Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining MEDLINE for Similar Genes and Similar Drugs

Hypothesis generation, a crucial initial step for making scientific discoveries, relies on prior knowledge, experience and intuition. Chance connections made between seemingly unrelated concepts sometimes turn out to be fruitful. A key goal in text mining is to assist in this process by automatically discovering a small set of interesting hypotheses from a suitable text collection. We focus on text mining in the biomedical domain using MEDLINE, the database produced by the National Library of Medicine with more than 12 million citations. Our overall goal is to build applications that mine MEDLINE for novel concept connections and thereby support scientists in hypothesis discovery. In this paper we first present concept profiles as a mechanism for generating concept representations from text collections. There are several advantages offered by concept profiles. They can be as current as the text database or they can be generated from temporal subsets. Profiles may be restricted to particular views and also they may be generated for concepts that are as complex as needed. We then show how concept profiles may be used to identify similar concepts. In particular, we present experiments where concept profiles are used to identify genes that are associated with the same disease and drugs that are functionally similar.
A novel telerobotic method for human-in-the-loop assisted grasping based on intention recognition

In this work, we present a methodology for enabling a robot to identify an object and grasp configuration of interest and assist the human teleoperating the robot, to grasp the object. The identification is carried out in real-time by detecting the motion intention of the human as they are teleoperating the remote robotic arm towards the object and the grasp configuration. Simultaneously, depending on the detected object and grasp configuration, the human user is assisted to translate and orient the remote arm gripper in order to preshape and grasp the object. The complete process occurs with the human teleoperating the arm, and without them having to interact with another interface. Motion intention recognition is carried out by using Hidden Markov Models (HMMs), trained offline by preshape trials performed by a skilled teleoperator. The environment is unstructured and comprises of a number of objects, each with multiple grasp configurations. Experimental tests on healthy human subjects have validated our intention recognition based assistance method. They show that the method allows objects to be grasped and placed 48% faster, and with much ease compared to unassisted teleoperation. Moreover, we have proved that the model for intention recognition, trained by a skilled teleoperator, can be used by novice users to efficiently execute a grasping task in teleoperation.
NO‐ARMAGEDDON MEASURE FOR ARBITRAGE‐FREE PRICING OF INDEX OPTIONS IN A CREDIT CRISIS

In this work, we consider three problems of the standard market approach to credit index options pricing: the definition of the index spread is not valid in general, the considered payoff leads to a pricing which is not always defined, and the candidate numeraire for defining a pricing measure is not strictly positive, which leads to a nonequivalent pricing measure. We give a solution to the three problems, based on modeling the flow of information through a suitable subfiltration. With this we consistently take into account the possibility of default of all names in the portfolio, that is neglected in the standard market approach. We show on market inputs that, while the pricing difference can be negligible in normal market conditions, it can become highly relevant in stressed market conditions, like the situation caused by the credit crunch.
Method on Change Impact Analysis for Object-Oriented Program

Software changes are inevitable during the process of software evolution. To accommodate the changes in the software process, it is necessary to analyze the impacts of the changes. Software change impact analysis (CIA) is a key technique for identifying unpredicted and potential effects caused by changes made to software. CIA allows developers assessing the possible effects of a change, which plays an important role in software maintenance. In this paper, we present the static CIA technology based on program dependence graph (PDG) through analyzing possible change impacts for Object-Oriented source code. An analysis prototype tool for C++ program is implemented. The experimental results show that the method is effective.
Low-Complexity Factor Graph Receivers for Spectrally Efficient MIMO-IDMA

Interleave-division multiple access (IDMA) has recently been introduced as an attractive alternative to CDMA. IDMA employs user-specific interleavers combined with low-rate channel coding for user separation. In this paper, we consider a MIMO-IDMA system with increased spectral efficiency due to the use of higher-order symbol constellations. Based on a factor graph framework and the sum-product algorithm, we develop an iterative turbo multiuser receiver. Gaussian approximations for certain messages propagated through the factor graph lead to a complexity that scales only linearly with the number of users. To further reduce complexity, we introduce a selective message update scheme. Numerical simulations demonstrate the performance of the proposed receiver algorithms.
Capital flows and credit booms in emerging market economies

