Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative Machine Learning with Information Fusion for Dynamic Decision Making in Diagnostic Applications

In many applications, use of all relevant data to extract more information from multiple sources of information and achieve higher accuracy in prediction is desirable. Cooperative learning is observed in human and some animal societies. Sound knowledge and information acquisition, cooperation in learning amongst multi-agent systems may result in a higher effectiveness compared to individual learning. Cooperative learning in multi agent systems is generally expected to improve both quality & speed of learning. According to survey maximum research papers focus on coordinated approach of agents. Multiple sources of data can be viewed as different, related views of the same learning problem, where dependencies between the views could potentially take on complex structures. This gives rise to interesting and challenging machine learning problems where data sources are combined for learning. This framework encompasses several data fusion tasks and related topics, such as transfer learning, multitask learning, multiview learning, and learning under covariate shift. The advantages of the multiple source learning paradigm is seen in situations where individual data sources are noisy, incomplete, and learning from more than one source can filter out problem-independent noise. Cooperative learning is an approach where one or more team of learners work together towards reaching a better understanding of a specified task. The purpose of this paper is to use this approach to describe a proposal for designing and building a cooperative machine learning system (Multi-Learning system) that contains two or more machine learners that cooperate together.
Context and Priming Effects in the Recognition of Emotion of Old and Young Listeners

The development of our ability to recognize (vocal) emotional expression has been relatively understudied. Even less studied is the effect of linguistic (spoken) context on emotion perception. In this study we investigate the performance of young (1825) and old (60-85) listeners on two tasks: an emotion recognition task where emotions expressed in a sustained vowel (/a/) had to be recognized and an emotion attribution task where listeners had to judge a neutral fragment that was preceded by a phrase that varied in speech rate and/or loudness. The results of the recognition task showed that old and young participants do not differ in their recognition accuracy. The emotion attribution task showed that young listeners are more likely to interpret neutral stimuli as emotional when the preceding speech is emotionally colored. The results are interpreted as evidence for diminished plasticity later in life.
Volatility and correlation : the perfect hedger and the fox

Why a Second Edition. What This Book Is Not About. The New Sub--Title. I Foundations. 1 Theory and Practice of Option Modelling. 2 Option Replication. 3 The Building Blocks. 4 Variance and Mean Reversion in the Real and the Risk--Adjusted Worlds. 5 Instantaneous and Terminal Correlation. II Smiles -- Equity and FX. 6 Pricing Options in the Presence of Smiles. 7 Empirical Facts about Smiles. 8 General Features of Smile--Modelling Approaches. 9 The Input Data: Fitting an Exogenous Smile Surface. 10 Quadratic Variation and Smiles. 11 Local--Volatility Models: the Derman--and--Kani Approach. 12 Extracting the Local Volatility from Option Prices. 13 Stochastic--Volatility Processes. 14 Jump--Diffusion Processes. 15 Variance--Gamma. 16 Displaced Diffusions and Generalizations. 17 No--Arbitrage Restrictions on the Dynamics of Smile Surfaces. III Interest Rates -- Deterministic Volatilities. 18 Mean Reversion in Interest--Rate Models. 19 Volatility and Correlation in the LIBOR Market Model. 20 Calibration Strategies for the LIBOR Market Model. 21 Specifying the Instantaneous Volatility of Forward Rates. 22 Specifying the Instantaneous Correlation Among Forward Rates. IV Interest Rates -- Smiles. 23 How To Model Interest--Rate Smiles. 24 Constant--Elasticity--of--Variance (CEV) Processes in the Context of the LMM. 25 Stochastic--Volatility Extensions of the LIBOR Market Model. 26 The Dynamics of the Swaption Matrix. 27 Stochastic--Volatility Extension of the LMM: Two--Regime Instantaneous Volatility. Bibliography. Index.
Influence of four major plant traits on average height, leaf‐area cover, net primary productivity, and biomass density in single‐species forests: a theoretical investigation

