Miracle-dz/UniFAR-FTUs huggingface dataset:
Pairwise Association of Seismic Arrivals with Convolutional Neural Networks

Correctly determining the association of seismic phases across a network is crucial for developing accurate earthquake catalogs. Nearly all established methods use travel-time information as the main criterion for determining associations, and in problems in which earthquake rates are high and many false arrivals are present, many standard techniques may fail to resolve the problem accurately. As an alternative approach, in this work we apply convolutional neural networks (CNNs) to the problem of associations; we train CNNs to read earthquake waveform arrival pairs between two stations and predict the binary classification of whether the two waveforms are from a common source or different sources. Applying the method to a large training dataset of previously cataloged earthquakes in Chile, we obtain > 80% true positive prediction rates for high-frequency data ( > 2 Hz ) and stations separated in excess of 100 km. As a secondary benefit, the output of the neural network can also be used to infer predicted phase types of arrivals. The method is ideally applied in conjunction with standard travel-time-based association routines and can be adapted for arbitrary network geometries and applications, so long as sufficient training data are available.
Adverse Metabolic Response to Regular Exercise: Is It a Rare or Common Occurrence?

Background Individuals differ in the response to regular exercise. Whether there are people who experience adverse changes in cardiovascular and diabetes risk factors has never been addressed. Methodology/Principal Findings An adverse response is defined as an exercise-induced change that worsens a risk factor beyond measurement error and expected day-to-day variation. Sixty subjects were measured three times over a period of three weeks, and variation in resting systolic blood pressure (SBP) and in fasting plasma HDL-cholesterol (HDL-C), triglycerides (TG), and insulin (FI) was quantified. The technical error (TE) defined as the within-subject standard deviation derived from these measurements was computed. An adverse response for a given risk factor was defined as a change that was at least two TEs away from no change but in an adverse direction. Thus an adverse response was recorded if an increase reached 10 mm Hg or more for SBP, 0.42 mmol/L or more for TG, or 24 pmol/L or more for FI or if a decrease reached 0.12 mmol/L or more for HDL-C. Completers from six exercise studies were used in the present analysis: Whites (N = 473) and Blacks (N = 250) from the HERITAGE Family Study; Whites and Blacks from DREW (N = 326), from INFLAME (N = 70), and from STRRIDE (N = 303); and Whites from a University of Maryland cohort (N = 160) and from a University of Jyvaskyla study (N = 105), for a total of 1,687 men and women. Using the above definitions, 126 subjects (8.4%) had an adverse change in FI. Numbers of adverse responders reached 12.2% for SBP, 10.4% for TG, and 13.3% for HDL-C. About 7% of participants experienced adverse responses in two or more risk factors. Conclusions/Significance Adverse responses to regular exercise in cardiovascular and diabetes risk factors occur. Identifying the predictors of such unwarranted responses and how to prevent them will provide the foundation for personalized exercise prescription.
Safety applications modeling methodology and performance optimization in road vehicle communication

For the safety applications in road vehicle communication, the existing research did not take it into account that the generation of the safety messages is event driven and the network traffic is self-similar. We propose an ON/OFF Pareto process based safety application self-similar model according to the above features and prove the effectiveness of this model analytically. Then we verify the model on NS2 simulation platform by showing the network traffic generated by our model is self-similar. At last, we use this model to simulate and analyze the performance of safety applications (adopting IEEE 802.11p) by computing the average delay and packet delivery ratio (PDR) with different vehicle densities, speeds and packets generation rates. The simulation results show that IEEE 802.11p can be used for safety applications in road vehicle communication. We also find the optimal working range for safety applications on vehicle density and packets generation rate except vehicle speed, which shows that we must make compromises between short delay and high packet delivery ratio. The conclusion is highly valued for safety applications applied in actual environment.
Absorption Characteristics Evaluation from Pulsed Photo-thermal Radiometry in the Determination of Lung Air-leak Integrity by Vital Staining