Private capital began flowing back to emerging market economies (EMEs) in 2002 and continued to mid-2006. In parallel, most of these countries also witnessed rapid growth in bank credit to the private sector (BCPS). This paper seeks to determine whether this strong credit expansion reflects financial deepening or excess liquidity. In the first case, this phenomenon forms part of an economic catch-up process. In the second, the main emphasis is on the potential weakness of domestic banking systems and increased macroeconomic vulnerabilities of the concerned countries. Capital inflows tend to exacerbate these risks, such that they often coincide with credit booms. Depending on the observation period and the sample of emerging countries, between 40% and 60% of credit booms took place at a time when capital inflows were high. However, the linkage between credit booms and banking and financial crises is weaker, insofar as only 6%-20% of credit booms lead to a crisis. To explore the role of capital inflows in the observed credit expansion in EMEs, this article presents an econometric analysis of a 27-country sample over the last four years. A two-stage approach is taken: first, countries that have experienced excessive growth in bank credit to the private sector are identifi ed; second, the causality relationship between capital inflows and bank credit in these countries is examined. The main findings suggest that of the 27 EMEs, which on the whole recorded strong capital inflows over the last four years, just nine experienced a credit boom. Moreover, there does not appear to be a clear-cut causality relationship between capital inflows and BCPS. It is therefore difficult to draw general conclusions as regards financial stability. In some countries, a combination of substantial capital infl ows and credit booms may generate risks of instability if the external financing causes profound macroeconomic and financial imbalances. In other countries, massive capital infl ows and rapid credit growth may be linked to a healthier process of financial deepening.
Performance evaluation of a binary control technique for brushless dc motor drives

With the availability of effective, yet low cost speed/torque regulators, brushless dc (BLDC) motor drives have now become very popular in electric drives. One promising controller [1] uses the binary (two-state) control scheme of current conduction angle. However, the scheme was limited to one load torque and a narrow speed range. Because the scheme was implemented on PSIM software, it was easy to verify/compare the results. In this paper, the simulation studies are further extended to the broad range of speed-torque combinations. In addition to percentage speed ripple, a performance index (percentage steady state error in speed) based on average and desired speed is defined. Both of these indices are calculated for a number of speed ranges keeping the load torque constant. The performance indices are repeatedly calculated for the same number of speed ranges by keeping the load torque constant at different values. Variations of the performance indices with speed and torque provide definite patterns which can be used to meet the system design for specific applications.
Stretching-Robust Laplace Spectral Descriptor for Non-rigid 3D Shape Retrieval

This paper proposes a framework based on harmonic mean normalized Laplace-Beltrami spectral descriptor for non-rigid 3D shape retrieval. A series of experiments show harmonic mean normalization is suited to classification of stretched shapes, and is robust to isometric transformation, holes, local scaling, noise, shot noise and sampling. To better distinguish among shapes with fine or rough details, weighting method and fusion method are employed. We use the two methods to reduce the adverse impact of high frequency when the shapes with fine and rough details are distinguished. In the experiments, three 3D shape retrieval benchmarks are used, and our approach has better performance than other state-of-the-art methods on both retrieval accuracy and time performance for stretched non-rigid 3D shapes.
Capacity of UWB networks supporting multimedia services

We analyze the capacity of UWB networks supporting multimedia services by calculating the number of multimedia connections that can be supported in a UWB network based on IEEE 802.15. 3 Medium Access Control (MAC) protocol, taking into consideration the overheads from different layers. We then propose how to increase the capacity by improving the MAC protocol design. To fully explore the potential of UWB technologies which favor concurrent transmissions if the interference is appropriately controlled, we study the capacity of cellular-like UWB networks. Our findings, which should provide important guidelines for UWB network planning, are a) the inter-cell interference of UWB networks is closely related to the Riemann Zeta function, and to guarantee the bounded inter-cell interference of UWB networks, the path loss exponent α must be larger than 2; b) the total throughput in an area is a concave function of the cell size; c) the best distance between adjacent cells is a function of path loss exponent, background noise level, and cross-correlation of the target signal and the interfering signal; and d) with the optimal cell size, a single flow's throughput is reduced by 2/α due to inter-cell interference. Simulation results are given to demonstrate the accuracy of the analysis.
Reconstruction of Echo Planar Images used in Functional MRI

Functional magnetic resonance imaging (fMRI) provides high resolution maps of neural activity. This is possible due to small variations in magnetic susceptibility, caused by local blood oxygenation changes in active brain areas. To measure these changes with high temporal resolution, a fast image acquisition sequence is required. Echo Planar Imaging (EPI) is such an acquisition method, with capability of acquiring images within fractions of a second. However, EPI suffers from various image degradations that must be compensated. In this thesis we discuss, suggest and evaluate implementations of several reconstruction algorithms for echo planar images used in functional MRI. The algorithms are evaluated with respect to their corresponding activation maps. Further, methods for correction of N/2 ghosting and geometric distortion due to B0 inhomogeneities are studied.
Multi-sample 3D face registration based on TPS transformation and linear combination model