1. Numerous plant traits are known to influence aspects of individual performance, including rates of carbon uptake, tissue turnover, mortality and fecundity. These traits are bound to influence emergent properties of vegetation because quantities such as leaf‐area cover, average height, primary productivity and density of standing biomass result from the collective behaviour of individuals. Yet, little is known about the influence of individual traits on these emergent properties, despite the widespread use in current vegetation models of plant functional types, each of which is defined by a constellation of traits.
DCAR coding gain modeling and analysis

Network coding is a new technique to improve network capacity and reliability. COPE and DCAR are basic network coding schemes which have been proposed for opportunistic network coding in wireless networks. The performances of these coding mechanisms have been studied by simulations or experiments. There is an interest in modeling the performances of these coding schemes mathematically. In fact, analytical approach can provide quicker performance analysis and comparison between these network coding schemes. In this paper, we propose an analytical model for the DCAR coding gain. The analytical results are validated by simulations in NS-2.
Traffic Analysis and Modeling for World of Warcraft

The popularity of MMOGs (massively multiplayer online games) has grown fast. This new type of online games uses a different type of protocol and has other limitations to delay and packet loss than the classical well established games like FPSs (first person shooters). This paper focuses on the traffic patterns generated by a MMOG named WoW (World of Warcraft). We analyzed IP layer information like packet size and rate from network traces and user level information like session durations. Finally we present a simple synthetic traffic generator for WoW traffic clients.
Nonlinear Model Predictive Control of Dimethyl Ether Combustion in a Jet Stirred Reactor

Abstract This work focuses on the nonlinear control of instabilities in the combustion of a diluted dimethyl ether (DME) / air mixture under low temperature conditions. A nonlinear model predictive control (NMPC) is utilized to stabilize the combustion in simulation with the aim to specify minimum actuation dynamic requirements and develop control strategies for an existing experimental chemical reactor.
Robust Method for Noisy Image Segmentation

A major problem in noisy image processing is the effective segmentation of its components. In this paper, we are proposing a K Medoid clustering algorithm for noisy image segmentation, which is able to segment all types of noisy images efficiently. As the presented clustering algorithm selects the centroids randomly hence it is less sensitive , to any type of noise as compare to other clustering algorithms. To prove this we will present experimental results on various images, effected by different noises, to demonstrate efficiency of the proposed method for segmentation of noisy image. Keywords— Colour image segmentation, Image noise, PSNR, K Medoids.
Static Pricing of Financial Assets

We maximize the expected utility of the terminal wealth of an investor with exponential utility. The investor trades today on a set of hedging instruments with the goal of mitigating the risk on a liability committed to at some time in the future. We show that such a static portfolio allocation problem may be viewed as a game against the market: In this game, the market chooses the probability measure that maximizes the investor’s (adjusted) expected loss. The investor thereafter is left with selecting the strategy that minimizes the damaging effect of the market choice. The allocation problem has an answer if and only if there exist a static risk –neutral probability under which the discounted expected value of hedging instruments is equal to their price today. The static risk neutral probability is analogous to its continuous counterpart although they show some differences. With additional conditions on hedging instruments, we can show that the solution to the static allocation problem has a limit as the risk aversion goes to infinity. This limit solution happens to be equal to the solution of the asymptotic problem i.e. the investor allocation game with an infinitely risk averse investor. The beauty of the asymptotic problem relies on the fact that it is free from the subjective risk aversion parameter. This allow us to introduce the concept of static hedge as the asymptotic portfolio. With the notion of static hedge comes the static price defined as the cost of setting up the asymptotic portfolio plus any reserve needed to cover the maximum potential loss which is guaranteed to be at its lowest through the static hedge. Questions: contact Dr. Natali Hritonenko nahritonenko@pvamu.edu
Asset Prices, Financial Imbalances and Monetary Policy: Are Inflation Targets Enough?

