waist level, and it has been shown that in particular the visceral fat depot is associated with metabolic disease risk. 24–30 Because the SAD or waist circumference alone are more strongly correlated with visceral fat than the WHR, 31–35 guidelines tend to focus onwaist circumference to estimate disease risk as suggested by Lean et al. 36 These widely used cut-points (i.e. 102 cm formen and 88 cm for women) were originally based on a replacement of the classification of BMI, 36 but other cut-points have also been suggested on the basis of relationships with visceral fat area. 37
Open Rating Systems

In the ofﬂine world, we look to the people we trust and those they trust for reliable information. In this paper, we present a computational model of this phenomenon and show how it can be used to identify high quality content in an Open Rating System, i.e., a system in which any user can rate content. We present a case study (Epinions.com) of a system based on this model and describe a new platform called PeopleNet for harnessing this phenomenon in an open distributed fashion.
Cooperative Regulation of Non-Small Cell Lung Carcinoma by Nicotinic and Beta-Adrenergic Receptors: A Novel Target for Intervention

Lung cancer is the leading cause of cancer death; 80–85% of lung cancer cases are non-small cell lung cancer (NSCLC). Smoking is a documented risk factor for the development of this cancer. Although nicotine does not have the ability to initiate carcinogenic events, recent studies have implicated nicotine in growth stimulation of NSCLC. Using three NSCLC cell lines (NCI-H322, NCI-H441 and NCI-H1299), we identified the cooperation of nicotinic acetylcholine receptors (nAChRs) and β-adrenergic receptors (β-ARs) as principal regulators of these effects. Proliferation was measured by thymidine incorporation and MTT assays, and Western blots were used to monitor the upregulation of the nAChRs and activation of signaling molecules. Noradrenaline and GABA were measured by immunoassays. Nicotine-treated NSCLC cells showed significant induction of the α7nAChR and α4nAChR, along with significant inductions of p-CREB and p-ERK1/2 accompanied by increases in the stress neurotransmitter noradrenaline, which in turn led to the observed increase in DNA synthesis and cell proliferation. Effects on cell proliferation and signaling proteins were reversed by the α7nAChR antagonist α-BTX or the β-blocker propranolol. Nicotine treatment also down-regulated expression of the GABA synthesizing enzyme GAD 65 and the level of endogenous GABA, while treatment of NSCLC cells with GABA inhibited cell proliferation. Interestingly, GABA acts by reducing β-adrenergic activated cAMP signaling. Our findings suggest that nicotine-induced activation of this autocrine noradrenaline-initiated signaling cascade and concomitant deficiency in inhibitory GABA, similar to modulation of these neurotransmitters in the nicotine-addicted brain, may contribute to the development of NSCLC in smokers. Our data suggest that exposure to nicotine either by tobacco smoke or nicotine supplements facilitates growth and progression of NSCLC and that pharmacological intervention by β blocker may lower the risk for NSCLC development among smokers and could be used to enhance the clinical outcome of standard cancer therapy.
Training Reinforcement Neurocontrollers Using the Polytope Algorithm Training Reinforcement Neurocontrollers Using the Polytope Algorithm

A new training algorithm is presented for delayed reinforcement learning problems that does not assume the existence of a critic model and employs the polytope optimization algorithm to adjust the weights of the action network so that a simple direct measure of the training performance is maximized. Experimental results from the application of the method to the pole balancing problem indicate improved training performance compared with critic-based and genetic reinforcement approaches. Abstract A new training algorithm is presented for delayed reinforcement learning problems that does not assume the existence of a critic model and employs the polytope optimization algorithm to adjust the weights of the action network so that a simple direct measure of the training performance is maximized. Experimental results from the application of the method to the pole balancing problem indicate improved training performance compared with critic-based and genetic reinforcement approaches.
HOLA: Heuristic and opportunistic link selection algorithm for energy efficiency in Industrial Internet of Things (IIoT) systems

