Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive Value of Conjointly Examined IL-1ra, TNF-R I, TNF-R II, and RANTES in Patients with Primary Glomerulonephritis

Interleukin-1 receptor antagonist (IL-1ra), tumor necrosis factor soluble receptors (sTNF-R) type I and II, and regulated upon activation, normal T-cell expressed and secreted (RANTES) play an important role in the modulation of primary glomerulonephritis (GN) course. The aim of the study was to assess whether pre-treatment measurements of IL-1ra, sTNF-R, and RANTES assessed conjointly may be useful as predicting factors in patients with GN. In 84 patients (45 males and 39 female) serum concentration (pg/mL) and urinary excretion (pg/mgCr) of cytokines were measured. After 12 months of therapy with steroids and cyclophosphamide the patients were divided into two subgroups: Responders (R) and Non-Responders (NR) according to the treatment results. The urinary IL-1ra, TNF-RI and RII were significantly higher in R than NR (1,732 vs 646 with P < 0.001, 13.1 vs 6.3 with P = 0.005, and 33.6 vs 14.4 with P = 0.012). The urinary RANTES excretion was increased in NR (79.6 vs 28.5; P < 0.001). The multivariable analysis showed that if conjointly assessed, only urinary IL-1ra, TNF-R I and R II, RANTES with 85% probability pointed the feature remission (R). In conclusion, the urinary excretion of IL-1ra, TNF-R I and R II, and RANTES examined conjointly are effective in predicting favorable response to immunosuppressive treatment in patients with GN.
Comparison of Three Interpolation Techniques in Comb-Type Pilot-Assisted Channel Coded OFDM System

Doppler shifts and channel induced fading effects are more likely to induce inter carrier interference (ICI), which is the challenging research area in the orthogonal frequency division multiplexing (OFDM). This paper uses channel estimation for canceling the effect of ICI from the received signal. One dimensional frequency domain comb-type channel estimation is considered because of its low computational complexity and effective tracking ability of the fast fading channel. The channel at pilot subcarriers is estimated by using zero forcing (ZF) estimator. In this paper an improved and computationally efficient interpolation technique is proposed for the estimation of channel impulse response at the data subcarriers. Simulation results reveal that the proposed interpolation technique outperforms other one dimensional interpolation techniques. Errors induced by the channel results in degradation of the BER performance. Turbo codes have been used in addition to ZF estimator for further improving BER performance of the OFDM system. Log maximum a posteriori (Log-MAP) decoding algorithm is used for the component decoders in the iterative turbo decoder. Rayleigh fading channel in the presence of AWGN is used to evaluate the performance of the proposed OFDM system.
Fast Content-Based Packet Handling for Intrusion Detection

It is becoming increasingly common for network devices to handle packets based on the contents of packet payloads. Example applications include intrusion detection, firewalls, web proxies, and layer seven switches. This paper analyzes the problem of intrusion detection and its reliance on fast string matching in packets. We show that the problem can be restructured to allow the use of more efficient string matching algorithms that operate on sets of patterns in parallel. We then introduce and analyze a new string matching algorithm that has average-case performance that is better than the best theoretical algorithm (Aho-Corasick) and much better than the currently deployed algorithm (multiple iterations of Boyer-Moore). Finally, we implement these algorithms in the popular intrusion detection platform Snort and analyze their relative performance on actual packet traces. Our results provide lessons on the structuring of content-based handlers, string matching algorithms in general, and the importance of performance to security.
A nonatomic‐game model for timing clearance sales under competition

We deal with dynamic revenue management (RM) under competition using the nonatomic‐game approach. Here, a continuum of heterogeneous sellers try to sell the same product over a given time horizon. Each seller can lower his price once at the time of his own choosing, and faces Poisson demand arrival with a rate that is the product of a price‐sensitive term and a market‐dependent term. Different types of sellers interact, and their respective prices help shape the overall market in which they operate, thereby influencing the behavior of all sellers. Using the infinite‐seller approximation, which deprives any individual seller of his influence over the entire market, we show the existence of a certain pattern of seller behaviors that collectively produce an environment to which the behavior pattern forms a best response. Such equilibrium behaviors point to the suitability of threshold‐like pricing policies. Our computational study yields insights to RM under competition, such as profound ways in which consumer and competitor types influence seller behaviors and market conditions. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 365–385, 2014
Accurate Transistor Modeling by Three-Parameter Pad Model for Millimeter-Wave CMOS Circuit Design