On 28-29 March 2003, the BIS held a conference on "Monetary stability, financial stability and the business cycle". This event brought together central bankers, academics and market participants to exchange views on this issue (see the conference programme and list of participants in this document). This paper was presented at the conference. Also included in this publication are the comments by the discussants. The views expressed are those of the author(s) and not those of the BIS. The opening speech at the conference by the BIS General Manager and the prepared remarks of the four participants on the policy panel are being published in a single volume in the BIS Papers series.
Performance of RFID with AWGN and Rayleigh fading channels for SDR application

— Radio Frequency Identification (RFID) is currently the hottest technology in wireless communication, in which data transmission with extreme low power or even without power in tag. Software-Defined Radio (SDR) plays an important role for a wireless communications system where all the signal processing is implemented in software. In this paper, we first build up a wireless communication simulator including Gray coding, modulation, different channel models (AWGN and Rayleigh fading channels) and demodulation. Then, we test the effect of different channel models to the RFID in receiver with BER (bit error rate) plots under Quadrature Amplitude Modulation. At last, we give detail results of the performance of AWGN and Rayleigh fading channels. We will see that in AWGN channel, the data is degraded by random noise; in Rayleigh fading channel, the data is degraded by random noise and block noise.
Elevated blood plasma levels of epinephrine, norepinephrine, tyrosine hydroxylase, TGFβ1, and TNFα associated with high-altitude pulmonary edema in an Indian population

Biomarkers are essential to unravel the locked pathophysiology of any disease. This study investigated the role of biomarkers and their interactions with each other and with the clinical parameters to study the physiology of high-altitude pulmonary edema (HAPE) in HAPE-patients (HAPE-p) against adapted highlanders (HLs) and healthy sojourners, HAPE-controls (HAPE-c). For this, seven circulatory biomarkers, namely, epinephrine, norepinephrine, tyrosine hydroxylase, transforming growth factor beta 1, tumor necrosis factor alpha (TNFα), platelet-derived growth factor beta beta, and C-reactive protein (CRP), were measured in blood plasma of the three study groups. All the subjects were recruited at ~3,500 m, and clinical features such as arterial oxygen saturation (SaO2), body mass index, and mean arterial pressure were measured. Increased levels of epinephrine, norepinephrine, tyrosine hydroxylase, transforming growth factor-beta 1, and TNFα were observed in HAPE-p against the healthy groups, HAPE-c, and HLs (P<0.0001). CRP levels were decreased in HAPE-p against HAPE-c and HLs (P<0.0001). There was no significant difference or very marginal difference in the levels of these biomarkers in HAPE-c and HLs (P>0.01). Correlation analysis revealed a negative correlation between epinephrine and norepinephrine (P=4.6E−06) in HAPE-p and positive correlation in HAPE-c (P=0.004) and HLs (P=9.78E−07). A positive correlation was observed between TNFα and CRP (P=0.004) in HAPE-p and a negative correlation in HAPE-c (P=4.6E−06). SaO2 correlated negatively with platelet-derived growth factor beta beta (HAPE-p; P=0.05), norepinephrine (P=0.01), and TNFα (P=0.005) and positively with CRP (HAPE-c; P=0.02) and norepinephrine (HLs; P=0.04). Body mass index correlated negatively with epinephrine (HAPE-p; P=0.001) and positively with norepinephrine and tyrosine hydroxylase in HAPE-c (P<0.05). Mean arterial pressure correlated positively with TNFα in HAPE-p and norepinephrine in HLs (P<0.05). Receiver operating characteristic curve analysis yielded a positive predictive value for these biomarkers with HAPE (area under the curve >0.70, P<0.05). The results clearly suggest that increased plasma levels of these circulatory biomarkers associated with HAPE.
Pectoral Muscle Boundary detection - A preprocessing method for early breast cancer detection