We evaluated the absorption characteristics of the lung surface with vital staining non-invasively by means of pulsed photo thermal radiometry (PPTR) to improve the success rate of laser air leak sealing from the lung. To seal the air leak after lung resection, we investigated laser treatment using diode laser irradiation (wavelength: 810 nm) and vital staining with indocyanine green (ICG, absorption peak wavelength: 805nm). We used muaradica and defined as A (mua: the absorption coefficient, a : the thermal diffusivity) in the approximate PPTR theory to analyze the PPTR signal as it was assumed the thermal diffusivity coefficient would be a constant when the lung collapsed during surgery. The accuracy of the constructed PPTR system with this assumption was A=plusmn 0.15s-1/2. In ex vivo studies, the measured A variation due to vital staining was 3.7s-1/2. This range was sufficiently large measured against the accuracy. We monitored the condition of the lung surface during continuous diode laser irradiation with our PPTR system. We successfully measured the absorption characteristic changes during laser irradiation. We believe this constructed PPTR system might be useful in improving the success rate of laser sealing with vital staining while arranging the laser energy by the value of A.
2 Title of dissertation : Calibration of the tree size distributions by combining the area-based approach and the individual tree detection using the airborne laser scanning

Individual tree detection (ITD) based forest inventory using the airborne laser scanning (ALS) data suffers from under-estimation problem, which arises mainly from the suppressed trees that are difficult to be detected from the air. Uncertainty of tree-level estimates, like tree height, diameter at breast height (DBH) and the modeled stem volume also contributes to the inaccuracy of the plot-level estimates. The doctoral work tackled the under-estimation problem from the perspectives of both tree and plot levels. At the plot level, suppressed trees were retrieved from the left tail of the tree size distributions derived from the area-based approach. At the tree level, DBH of single trees were predicted using the quantile-based nearest neighbor imputation. Area-based approach (ABA) based forest inventory is able to provide accurate and unbiased plot-level estimates of forest attributes, such as total stem volume. K-MSN method is used in the ABA to simultaneously predict the forest attributes of interest. If treelevel field measurements are available in the sample plots, it’s possible to apply the k-MSN method to predict tree size (DBH or height) distributions for the sample plots. The combination of the ITD-derived tree size distributions with the ABA-derived distributions makes it possible not only to improve the ABA-derived saw log estimates, but also to retrieve the suppressed trees for the ITD-derived tree size distributions. The replacement and the histogram matching were utilized to calibrate the tree size distributions. The results showed that after the calibration, the RMSE of the predicted total volume decreased by 2 %, and the bias was negligible. The quantile-based nearest neighbor imputation was able to predict the DBH as accurate as the benchmarking method, the k-MSN. It utilized the ALSmeasured tree height and crown diameter as the two predictor variables and achieved even better accuracy than the k-MSN method for larger trees with diameters 16 cm. The improved DBH estimates also benefit stem volume estimation, which led to the improved treeand plot-level estimations of the stem volume.
Mixed modified weighted bit-flipping decoding of low-density parity-check codes

In this study, a new weighted bit-flipping (WBF) algorithm called mixed modified WBF (MM-WBF) decoding is proposed for low-density parity-check codes. The new algorithm is built by mixing two WBF algorithms, one acting as the main decoding algorithm and the other acting as the auxiliary. Simulation results show that the new algorithm achieves a notable performance gain over reliability ratio-based WBF, improved M-WBF and low-complexity WBF algorithms with almost the same computational complexity. Compared with some belief-propagation-based algorithms, MM-WBF also provides an appealing performance against complexity trade-off.
Rapid vision-based shape and motion analysis system for fast-flowing cells in a microchannel