This paper proposes accurate CMOS device de-embedding and modeling methods. For millimeter-wave circuit design, accurate simulation models are required. For this reason, an accurate measurement is a key technique for device characterization, and de-embedding and modeling methods are also very important. In this work, a three-parameter pad model based on L-2L de-embedding method and a transistor model with frequency and bias dependency are proposed. The pad model is derived from the assumption that the capacitance of PADs becomes constant at high frequencies. In the transistor modeling, parasitic elements are extracted mathematically. A five-stage low-noise amplifier is fabricated by 65-nm CMOS technology to confirm the accuracy of simulation, and the simulation and measurement results match well with each other.
Detection and Classification of Hard Exudates in Human Retinal Fundus Images Using Clustering and Random Forest Methods

Diabetic Retinopathy (DR) is a vascular disorder where the retina is damaged because fluid leaks from blood vessels into the retina. One of the primary lesions of diabetic retinopathy is exudates, which appear on retinal images as bright patches with various borders. In this work an image processing framework is presented to automatically detect and classify the presence of hard exudates in the human retinal fundus images. A total of 50 images have been used to detect the hard exudates from the Messidor database. Digital image processing methods help to extract the location and level of abnormalities in retinal fundus images. The contrast adaptive histogram equalization is used for preprocessing stage and Fuzzy CMeans (FCM) and K-means clustering algorithms are applied to segment the exudates in abnormal images. A set of features such as the standard deviation, mean, energy, entropy and homogeneity of the segmented regions are extracted and fed as inputs into random forest (RF) classification to discriminate between the normal and pathological image. The proposed method achieved 92.94% accuracy for early detection of DR.
Monograph Series Washback in Language Testing

This monograph summarizes recent research on language testing washback. It begins by compiling several definitions of washback and related constructs. It then poses a model of language testing washback and examines the available research related to this model. The monograph concludes with recommendations for appropriate research methods to be used in future investigations of washback.
On Shapley-Shubik Equilibria with Financial Markets 1

In this paper we extend the Shapley-Shubik model to a two period financial economy and essentially address the question of the existence of an equilibrium. More precisely, we show the existence of nice equilibria, i.e. situation in which prices for both assets and commodities are strictly positive. Even if the general lines of the proof are largely influenced by the paper of Dubey-Shubik (1978), most of the arguments are new because of the financial nature of the economy. It forces us to deal with a generalized Nash equilibrium and to proscribe the use of arguments which only works with a single cash-in-advance constraint.
Estimation of the Gravity Equation of Bilateral Trade in the Presence of Zero Flows

The gravity model is the workhorse model to describe and explain variation in bilateral trade empirically. Consistent with both Heckscher-Ohlin models and models of imperfect competition and trade, this versatile model has proven to be very successful, explaining a large part of the variance in trade flows. However, the loglinear model cannot straightforwardly account for the occurrence of zero-valued trade flows between pairs of countries. This paper investigates the various approaches suggested to deal with zero flows. Apart from the option to omit the zero flows from the sample, various extensions of Tobit estimation, truncated regression, probit regression and substitutions for zero flows have been suggested. We argue that the choice of method should be based on both economic and econometric considerations. The sample selection model appears to fit both considerations best. Moreover, we show that the choice of method may matter greatly for the results, especially if the fraction of zero flows in the sample is large. In the end, the results surprisingly suggest that the simplest solution, to omit zero flows from the sample, often leads to acceptable results, although the sample selection model is preferred theoretically and econometrically.
Distance Value Model: Geospatial Implementation of Environmental Justice

Jurisdictions that receive Federal funding must be responsive to issues of environmental justice. Environmental justice requires that protected classes (e.g., minority and low-income populations) are neither disproportionately denied the benefits of transportation projects nor subjected to the detriments of transportation projects. However, there has been very little research on the financial distribution of transportation resources as a form of environmental justice. The objective of this paper is to describe a financial model for the measurement of environmental justice that can be used by transportation planners at both metropolitan planning organizations as well as state departments of transportation in the development of both short- and long-range transportation plans. The paper begins with a review of environmental justice domains and recent research in those domains. Then the Distance Value Model is described, including its two fundamental constructs: the Ideal Distribution and the Planned Distribution. The Ideal Distribution is the proportional allocation of transportation project values to a protected class in a transportation planning area. The Planned Distribution is the allocation of project values to a class in a planning area adjusted by the distance between the class and the projects. A statistically significant difference between the Ideal and Planned Distributions may indicate environmental injustice. The paper concludes with an application of the model to data from a metropolitan planning organization in the western United States and a discussion of the results.
Detection of individual tree crowns in airborne lidar data

Laser scanning provides a good means to collect information on forest stands. This paper presents an approach to delineate single trees automatically in small footprint light detection and ranging (lidar) data in deciduous and mixed temperate forests. In rasterized laser data possible tree tops are detected with a local maximum filter. Afterwards the crowns are delineated with a combination of a pouring algorithm, knowledge-based assumptions on the shape of trees, and a final detection of the crown-edges by searching vectors starting from the trees’ tops. The segmentation results are assessed by comparison with terrestrial measured crown projections and with photogrammetrically delineated trees. The segmentation algorithm works well for coniferous stands. However, the implemented method tends to merge crowns in dense stands of deciduous trees.
Involvement of Amp Kinase in Glucose Uptake and Palmitate Oxidation in L6 Muscle Cell Cultures