Internet of Things (IoT) promises to be a key enabler in Smart Manufacturing and Smart Supply Chain. The IoT systems are responsible for enabling and improving the operational efficiencies of factories, plant floors, including assembly plants. These systems are characterized by reliable sensing and reporting of multiple parameters within the factory floor. Such sensing activities offer safe, efficient and optimized performance of not only the machines manufacturing the products, but also the workforce operating them. Industrial IoT (IIoT) systems could suffer from high and uneven energy consumption due to the nature of the network deployment. Such behavior is unacceptable as it not only increases the carbon footprint of the plant, but also makes the planned maintenance of IoT devices for battery replacement a huge challenge. In this paper, we propose a heuristic and opportunistic link selection algorithm, HOLA, which not only reduces the overall energy consumption of the IoT network but also balances it across the network. HOLA achieves this energy-efficiency by opportunistically offloading the IoT device data to smart-devices being carried by the workforce in the factory settings. Further, these smart-devices with multiple radio links such as Bluetooth, Wi-Fi, and 3G/4G LTE heuristically determine the best link to transmit the data to the Cloud based on the quality and energy cost of the link. Our experimental and simulation studies validate that HOLA can improve the energy efficiency of IIoT systems by reducing the overall energy consumption and balancing it across the network.
Performance Analysis of cdma 2000 Wireless Standard Error Correcting Codes

Third Generation Partnership Project-2 proposed cdma2000 standards, which offers two error correcting coding techniques, Convolutional Codes and Turbo Codes. In this paper we analyze the encoding and decoding techniques of the convolutional codes of cdma2000 standards. The performance, in the form of BER (Bit Error Rate) vs. 0 / b E N (bit energy per noise spectral ratio), by varying code rate, frame size, number of decoding iteration of the standardized turbo codes is shown. It is found that if architectural components of turbo codes is changed, not only the BER performance but also the decoding delay and throughput are changed. Results, presented in this paper, facilitate the service provider to trade off among delay, throughput and BER performance as per its requirement.
Denoising Nonlinear Time Series by Adaptive Filtering and Wavelet Shrinkage: A Comparison

Time series measured in real world is often nonlinear, even chaotic. To effectively extract desired information from measured time series, it is important to preprocess data to reduce noise. In this Letter, we propose an adaptive denoising algorithm. Using chaotic Lorenz data and calculating root-mean-square-error, Lyapunov exponent, and correlation dimension, we show that our adaptive algorithm more effectively reduces noise in the chaotic Lorenz system than wavelet denoising with three different thresholding choices. We further analyze an electroencephalogram (EEG) signal in sleep apnea and show that the adaptive algorithm again more effectively reduces the Electrocardiogram (ECG) and other types of noise contaminated in EEG than wavelet approaches.
Blondie24, Playing at the Edge of AI (Book Review)

Computer science has failed abysmally at producing machines which display intelligence. According to Fogel, the last 50 years of effort in artificial intelligence have been on the wrong track, leaving us no closer to the goal than when we started. The wrong track has been the attempt to make the computer imitate our behavior. Scientists striving to build an artificial intelligence load the computer with knowledge on a chosen topic, along with an algorithm to do the associated task. The hope is that the computer will equal or surpass our intelligence for that subject. This approach dates back to the Turing Test, which Fogel points out has been misquoted and misinterpreted almost from day one. Misquoted or not, the Turing Test has a computer pretend to be human, and this paradigm became a signpost saying that the road to artificial intelligence is through mimicry of human behavior. According to Fogel, however, that path leads only to an illusion of intelligence — for example the kind of wooden intelligence exhibited by Deep Blue. If imitation of human intelligence has not led to machine intelligence, then what will? What is intelligence? Fogel is critical in general of researchers in this field for skirting this last question. He believes that if the field of artificial intelligence had started with a proper definition of intelligence then there would have been a better chance of creating it. That is common sense — knowing what you are trying to build is crucial. Fogel therefore gives the following definition of intelligence.
An FCM-based method to recognize and extract ripe tomato for harvesting robotic system

In harvest robotic system with vision process, extracting ripe fruit from uncertain background is an important issue. In this paper, an FCM (Fuzzy C-Means)-based method combining with mathematical morphology is proposed, while tomato images getting from greenhouse are used to verify the proposed method. The image getting from the vision sensor is color image in our system. Therefore, CIE L*a*b* color space is selected to express the color image in this proposed method at first. Then, the segmentation for the effective color feature component is made using FCM segmentation method. After that, the component with the desired characteristics can be obtained and transferred into binary image for further processing. Lastly, the mathematical morphology method with geometric characteristic is used to extract the largest connected component as the ideal result, and to mark the center and bound rectangle of the recognized fruit. Experiment results indicate that the proposed method achieved good performance.