This paper proposes a novel method for simultaneous cell shape and motion analysis in rapid microchannel flows based on a multi-object feature extraction algorithm with a frame-straddling high-speed vision platform. This system can synchronize two camera inputs that share the same view with only a very small sub-microsecond time delay. Real-time video processing is performed using the hardware logic by extracting the moment features of multiple cells at 2000 fps or more, which are obtained from the two camera inputs, and their frame-straddling time can be adjusted from 0 to 0.5 ms in 9.9 ns steps. After setting the frame-straddling time within a certain range to avoid large image displacements between the two camera inputs, the frame-straddling high-speed vision platform can perform simultaneous shape and motion analysis of cells in fast microchannel flows of 1 m/s or greater. The results of real-time experiments conducted to analyze the deformabilities, velocities, and shapes of fast-flowing sea urchin egg cells in straight and L-type microchannels verified the efficacy of our vision-based cell analysis system.
A temporal requirement for Hippo signaling in mammary gland differentiation, growth, and tumorigenesis

In this study, Chen et al. discover that the Hippo pathway is functionally dispensable in virgin mammary glands but specifically required during pregnancy. YAP hyperactivation in mammary epithelia leads to defects in terminal differentiation. Loss of YAP causes no obvious defects in virgin mammary glands but potently suppresses oncogene-induced mammary tumors. This selective requirement for YAP in oncogenic growth suggests YAP inhibitors as targeted therapies against breast cancers.
An adaptive simple particle swarm optimization algorithm

The particle swarm optimization algorithm with constriction factor (CFPSO) has some demerits, such as relapsing into local extremum, slow convergence velocity and low convergence precision in the late evolutionary. An adaptive simple particle swarm optimization with constriction factor (AsCFPSO) is combined with chaotic optimization, then a new CFPSO is developed, i.e., a chaotic optimization-based adaptive simple particle swarm optimization equation with constriction factor (CAsCFPSO). Distribution vector of particles is defined as constriction factor in optimization process. Furthermore, piecewise linear chaotic map is employed to perform chaotic optimization due to its ergodicity and stochasticity. Consequently, the particles are accelerated to overstep the local extremum in AsCFPSO algorithm. The experiment results of six classic benchmark functions show that the proposed algorithm improves extraordinarily the convergence velocity and precision in evolutionary optimization, and can break away efficiently from the local extremum. Furthermore, the algorithm obtains better optimization results with smaller populations and evolutionary generations. Therefore, the proposed algorithm improves the practicality of the particle swarm optimization.
International Journal of Nanomedicine Dovepress Dual-modal Tracking of Transplanted Mesenchymal Stem Cells after Myocardial Infarction

Purpose: Results for implantation efficiency and effective improvement of cardiac function in the field of mesenchymal stem cells (MSCs) are controversial. To attempt to clarify this debate, we utilized magnetic resonance imaging (MRI) and near-infrared optical imaging (OI) to explore the effects of different delivery modes of mesenchymal stem cells on cell retention time and cardiac function after myocardial infarction (MI). Methods: Rat MSCs were labeled with superparamagnetic iron oxide nanoparticles and 1,
Performance Analysis of Wireless Ad hoc Networks in Different Network Situations from Routing Point of View

The research describes the performance of the three routing protocols (AODV,DSR,TORA)in different network situations, specially varying the size of the networks. AODV shows a considerable better performance over the others for any number of nodes. TORA and DSR show moderate performance for minimum number of nodes, where in the case of large networks, DSR shows some performance rather than TORA. OPNET Modeler 10.5 is used to model the network and to simulate the protocols. The thesis will show a future performance improvement for more routing protocols using OPNET Modelers or other Network Simulators.
Empirical evaluation of the textual differencing regression testing technique

Regression testing is a commonly used activity whose purpose is to determine whether the modifications made to a software system have introduced new faults. Textual differencing is a new, safe and fairly precise, selective regression testing technique that works by comparing source files from the old and the new version of the program. We have implemented the textual differencing technique in a tool called Pythia. Pythia has been developed primarily through the integration of standard, well known UNIX programs, and is capable of analyzing large software systems written in C. We present results from a case study involving a software system of approximately 11,000 lines of source code written for the European Space Agency. The results provide empirical evidence that textual differencing is very fast and capable of achieving substantial reductions in the size of the regression test suite.
TNO-UT at TREC-9: How Different are Web Documents?