To conquer the point-to-point registration of 3D face, we present an automatic registration method for multi-sample 3D face based on the thin-plate spline(TPS) transformation and the linear combination model. In the method, the data registration is divided into two stages. In the first stage, each sample face will be registered with the selected reference face by the TPS based non-rigid registration method to obtain the primary data registration; in the second stage, the combination model is set up based on the first stage primarily registered multi-sample data. For each sample face, matched with the combination model a similar reference face will be generated to facilitate the accurate data registration by TPS registration. To eliminate the outliers of different face samples, countermeasures are adopted in both stages of the data registration. The experiments on the BJUT-3D face database show that our method is effective for the registration of 3D face and robust to the outliers of face data.
Double Robust Semiparametric Efficient Tests for Distributional Treatment Effects under the Conditional Independence Assumption

This note describes methods to test for distributional treatment effects under the conditional independence assumption. The differences between latent outcome distributions are judged by testing hypotheses of distributional equality and stochastic dominance. Furthermore, semiparametric efficient versions of the test statistics are given. The latter test statistics are double robust, i.e., they are consistent under misspecification of either the outcome equation or the propensity score. Consistent bootstrap procedures for deriving critical values of all tests are proposed. JEL-Classification: C14, C15, C21
A pr 2 00 0 Gravitation Without Curved Space-time

A quantum-mechanical theory of gravitation is presented, where the motion of particles is based on the optics of de Broglie waves. Here the large-scale geometry of the universe is inherently flat, and its age is not constrained to < 13 Gyr. While this theory agrees with the standard experimental tests of Einstein's general relativity, it predicts a different second-order deflection of light, and measurement of the Lense-Thirring effect in the upcoming NASA experiment Gravity Probe B.
Divergence in behaviour between the European corn borer, Ostrinia nubilalis, and its sibling species Ostrinia scapulalis: adaptation to human harvesting?

Divergent adaptation to host plant species may be the major mechanism driving speciation and adaptive radiations in phytophagous insects. Host plants can differ intrinsically in a number of attributes, but the role of natural enemies in host plant specialization is often underappreciated. Here, we report behavioural divergence between the European corn borer (ECB, Ostrinia nubilalis) and its sibling species Ostrinia scapulalis, in relation to a major enemy: humans. Harvesting maize imposes selective mortality on Ostrinia larvae: those located above the cut-off line of the stalk face almost certain death. We show that ECB larvae diapause closer to the ground than those of O. scapulalis, which is sympatric but feeds mainly on weeds. The difference in diapause height results from genetically determined differences in geotactic behaviour. ECB larvae descend towards the ground specifically at harvest time, increasing their chances of surviving harvesting by about 50 per cent over O. scapulalis larvae. Natural enemies appear as a major driver of host-plant specialization in this example, stressing the need to consider ‘tri-trophic’ ecological niches to understand insect diversification. Our results also strongly suggest that geotaxis evolved as a singular instance of behavioural resistance in a major agricultural pest.
Forecasting Inflation with Monetary Aggregates

Although few would disagree that “infl ation is always and everywhere a monetary phenomenon” (Friedman 1963), the last decades have seen a diminished role assigned to money in the conduct of monetary policy. On one hand, mainstream so-called New-Keynesian monetary analysis lives in cashless economies where money demand is considered redundant given an interest rate policy (see, e.g., Woodford 2007a) or, similarly, the long-run relation between money and infl ation is seen as just one among many steady-state relations (see Galí 2002). This does not come without criticisms as steady state infl ation is taken as exogenous (the central bank target), independent of money supply (see Nelson 2008). On the other hand, issues of instability of money demand and the fact that money seems useless in forecasting infl ation (see e.g., Estrella and Mishkin 1997 for an earlier reference) contribute to the de-emphasis of the role of money in monetary policy analysis. In any case, there is broad recognition of the long-run relation between money growth and infl ation.
Sonic Nirvana : Using MEMS Accelerometers as Acoustic Pickups in Musical Instruments

Introduction MEMS (microelectromechanical systems) technology builds on the core fabrication infrastructure developed for silicon integrated circuits. Micromechanical structures are created by etching defined patterns on a silicon substrate to form sensor elements or mechanical actuators that can move fractions of a micron. Pressure sensors, one of the first high volume MEMS applications, now monitor pressure in hundreds of millions of engine manifolds and tires; and MEMS accelerometers have been used for over 15 years for airbag deployment, rollover detection, and automotive alarm systems. MEMS accelerometers are also used for motion sensing in consumer applications, such as video games and cell phones. MEMS micromirror optical actuators are used in overhead projectors, HDTVs, and digital theater presentations. In recent years, MEMS microphones have begun to proliferate the broad consumer market, including cell phones, Bluetooth headsets, personal computers, and digital cameras.
MA/MF MAC Protocol for Industrial Wireless Network and Performance Analysis

