Miracle-dz/UniFAR-FTUs huggingface dataset:
Interannual variability in the longitudinal structure of the low‐latitude ionosphere due to the El Niño–Southern Oscillation

[1] The ratio of monthly median foF2 values between the ionosondes at Maui (20.8°N, −156°E geographic; 21.2°N, −90.4°E geomagnetic) and Yamagawa (31.2°N, 130.6°E geographic; 20.6°N, −160.9°E geomagnetic) from January 1960 to June 1993 are used to investigate interannual variability in the wave-4 longitudinal structure of the low-latitude F region ionosphere. Analysis of Global Positioning System total electron content between January 1998 and December 2008 reveals that the ratio between these two locations is a suitable proxy for the amplitude of the wave-4 longitudinal structure in the Northern Hemisphere. Significant interannual variability is present in the foF2 ratio after removing the solar cycle and intra-annual variability. The remaining variability is thought to be due, in part, to changes in atmospheric and oceanic circulations arising from the El Nino–Southern Oscillation (ENSO). Wavelet analysis reveals that similar periodicities and occurrence times exist for the foF2 ratio monthly anomalies and sea surface temperature anomalies, represented by the Oceanic Nino Index (ONI). Furthermore, the yearly ONI extreme value is well correlated with the extreme value of the foF2 ratio monthly anomalies in the subsequent 5 months. This surprising connection is attributed to changes in tropospheric convection, and hence latent heating, associated with changing sea surface temperatures due to the ENSO. Changing distributions of latent heat tidal forcing are thought to induce changes in the strength of the upward and eastward propagating diurnal tide with zonal wave number s = −3 (DE3) which subsequently produces the observed changes in the amplitude of the wave-4 longitudinal structure through modulation of the electric fields generated by the dynamo mechanism in the ionospheric E region. Our results demonstrate that there is significant interannual variability in the ionospheric wave-4 longitudinal structure and further indicate that the ENSO phenomenon represents a source of ionospheric variability which has previously not been considered.
DT- CWT sub-band partitioning for face recognition

Principal Component analysis extracts the features from the low frequency content of the face image and performs the face recognition with minimal reconstruction error. This statistical method de emphasizes the high frequency information, available to improve the recognition performance. In this paper, the face image is partitioned in to different frequency sub bands prior to PCA analysis. This prior partitioning of the face image, results in more information available for improving the performance of the PCA. Motivated by the shift invariance and Directional property of the Dual Tree Complex Wavelet transform (DT-CWT), this technique is the choice for partitioning the face images. First, the image is partitioned in to different frequency sub bands using DT-CWT, the partitioned sub bands are arranged as a column vector from low frequency to high frequency to form a novel OneS representation. Further, PCA analysis is performed. The resultant feature vectors are classified using k nearest neighbor classifier with Maholanobis cosine distance. Simulations are performed in Matlab, on ORL Database. The DTCWT partitioning of face images is compared with other partitioning techniques like, Discrete Wavelets `db2' & `coif2', with baseline as PCA. To show the efficacy of the partitioning, prior to dimensionality reduction, Detection error tradeoff (DET) curves are computed. The DET curves obtained shows that prior partitioning of the face images improves the performance of the further PCA dimensionality reduction.
A note on the Bayesian regret of Thompson Sampling with an arbitrary prior

We consider the stochastic multi-armed bandit problem with a prior distribution on the reward distributions. We show that for any prior distribution, the Thompson Sampling strategy achieves a Bayesian regret bounded from above by $14 \sqrt{n K}$. This result is unimprovable in the sense that there exists a prior distribution such that any algorithm has a Bayesian regret bounded from below by $1/20 \sqrt{n K}$.
TCP flow-based performance analysis of two on-demand routing protocols for mobile ad hoc networks

Researches on mobile ad hoc networks have been concentrated on implementations and performance comparisons of routing protocols. Little attention was paid to the interaction between end-to-end TCP traffic flows and these routing protocols. In this paper, we study the performance of two reactive on-demand routing protocols-DSR and AODV based on TCP traffic flows. Our performance simulations show that DSR performs better in a small window size and AODV works better in a large window size. Both of them need further improvements to provide better performance for TCP flow transmission. In addition, current TCP implementations can not guarantee a stable performance because they lack the ability to distinguish packet losses caused by network congestion or by route failure. The effects of interactions among routing, MAC and TCP protocol are also briefly discussed. This paper provides performance comparisons based on several important performance metrics.
A Fast Neural { Network Algorithm for Cell