AICAR (5-aminoimidazole-4-carboxamide 1-s-D-ribonucleoside) is known to activate the AMP-activated protein kinase (AMPK) in many cell types, including skeletal muscle. We showed that AICAR activated glucose uptake, fatty acid oxidation, and lactate formation by L6 skeletal muscle cell cultures. All of the actions were duplicated by adiponectin, another known activator of AMPK, demonstrating selectivity of AICAR. Moreover, AICAR and adiponectin similarly caused phosphorylation of AMPK, and its target proteins acetyl CoA carboxylase and S6Kinase. While creatine treatment of cells is known to greatly enhance creatine and creatine phosphate levels, it was proposed to paradoxically activate AMPK, and yet not affect glucose transport. However, we found creatine treatment to be without effect on glucose transport, fatty acid oxidation, or phosphorylation of AMPK or its target proteins. Unlike AICAR and adiponectin, creatine treatment stimulated glycogen formation from glucose and inhibited lactate formation. Consistent with this, we observed a diminution in phosphofructokinase expression. Thus, we conclude that creatine and creatine phosphate are not significant allosteric modulators of AMPK in intact cells. We investigated the role of AMPK in glycogen metabolism, using an inhibitor of glycogen phosphorylase. While the inhibitor enhanced glucose incorporation into glycogen, AICAR and adiponectin still diminished glycogen formation, supporting a direct action of AMPK on glycogen synthase. To probe the mechanism for adiponectin, we used siRNA constructs against adenyate kinase and LKB1 (the AMPK kinase). We concluded that adiponectin likely acts through an activation of LKB1, rather than indirectly increasing the turnover of ATP, involving adenylate kinase.
Complexity control in the topology optimization of continuum structures

A general mesh independent filter as a mean to control the complexity of topology optimization designed structures is discussed. A new mesh-independent filter, applied over the move-limits of the sequential linear programming is proposed, and it is shown that its use alleviates common problems in the continuum topology optimization, like checkerboarding, mesh dependency, as well as effects associated to non-structured meshes, like numerical anisotropy. The structural optimization formulation adopted in this work is the minimization of a penalized function of the volume, with constraints on the compliance of each load case. Aspects of this penalized objective function are discussed, and several numerical examples are shown.
A New Method of Query over Encrypted Data in Database using Hash Map

Critical business data in databases is an attractive target for attack. Therefore, ensuring the confidentiality, privacy and integrity of data is a major issue for the security of database systems. High secure data in databases is protected by encryption. When the data is encrypted, query performance decreases. In our paper we propose a new mechanism to query the encrypted data beside make a tradeoff between the performance and the security. Our mechanism will work over many data-types. We implement our work as a layer above the DBMS; this makes our method compatible with any DBMS. Our method based on replacing the select conditions on the encrypted data with another condition which is faster. The new way must have no security weak that is can't show an aspect for the plain data. The results of the experiments validate our approach.
Impact of brisk walking and aerobics in overweight women

[Purpose] Lack of physical activity and an uncontrolled diet cause excessive weight gain, which leads to obesity and other metabolic disorders. Studies have indicated that brisk walking and aerobics are the best methods for controlling and reducing weight and body mass composition. [Subjects and Methods] In this study, 45 overweight women were enrolled and divided into 3 groups. Women not involved in brisk walking or aerobics were included in group A (n = 15) as control subjects; women involved in brisk walking were in group B (n = 15); and those involved in aerobics were in group C (n = 15). [Results] This program was carried out 5 days/week for 10 weeks. Pre- and post-measurements of body mass index, waist and hip circumference, and skinfold thickness of the abdomen, subscapular area, biceps, and triceps were recorded for the women in all 3 groups. All values decreased in women who participated in brisk walking and aerobics for 10 weeks. [Conclusion] These results indicate that aerobics with diet therapy is a more effective intervention program for controlling and reducing body mass index and skinfold thickness than brisk walking with diet therapy in North Indian women.
Quantization on EEG covariance matrix images during TOVA attention test for depression disorder classification

The major depression disorder (MDD) is the mental disorder that causes patients to lose their life ability. It is important to develop a computer-aid diagnosis method based on electro-encephalography (EEG) screening. Test of variables of attention (T.O.V.A.®) was applied in this research and the surface EEG was recorded simultaneously. The proposed method quantizes covariance matrix images of EEG channel interactions by combining both approximate entropy and 2D Fourier transform methods. The higher approximate entropy values were found at MDD group and lower high-frequency components were found in the control group. Overall, the research classified MDD patients and normal population with high accuracy. The covariance matrix images from TOVA target sessions offered better distinguishability on depressive disorder patients than TOVA non-target sessions.
Speech source localization based on copula rank correlation matrix