Pectoral Muscle (PM), a significant region in Medio-Lateral Oblique (MLO) view of mammogram may adversely affect anomaly detection due to its resemblance to abnormal tissues. The removal of PM region can be considered as a prerequisite step for early breast cancer detection using mammographic images. The principal component of PM boundary component is extracted using the orientation and eccentricity property of Canny edge detected components of coarse mammographic image obtained after a multiscale decomposition technique using Laplacian Pyramid (LP). The principal component of PM boundary is extended to top and left boundaries using nearest neighbor approach. The algorithm was tested on images from the Mammographic Image Analysis Society (MIAS) database as well as mammograms obtained from a representative set of Indian populace provided by Lakeshore Hospital Kochi, India. On comparison with the PM boundary assessed by radiologists, the proposed method yielded an average false positive rate of 0.28%, average false negative rate of 3.67% and low Hausdorff distance for 83 images in mammographic database. Based on the performance analysis of the proposed algorithm, it is observed that 97% of images have an average error less than 3 mm which is promising.
Indices of the iterates of ℝ3‐homeomorphisms at fixed points which are isolated invariant sets

Let U ⊂ ℝ3 be an open set and f : U → f(U) ⊂ ℝ3 be a homeomorphism. Let p ∈ U be a fixed point. It is known that if {p} is not an isolated invariant set, then the sequence of the fixed‐point indices of the iterates of f at p, (i(fn, p))n ⩾ 1, is, in general, unbounded. The main goal of this paper is to show that when {p} is an isolated invariant set, the sequence (i(fn, p))n ⩾ 1 is periodic. Conversely, we show that, for any periodic sequence of integers (In)n ⩾ 1 satisfying Dold's necessary congruences, there exists an orientation‐preserving homeomorphism such that i(fn, p) = In for every n ⩾ 1. Finally we also present an application to the study of the local structure of the stable/unstable sets at p.
Timing and magnitude of increases in levothyroxine requirements during pregnancy in women with hypothyroidism.

BACKGROUND Hypothyroidism during pregnancy has been associated with impaired cognitive development and increased fetal mortality. During pregnancy, maternal thyroid hormone requirements increase. Although it is known that women with hypothyroidism should increase their levothyroxine dose during pregnancy, biochemical hypothyroidism occurs in many. In this prospective study we attempted to identify precisely the timing and amount of levothyroxine adjustment required during pregnancy. METHODS Women with hypothyroidism who were planning pregnancy were observed prospectively before and throughout their pregnancies. Thyroid function, human chorionic gonadotropin, and estradiol were measured before conception, approximately every two weeks during the first trimester, and monthly thereafter. The dose of levothyroxine was increased to maintain the thyrotropin concentration at preconception values throughout pregnancy. RESULTS Twenty pregnancies occurred in 19 women and resulted in 17 full-term births. An increase in the levothyroxine dose was necessary during 17 pregnancies. The mean levothyroxine requirement increased 47 percent during the first half of pregnancy (median onset of increase, eight weeks of gestation) and plateaued by week 16. This increased dose was required until delivery. CONCLUSIONS Levothyroxine requirements increase as early as the fifth week of gestation. Given the importance of maternal euthyroidism for normal fetal cognitive development, we propose that women with hypothyroidism increase their levothyroxine dose by approximately 30 percent as soon as pregnancy is confirmed. Thereafter, serum thyrotropin levels should be monitored and the levothyroxine dose adjusted accordingly.
Coordination of human and mobile manipulator formation in a perceptive reference fame

This paper presents an analysis and design method for human/robot integrated systems, especially fro the coordination of human and robot formations based on a group of distributed mobile manipulators. The key for the human/robot integrated system is to create a common motion reference that can be understood by both human and the robots in the formation. First, the perceptive reference frame is introduced and the characteristics of perceptive frame are compared with time based reference frame. Next, the stability of the system based on perceptive reference frame is investigated. The applications of perceptive reference frame to multi-agents coordination in a formation, human/mobile manipulators coordination are then discussed. Based on the perceptive reference frame, the human can be naturally integrated into the robot formation. Human intelligence can therefore be integrated with the mobility and dexterous manipulation capability of the mobile manipulators to undertake complex tasks. The robot formation is therefore able to reconfigure and thus cope with unexpected events. Experiments have been used to verify the theoretical results.
Cyclophosphamide reduces neutrophilic alveolitis in patients with scleroderma lung disease: a retrospective analysis of serial bronchoalveolar lavage investigations