Although at first sight, the web track might seem a copy of the ad hoc track, we discovered that some small adjustments had to be made to our systems to run the web evaluation. As we expected, the basic language model based IR model worked effectively on this data. Blind feedback methods however, seem less effective on web data. We also experimented with rescoring the documents based on several algorithms that exploit link information. These methods yielded no positive result.
Methane emissions from typical paddy fields in Liaohe Plain and Sanjiang Plain, Northeast China

Methane is one of the most important greenhouse gases and is emitted from waterlogged rice regions. Eddy covariance was used to obtain long-term (2017–2018), high-frequency data for the CH4 flux at typical rice paddy fields in Sanjiang Plain and Liaohe Plain. This study examines the CH4 emission process, emission characteristics at different time scales and the intensity of different emission sources. The relationships between CH4 emissions and temperature and photosynthetically active radiation were also analysed. CH4 emissions from Sanjiang Plain and Liaohe Plain in 2017 were 26.77 and 16.17 g CH4 m−2year−1, respectively. The CH4 fluxes in 2017 and 2018 were similar; emissions were higher at the Sanjiang site in 2018. Peak CH4 emissions (daily average: 0.127 μmol CH4 m−2s−1) corresponded to the tillering stage in Sanjiang Plain. CH4 emissions peaks corresponding to the jointing–heading and mature stages at Liaohe Plain. Monthly CH4 emissions were highest in July. The daily averaged flux was 0.065 μmol CH4 m−2s−1 during the growing season. The field-transplanting stage exhibited the highest CH4 emissions. No CH4 was emitted during the greening–tillering stages. Emissions increased again during the jointing–heading stages to 0.102 μmol CH4 m−2 s−1, and then decreased gradually. A significant linear correlation was observed between PAR and the methane flux in Liaohe Plain. CH4 emissions in Sanjiang Plain were more sensitive to changes in temperature. The temperature coefficient value was highest from the sowing period to the green period. The CH4 flux at Sanjiang Plain depended on the stage of rice growth, the temperature, the degree of irrigation and drainage, and the soil pH. In November (during the non-growing season) at Liaohe Plain, a slight negative flux (a weak CH4 sink) was observed. CH4 emissions were also found to be inhibited in the growing season by increased soil alkalinity.
Exploring the Mechanism of Physcomitrella patens Desiccation Tolerance through a Proteomic Strategy 1 [ W ] [ OA ]

College of Life Sciences, Capital Normal University, Beijing 100048, China (X.Q.W., W.Z.L., Y.H., T.Y.K., Y.K.H.); Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China (X.Q.W., H.C., T.Y.K., S.H.S.); Department of Energy Plant Research Laboratory, Michigan State University, East Lansing, Michigan 48824 (P.F.Y.); Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom (Z.L.); and Department of Biology, Duke University, Durham, North Carolina 27708 (Z.M.P.)
North-South Standards Harmonization and International Trade

Recent years have seen a surge in economic integration agreements (EIAs) and the development of non-tariff measures (NTMs). As a consequence, a growing number of EIAs include provisions on NTMs. However, little attention has been given in the literature to the effects of NTM liberalization in the context of EIAs. In this paper, we focus on provisions for technical regulations and analyze whether the North-South harmonization of technical barriers affects international trade. Using a gravity equation, we test whether, as a result of the deep integration associated with standards provisions included in the EIA, the Southern partners' trade expands with the North, but at the expense of their trade with non-bloc Southern partners. Empirical results provide strong support for this conjecture. Moreover, harmonization on the basis of regional standards negatively impacts the exports of developing countries to the North.
Momentum-Mapped Inverted Pendulum Models for Controlling Dynamic Human Motions