Direction-of-arrival (DOA) estimation of a speech source has generated great interest in recent years. Traditional methods, such as the steered response power (SRP) estimator, make use of a multi-element microphone array and can perform well in the presence of moderate noises and reverberations. Those algorithms are particularly good for Gaussian source signals, while for non-Gaussian speech signals, they may not be sufficient. For such cases, copulas can be useful to measure the dependence between random variables. In this paper, we present a copula-based source DOA estimator, based on a copula rank correlation matrix constructed from the rank correlation coefficient Kendall's τ, which we call CRCM. A set of simulations and real-data experiments demonstrates the advantages of the proposed estimator over the classical SRP method.
A multi-period and multi-product optimizer for cooperative supply chains

Members in a traditional supply chain compete to reduce their individual costs. But total cost is minimized in a cooperative, or a corporate managed, supply chain. A lower average cost and a lower cost variation are achieved by cooperative individual members in the long-run. The problem is formulated and solved as an integrated flow network. Previous research is expanded to include multi-period and multi-product cooperative supply chain with possibility of holding inventory in a multi-stage, multi-member setup. A Cooperative Supply Optimizer System (CSOS), a software-based coordination mechanism, is developed for large chains. It gathers operational information from members of the supply chain, and then guides them on ordering decisions for a minimum cost of the entire supply chain. Simulation results indicate an approximately 26% reduction in total supply chain costs, utilizing this formulation over a competitive setup. As the holding costs increase, the problem decomposes into single period (Just-in-time) again. The disturbing bullwhip effect disappears in cooperative supply chains.
TREN- Turkish recognition engine for distributed applications

Turkish Recognition ENgine (TREN) is a modular, Hid- den Markov Model based (HMM-based), speaker inde- pendent and Distributed Component Object Model based (DCOM-based) speech recognition system. TREN is a two-layered system containing specialized modules that allow a fully interoperable platform including a Turkish speech recognizer, a feature extractor, an end-point de- tector and a performance monitoring module. In order to increase the recognition performance, a Turkish telephony speech database with a very large word corpus is collected and statistically the widest span of triphones representing Turkish is examined. TREN has been used to assist speech technologies which require a modular and a multithreaded speech recognizer with dynamic load sharing facilities. For the complex speech processing systems, a layered ar- chitecture which is a natural outgrowth of the client-server model, could be an effective solution concerning the prob- lems such as lack of scalability and portability. Compared with the traditional client-server model, layered architec- ture of TREN offers a natural way to separate user inter- face from the background of the hard work performed by the recognizer. TREN is composed of two layers: Cen- tral server (CS) constitutes the first layer of the system which is subjected to apply some speech processing rou- tines (feature extraction and end-point detection) to the audio files collected as an input from third party appli- cations. CS is also responsible for the authorization of a remote server (RS) with the least CPU load of the recogni- tion process (LP CP U ) as compared to the other RSs all of which constitute the second layer of TREN. Once this au- thorization is accomplished the selected RS will become ready to serve as a recognizer. This two-layered architec- ture allows RSs work in a parallel and distributed manner. Note that this architecture also gives a flexibility to in- stall or uninstall any number of machines according to the application requirements. TREN supports up to 64 simul- taneous recognitions resembling a 64-channel system.
Evaluating the Memory System Performance of Software-Initiated Inter-core LLC Prepushing

Data prefetching speculatively issue memory requests for data needed later by the main computation, and therefore can lead to increased stress on limited resources on chip multiprocessors. If not properly used, it can cause harmful effects such as cache pollution and waste of bandwidth. Therefore, accurate and fine grain measurement of the related runtime metrics is important as the first step in reducing harmful prefetches and increasing memory level parallelism on chip multiprocessors. However, the required measurement is prohibitively impossible on real machines without bringing nontrivial performance overhead and thus leading to inaccurate results. In this paper, we use cycle accurate full-system simulation to study the memory system performance of our previous proposed data prefetching technique with control of harmful prefetches on chip multiprocessors - software-initiated inter-core LLC prepushing. We modified the GEMS multiprocessor simulator to support trace-based measurement and offline analysis of MLP, DRAM BLP and their relationship with software-initiated intercore LLC prepushing. Results show that, prepushing can achieve speedups of 1.628, 1.019 and 1.032 in mst, em3d and 429.mcf, respectively. Average L2 MLP is increased by 26%, 0.3% and-1%, in mst, em3d and 429.mcf, respectively.