Privacy protection is one of the important topics in network security. Although a lot of work has been done, there are still some open issues and challenges that need to be addressed. Now, open and dynamic computing environments offer flexible and convenient sharing of information and services for users. Consequently, there exist a lot of different policies for privacy protection to deal with dynamic changes in each application scenario. This raises the issue of privacy policy specification. Although trust can help protect user privacy, the use of unified trust values or a simple trust rank cannot satisfy the requirement for privacy protection because different privacy may need its own trust evidence for the evaluation of trust. To solve this problem, we propose a novel approach for privacy protection based-on ontology in this paper. Our main contributions in this paper include (1) specifying privacy policies in a semantic way and (2) abstracting the policies as trust attributes for privacy ontology. In addition, our method can be used to protect sensitive policies at the same time.
Computing eigenvectors and corresponding eigenvalues with largest or smallest modulus of real antisymmetric matrix based on neural network with less scale

In this paper, we extend the neural network based approaches, which can asymptotically compute the largest or smallest eigenvalues and the corresponding eigenvectors of real symmetric matrix, to the real antisymmetric matrix case. Given any n-by-n real antisymmetric matrix, unlike the previous neural network based methods that were summarized by some ordinary differential equations (ODEs) with 2n dimension, our proposed method can be represented by some n dimensional ODEs, which can much reduce the scale of networks and achieve higher computing performance. Simulations verify the computational capability of our proposed method.
Will Social Security and Medicare Remain Viable as the U.S. Population is Aging? An Update

Yes, subject to concerns about Medicare inefficiencies and potentially self-confirming skepticism. The U.S. social security system-broadly defined to include Medicare-faces significant financial problems as the result of an aging population. But demographic change is also likely to raise savings, increase wages, and reduce interest rates, and up to a point, a growing GDP-share of medical spending is an efficient response to an aging population. Thus viability is more a political economy than an economic feasibility issue. To examine the political viability of social security, I focus on intertemporal cost-benefit tradeoffs in a median voter setting. For a variety of assumptions and policy alternatives, I find that social security should retain majority support.
Segmentation of shadow images using IR based adaptive Level set model

Images captured under non uniform lightening and illumination conditions consist of unwanted shadow regions. Segmentation of these images using conventional level set methods show improper results which is a major problem in many real time applications such as medical imaging, pattern recognition etc. In this paper we propose an adaptive Level set model by introducing a new adaptive force function on the level sets evolution based on reflectance & illumination present in the image. This method is proved to be successful in segmentation of images by excluding the shadow regions present in the images.
Bmi1 Is Down-Regulated in the Aging Brain and Displays Antioxidant and Protective Activities in Neurons

Aging increases the risk to develop several neurodegenerative diseases, although the underlying mechanisms are poorly understood. Inactivation of the Polycomb group gene Bmi1 in mice results in growth retardation, cerebellar degeneration, and development of a premature aging-like phenotype. This progeroid phenotype is characterized by formation of lens cataracts, apoptosis of cortical neurons, and increase of reactive oxygen species (ROS) concentrations, owing to p53-mediated repression of antioxidant response (AOR) genes. Herein we report that Bmi1 expression progressively declines in the neurons of aging mouse and human brains. In old brains, p53 accumulates at the promoter of AOR genes, correlating with a repressed chromatin state, down-regulation of AOR genes, and increased oxidative damages to lipids and DNA. Comparative gene expression analysis further revealed that aging brains display an up-regulation of the senescence-associated genes IL-6, p19Arf and p16Ink4a, along with the pro-apoptotic gene Noxa, as seen in Bmi1-null mice. Increasing Bmi1 expression in cortical neurons conferred robust protection against DNA damage-induced cell death or mitochondrial poisoning, and resulted in suppression of ROS through activation of AOR genes. These observations unveil that Bmi1 genetic deficiency recapitulates aspects of physiological brain aging and that Bmi1 over-expression is a potential therapeutic modality against neurodegeneration.
Decision making for remote robotic operations

Robotic systems are often used for remote operations in Department of Energy Environmental Management applications because they allow the removal of personnel from dangerous environments. Typically, these systems are operated in pure teleoperation mode by a human operator. While these systems are capable of performing many tasks, their performance can be greatly enhanced through the use of telerobotics (a combination of teleoperation, automation, and decision making). This paper describes an analytical approach to decision making for robotic systems used in remote operations. This approach utilizes redundancy in the system or the task to improve the overall system performance based on analytical criteria. The approach is illustrated by application to the dual arm telerobot at Oak Ridge National Laboratory (ORNL) and the pit viper system at Pacific Northwest National Laboratory (PNNL). In both instances, decision making clearly reduces the operator involvement in tedious tasks while improving performance.