Designing a unified framework for simulating a broad variety of human behaviors has proven to be challenging. In this article, we present an approach for control system design that can generate animations of a diverse set of behaviors including walking, running, and a variety of gymnastic behaviors. We achieve this generalization with a balancing strategy that relies on a new form of inverted pendulum model (IPM), which we call the momentum-mapped IPM (MMIPM). We analyze reference motion capture data in a pre-processing step to extract the motion of the MMIPM. To compute a new motion, the controller plans a desired motion, frame by frame, based on the current pendulum state and a predicted pendulum trajectory. By tracking this time-varying trajectory, the controller creates a character that dynamically balances, changes speed, makes turns, jumps, and performs gymnastic maneuvers.
Face Tracker for Head Position Detection

The driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. Current facial features tracking techniques faces three challenges: 1) variety of light conditions and head orientation failure of some or all the facial features, 2) multiple and non rigid object tracking, and 3) facial feature occlusion. In this paper, we propose a new approach. First, the single camera (webcam) is used to detect face under various lighting conditions. The detected face is used to track facial features by using color model. Because color processing is very fast that mean time requirement is less. And from tracked facial features we predict the head motions in up-down and left-right direction. Furthermore, face movement are assumed to be smooth so that a facial features can be tracked with three point algorithm. Simultaneous use of YCbCr color mode, three point algorithms and the Geometric model greatly increases the prediction accuracy for each feature position. The experimental results shows validity of our approach to a real life facial tracking under various light condition, head orientations and facial expression. General Terms YCbcr color model, three point algorithm
Suppressing opposite-direction interference in TDD/CDMA systems with asymmetric traffic by antenna beamforming

One of the key advantages for the time-division duplex (TDD) system is the capability to deliver asymmetric traffic services by allocating different numbers of uplink and downlink time slots. However, in a TDD/code-division multiple-access (CDMA) system, asymmetric traffic may result in severe opposite-direction interference because downlink transmitted signals from neighboring base stations may interfere with the uplink received signals of the home cell. In this paper, we investigate the effect of four-antenna beamforming schemes from the perspective of suppressing the opposite-direction interference. We compare the uplink bit energy-to-interference density ratio of a traditional beam-steering technique (Scheme I) with that of the minimum-variance distortionless-response (MVDR) beamformer (Scheme II). Furthermore, Scheme III applies the conventional beam-steering technique for both downlink transmissions and the uplink reception. In Scheme IV, we implement beam-steering for downlink transmissions, while adopting the MVDR beamformer to process the uplink signals received at base stations. Our numerical results indicate that Scheme IV outperforms all the other three schemes, which can effectively suppress the strong opposite-direction interference in TDD/CDMA systems. While keeping low implementation costs in mind, employing the simpler Scheme III in a sectorized cellular system can also allow every cell to provide different rates of asymmetric traffic services.
The Effect of Economic and Relational Direct Marketing Communication on Buying Behavior in B2B Markets

The Effect of Economic and Relational Direct Marketing Communication on Buying Behavior in B2B Markets BY Kihyun Kim April 13, 2016 Committee Chair: Dr. V. Kumar Major Academic Unit: Marketing Business to Business (B2B) firms spend significant resources managing close relationships with their customers, yet there is limited understanding of how the customers perceive the relationship based on the customer management efforts initiated by the firm. Specifically, studies on how firms communicate different values to B2B customers and how they perceive the values the firm offers by consistently evaluating the direct marketing communication which ultimately affect their buying behaviors have been largely overlooked. Typically, the direct marketing communication efforts are geared towards explicitly featuring economic values or relational values. To implement an effective communication strategy catering to customers’ preferences, firms should understand how these organizational marketing communications dynamically influence the perceived importance of different values offered by the firm. Therefore, using data from a Fortune 500 B2B service firm and employing a content analysis and a robust econometric model, we find that (i) the effect of economic and relational marketing communication on customer purchase behavior vary by customers and change overtime (ii) the latent stock variable of direct marketing communication affect the customer purchase behaviors and (iii) the evolution of customers’ perceived importance can be recovered using the transaction data. Overall, we provide a marketing resource reallocation strategy that enables marketers to customize marketing communication and improve a firm’s financial performance.