|Cell placement is an important phase of current VLSI circuit design styles as standard cell, gate array, and Field Programmable Gate Array (FPGA). Although nondeterministic algorithms such as Simulated Annealing (SA) have been successful in solving this problem, they are known to be slow. In this paper, we propose a neural network algorithm that produces solutions as good as SA in substantially less time. Our algorithm is based on Mean Field Annealing (MFA) technique, which has been successfully applied to various combinatorial optimization problems. We derive a MFA formulation for the cell placement problem that can easily be applied to all VLSI design styles. To demonstrate that the proposed algorithm is applicable to real world problems, we derive a detailed formulation for the FPGA design style, and generate the layouts of several benchmark circuits. The performance of the proposed cell placement algorithm is evaluated in comparison with commercial automated circuit design software Xilinx Automatic Place and Route (APR) which uses SA technique. Performance evaluation is performed using ACM/SIGDA Design Automation benchmark circuits. Experimental results indicate that the proposed MFA algorithm produces comparable results with APR. However, MFA is almost 20 times faster than APR on the average.
Evolutionary understanding of corporate foreign investment behaviour: US foreign direct investment in Europe

Evolutionary understanding of behaviour of firms is gradually becoming more accepted in a variety of disciplines such as economics, management and organization. Contributing to a multi-disciplinary understanding of strategic behaviour, this paper analyzes foreign direct investment strategies of US firms in Europe since the second world war. Taking routinized investment behaviour, satisficing strategies and learning economies as major building blocks of an emerging theoretical framework the analysis follows the ’lagged co-evolution’ of company investment strategies and changing international economic environments.
Spread Spectrum Modulation by Using Asymmetric-Carrier Random PWM

This paper presents a new fixed-carrier-frequency random pulsewidth modulation method, where a new type of carrier wave is proposed for modulation. Based on simulations and experimental measurements, it is shown that the spread effect of the discrete components from the motor current spectra and acoustic spectra is very effective and is independent from the modulation index. The flat motor current spectrum generates an acoustical noise close to the white noise, which improves the acoustical performance of the drive. The new carrier wave is easy to implement digitally, without employing any external circuits. The modulation method can be used in both open- and closed-loop motor control applications.
MULTI-AGENT PLANNING AND SCHEDULING ENVIRONMENT FOR ENHANCED SPACECRAFT AUTONOMY

Spacecraft autonomy has the potential for effecting significant cost savings in mission operations by reducing the need for dedicated ground staff. In an autonomous operating mode, operators will communicate only highlevel goals and deadlines directly to the spacecraft. The spacecraft will then perform its own planning and scheduling, decomposing a goal into a set of sub-goals to be achieved with onboard subsystems andlor in cooperation with other spacecraft in the environment. In this paper, we present this distributed (or equivalently, multi-agent) approach to onboard planning and scheduling that helps a spacecraft function as an autonomous agent. Such an agent's domain knowledge of tasks and their components is manifested through a hierarchical language taking into account spacecraft operational aspects and resource constraints. The task decentralization problem is solved by the use of the hierarchical knowledge structures, and the resource optimization problem is addressed by its explicit representation within the model. The reasoning performed by an agent for the required planning and scheduling tasks is based on a constraint propagation paradigm. Schedule quality is enhanced by the introduction of agent cooperation. A limited-scope Java prototype is developed and demonstrated using space-based scenarios involving onboard sensors and a satellite constellation. We are specifically targeting our effort to enhance the planning and scheduling capability of NASA's proposed Remote Agent architecture.
Interpreting and Reconstructing Data from Sensor Networks

Geophysical phenomena are often three-dimensional, time-variant, and physically large, making them diﬃcult to measure. As wireless sensor nodes become cheaper, smaller, and more powerful, using a sensor swarm as a sampling framework seems to be a viable approach to this problem. However, samples from the network can be sparse and unstructured, creating an incomplete picture. Thus, the question addressed by this project is the following: How can we easily construct and interpret the best model of the underlying reality over some domain, given a possibly sparse and irregular set of samples? We present the design, implementation, and evaluation of the Signal Reconstruction Panel, a graphical program for tackling this problem. Using a method of Support Vector Regression, we demonstrate the program’s performance on a variety of data sets including the Collisionless Terrella Experiment (CTX), the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), the Poker Flats Incoherent Scatter Radar (PFISR), and GreenCube5, a detailed study of the Ompompanoosuc River ﬂow.
A graph-theory-based method for parallelizing the multiple-flow-direction algorithm on CUDA compatible graphics processing units