Objectives: To determine whether cyclophosphamide is beneficial for patients with scleroderma lung disease (SLD). Methods: The effect of 6 months’ treatment with intravenous cyclophosphamide on the functional capacity of patients, lung function tests, high resolution computed tomography of the lungs, and cytology of bronchoalveolar lavage was evaluated in 21 patients with SLD. Results: The treatment was well tolerated and all patients completed 6 months’ treatment. Intravenous cyclophosphamide stabilised or improved the patients’ functional status and lung function tests. The extent of the lungs affected remained unchanged, as assessed with HRCT of the lungs. Patients with SLD and neutrophilic alveolitis (NA) showed greater improvement than patients with normal levels of granulocytes in the bronchoalveolar lavage fluid (BALF). Significant reduction of neutrophils was also seen in the patients with SLD and NA, whereas no significant change was seen in the level of granulocytes in patients with SLD and an initially normal percentage of granulocytes. Conclusions: Previous reports that patients with SLD with increased levels of granulocytes in BALF are more likely to benefit from treatment with intravenous cyclophosphamide are confirmed. Additionally, clinical improvement in this group of patients is accompanied by a significant decrease in the percentage of granulocytes in BALF.
Benchmarking database systems for social network applications

Graphs have become an indispensable tool for the analysis of linked data. As with any data representation, the need for using database management systems appears when they grow in size and complexity. Associated to those needs, benchmarks appear to assess the performance of such systems in specific scenarios, representative of real use cases. In this paper we propose a microbenchmark based on social networks. This includes a data generator that synthetically creates social graphs, and a set of low level atomic queries that model parts of the behavior of social network users. In order to understand how different data management paradigms are stressed, we execute the benchmark over five different database systems representing graph (Dex and Neo4j), RDF (RDF-3X) and relational (Virtuoso and PostgreSQL) data management. We conclude that reachability queries are those that put all the database systems into more difficulties, justifying themselves, and making them good candidates for more complex benchmarks.
Bengali word embeddings and it's application in solving document classification problem

In this paper, we present Bengali word embeddings and it's application in the classification of news documents. Word embeddings are multi-dimensional vectors that can be created by exploiting the linguistic context of the words in large corpus. To generate the embeddings, we collected Bengali news document of last five years from the major daily newspapers. Word embeddings are generated using the Neural Network based language processing model Word2vec. We use the vector representations of the Bengali words to cluster them using K-means algorithm. We show that those clusters can be used directly to perform various natural language processing task by solving the problem of Bengali news document classification. We use the Support Vector Machine (SVM) for the classification task and achieve ∼91% F1-score. The accuracy of our method demonstrates that our word embeddings could capture the semantics of word from the respective context correctly.
Properties and origins of protein secondary structure.

Proteins contain a large fraction of regular, repeating conformations, called secondary structure. A simple, generic definition of secondary structure is presented which consists of measuring local correlations along the protein chain. Using this definition and a simple model for proteins, the forces driving the formation of secondary structure are explored. The relative role of energy and entropy are examined. Recent work has indicated that compaction is sufficient to create secondary structure. We test this hypothesis, using simple nonlattice protein models.
Selective dysregulation of the FcγIIB receptor on memory B cells in SLE

The inappropriate expansion and activation of autoreactive memory B cells and plasmablasts contributes to loss of self-tolerance in systemic lupus erythematosus (SLE). Defects in the inhibitory Fc receptor, FcγRIIB, have been shown to contribute to B cell activation and autoimmunity in several mouse models of SLE. In this paper, we demonstrate that expression of FcγRIIB is routinely up-regulated on memory B cells in the peripheral blood of healthy controls, whereas up-regulation of FcγRIIB is considerably decreased in memory B cells of SLE patients. This directly correlates with decreased FcγRIIB-mediated suppression of B cell receptor–induced calcium (Ca2+) response in those B cells. We also found substantial overrepresentation of African-American patients among those who failed to up-regulate FcγRIIB. These results suggest that the inhibitory receptor, FcγRIIB, may be impaired at a critical checkpoint in SLE in the regulation of memory B cells; thus, FcγRIIB represents a novel target for therapeutic interventions in this disease.