Flow direction algorithm based on gridded DEM is one kind of the most widely used algorithms in digital terrain analysis. Being a typical recursive algorithm, flow direction algorithm coded traditionally for sequential computation is very time consuming, especially for application on the gridded DEM of large-area with high spatial resolution. Recently, the graphics processing units (GPUs) were applied to speeding up the execution of single flow direction algorithm (SFD) by parallel computing based on compute unified device architecture (CUDA). Although multiple flow direction (MFD) algorithms perform generally better than SFD, parallel MFD algorithm on GPU hasn't been reported. In this paper, first we designed a CUDA-based parallel implementation on the NVIDIA GPU of a widely-used MFD algorithm (FD8) by using the parallelization strategy of the existing CUDA-based parallel SFD algorithm. Further analysis shows that this parallelization strategy has a problem of computing redundancy. Then, we proposed a graph-theory-based parallel implementation of FD8 algorithm in which the problem of computing redundancy could be released. The application result shows that the proposed graph-theory-based parallel FD8 algorithm gets faster acceleration than the parallel FD8 algorithm using the parallelization strategy of the existing CUDA-based parallel SFD algorithm, and performs much faster than the traditional serial FD8 algorithm.
The Differential Influence of Decision Characteristics on the Information Acquisition of Expert and Novice Decision Makers

In this study, we examine how task and environmental characteristics differentially affect the decision processes of novice and expert decision makers. Specifically, we consider how decision importance, accountability and complexity influence the information acquisition processes of manager and student subjects in a strategic business decision task. Based on prior research on expert decision making, we formulate hypotheses about whether these three decision characteristics will affect novices and experts differently. In two experiments, we find that importance affects experts but not novices. Also, we find that accountability affects novices but not experts and complexity affects both groups' information acquisition behavior.
Antithrombin reduces shedding of the endothelial glycocalyx following ischaemia/reperfusion.

AIMS Antithrombin is an important inhibitor of the coagulation system, additionally exerting specific anti-inflammatory effects on endothelial cells. Healthy vascular endothelium is coated by the endothelial glycocalyx, diminution of which increases capillary permeability, e.g. after ischaemia. Antithrombin is known to infiltrate the glycocalyx, binding to glycosaminoglycans, and to preserve the glycocalyx after application tumour necrosis factor-alpha. We investigated the influence of antithrombin on glycocalyx subjected to ischaemia/reperfusion. METHODS AND RESULTS Isolated guinea pig hearts were perfused with Krebs-Henseleit buffer (KHB). Antithrombin was applied to achieve physiological levels (1 U/mL) before inducing 20 min of ischaemia (37 degrees C). Hearts were reperfused for 20 min at constant flow (baseline perfusion pressure 70 cmH(2)O) with KHB or KHB plus 2 g% hydroxyethyl starch (130 kDa). Coronary net fluid filtration was assessed directly by measuring transudate formation on the epicardial surface. Post-ischaemic coronary release of syndecan-1 and heparan sulfate was quantified by ELISA. Hearts were perfusion-fixed to visualize the glycocalyx by electron microscopy. Ischaemia/reperfusion caused degradation of the glycocalyx, enhanced coronary perfusion pressure, and increased vascular permeability. Antithrombin significantly reduced post-ischaemic glycocalyx shedding, coronary perfusion pressure, coronary leak, and tissue oedema formation compared to untreated hearts. Additional application of colloid augmented these actions of antithrombin. Electron microscopy revealed a mostly intact glycocalyx after antithrombin treatment. CONCLUSION Antithrombin preserves the endothelial glycocalyx, sustaining the vascular barrier function and reducing interstitial oedema. The potentiated effect of colloid in these hearts suggests that the prevention of shedding should be of functional benefit also in vivo.
Traffic pattern based connection-level active rerouting algorithm in all-optical WDM networks

This paper proposes a connection-level active rerouting algorithm in all-optical WDM networks with traffic grooming and alternate routing to reduce the connection blocking probability. The main idea of the proposed rerouting algorithm is to reroute the existing connections to a predefined routing path, which is called the best rerouting path, between the source-destination pair. The best rerouting path is obtained by solving a non-linear optimization problem in which the objective function is to minimize the approximate blocking rate. After obtaining best rerouting path, the rerouting algorithm is devised to immigrate the connections to the best rerouting path when a connection finishes transmission. Simulation results show that the proposed rerouting algorithm yields lower connection blocking probability than the case without rerouting algorithms. Besides, we also found that the rerouting overhead produced by the proposed algorithm is very small. The results show that the proposed rerouting algorithm is able to produce low connection blocking probability with small rerouting overhead.
It is not the parts, but how they interact that determines the behaviour of circadian rhythms across scales and organisms

Biological rhythms, generated by feedback loops containing interacting genes, proteins and/or cells, time physiological processes in many organisms. While many of the components of the systems that generate biological rhythms have been identified, much less is known about the details of their interactions. Using examples from the circadian (daily) clock in three organisms, Neurospora, Drosophila and mouse, we show, with mathematical models of varying complexity, how interactions among (i) promoter sites, (ii) proteins forming complexes, and (iii) cells can have a drastic effect on timekeeping. Inspired by the identification of many transcription factors, for example as involved in the Neurospora circadian clock, that can both activate and repress, we show how these multiple actions can cause complex oscillatory patterns in a transcription–translation feedback loop (TTFL). Inspired by the timekeeping complex formed by the NMO–PER–TIM–SGG complex that regulates the negative TTFL in the Drosophila circadian clock, we show how the mechanism of complex formation can determine the prevalence of oscillations in a TTFL. Finally, we note that most mathematical models of intracellular clocks model a single cell, but compare with experimental data from collections of cells. We find that refitting the most detailed model of the mammalian circadian clock, so that the coupling between cells matches experimental data, yields different dynamics and makes an interesting prediction that also matches experimental data: individual cells are bistable, and network coupling removes this bistability and causes the network to be more robust to external perturbations. Taken together, we propose that the interactions between components in biological timekeeping systems are carefully tuned towards proper function. We also show how timekeeping can be controlled by novel mechanisms at different levels of organization.
Differential-Algebraic Equations Model for Quadratic Programming

A differential-algebraic equations (DAEs) model for solving convex quadratic programming (CQP) is studied in this paper. By using Frisch's logarithmic barrier function, the DAEs model is established and the corresponding relationships of the solutions to the proposed DAEs with the CQP problems is analyzed in details here. All the results shows that this new model is different from traditional optimization algorithms which tries to find optimal solutions by the classical discrete iterated sequence points as well as different from neural network method based on the ODEs which tries to find the optimal solutions by tracking trajectories of a set of ordinary differential equation systems. It is well-known that different numerical schemes to DAEs algorithm can lead to new algorithms or some classical iterated algorithms, for instance, the path-following interior point algorithm could be conducted by a scheme of the proposed DAEs algorithm. So, in this aspect, the conventional interior point method can be viewed as a special case of the new DAEs method. Hence, this DAEs model provides a promising alternative approach for solving convex quadratic programming problems.
Interests of Social Groups, Direction of Technical Progress, and Barriers to Development: How Sustainable is the World Economic Growth?

A considerable part of literature in the theory of economic growth is devoted to detecting of a relative role of factor accumulation, technological changes and institutions in economic growth. In the present paper an attempt is made to link and explain stylized facts characterizing economic growth in the contemporary World: i) there is a high degree of heterogeneity in levels of development and growth rates of countries, ii) the countries are subdivided into groups characterized, correspondingly, by low, intermediate and high levels of the capital to labor ratio and of the average labor productivity, iii) these groups of countries are rather stable in their composition; in particular some countries with a low capital to labor ratio stay in a “poverty trap” for a long time, iv) there is a global tendency of an increase in the capital share in GNP, v) the growth is influenced by political and social factors. In this paper a model is proposed in which two types of technological changes are distinguished: (a) an endogenous growth of the total factor productivity (TFP) and (b) a change in a technological parameter of a production function defining a directedness of technological progress. The latter change in technology is controlled by social groups – owners of labor (workers) and owners of capital (“capitalists”) – in a country and takes place together with a change in factor shares. We describe areas of coincidence and of non-coincidence of interests of the social groups related to a choice of technology and, correspondingly, to a distribution of the national product. The frontiers of these areas are made more precise taking account of a boundedness of the capital to labor ratio. Roles of the TFP and the elasticity of substitution in formation of the areas of social cohesion are of social conflict are studied. It is proved that, under some conditions, a degree of social cohesion increases. In a certain degree, the model is close to models of the new political economy (see e.g. Besley, 2007) and fills their shortage of account of technological progress and of dependence of political decisions on the state of economy. The model provides a possible explanation of a stability of the poverty traps, it shows a role of the TFP as a potential for the economic growth, and, in particular, it demonstrates a possibility of an economic crisis in industrial countries in result of an “innovation pause”. The model also throws light on differences in possibilities of growth in poorly developed, actively developing and industrial countries; in particular, it explains, why there is no advantage of late start in low income countries in a poverty trap.