Miracle-dz/UniFAR-FTUs huggingface dataset:
Detailed spectral analysis of two small New York state earthquakes

abstract A statistically complete methodology for the analysis of SMA-1 data, including a direct inversion of the amplitude spectra, is developed and applied to the records of two small earthquakes ( M L = 1.5 in Attica and M L = 2.2 in Blue Mountain Lake) obtained at epicentral distances of ≈1 km. Using ray dependent corner frequency-radius relations, the fault radii are determined to be a = 80 ± 15 m and 25 ± 10 m. The stress drops vary by an order of magnitude; Δσ = 6 ± 4 bars and 85 ± 60 bars. Using hydrofracture data to estimate σ ¯ , the average stress, the seismic efficiency of the Attica event is determined to be ≈0.08. Because of a high estimate of the fracture energy associated with its rupture, the Blue Mountain Lake event is interpreted as having fractured fresh rock. The stopping character of the two events, inferred from their spectral shapes, is shown to differ considerably. These differences are used to contrast the stress and frictional regimes of the two source regions.
Path Optimal Control of Markov Decision Processes with Temporal Logic Specifications

Markov decision processes (MDP) are probabilistic models widely used in various areas, such as control theory, game theory, machine learning and robotics. Recent years have seen a surge of research interest in the control of Markov decision process (MDP) under temporal logic specifications. Existing methods, such as abstraction-based approach and receding horizon approach, are hard to extend to MDP with continuous states, need a precise knowledge of the model, and are computationally demanding due to the curse of dimensionality. In this letter, we propose a randomized controller design algorithm for continuous state MDP with unknown transition probabilities with respect to signal temporal logic (STL) specifications. Our basic idea is to convert the controller design into an optimization problem with its robustness index as a cost function, where the optimal control policy corresponds to the optimal solution follow a probabilistic distribution. Sampling approach is employed to asymptotically approximate the optimal distribution. The convergence property is formally proved with an estimate of the convergence rate. Numerical example is given to illustrate the effectiveness of the proposed method.
Southwest Archaeology in the Twentieth Century

Mesa Verde, Chaco Canyon, Canyon de Chelly, and Paquime are as well known to tourists as they are to scholars as emblems of the American Southwest. This region has been the scene of intense archaeological investigation for more than a hundred years, with more research done here than in any other part of the United States. The arid and sparsely populated landscape provides excellent site preservation, while the living native peoples give cultural continuity with the past. In the first decades of the twentieth century Americans saw the Southwest as exotic as opposed to the Mexican perspective, which viewed the region, sometimes called the Northwest, as more of a backwater. Both views continue to shape and color the study of the area today. With contributions from well-known archaeologists, Southwest Archaeology in the Twentieth Century reviews the histories of major archaeological topics of the region during the twentieth century, with particular attention to the vast changes in southwestern archaeology during the later decades of the century. Included are the huge influence of field schools, the rise of cultural resource management (CRM), the uses and abuses of ethnographic analogy, the intellectual contexts of archaeology in Mexico, and current debates on agriculture, sedentism, and political complexity. By looking back at the previous century of study, this book provides an authoritative retrospective of intellectual trends as well as a synthesis of current themes in the arena of the American Southwest.
Implementation of Real Time Normalized Advantage Function Control for a Buck Converter

This paper proposes a normalized advantage function (NAF) control. The NAF control consists of a neural network (NN) block of the NAF agent and a PWM block. Based on multiple input variables, the NN block outputs a reference, which is inputted to the PWM to generate switching signals for the circuit. Multiple input variables and high non-linearity of the NN result in high control performance. Learning of the NAF agent was executed in a simulated environment. The effect of the parameters; state, reward, and the number of nodes of the NAF agent on the control performance and learning speed was investigated. The NAF control based on the NN parameters, weight, and bias obtained by the learning, was implemented in FPGA to achieve real-time control at a control frequency of 50kHz. The experiments confirm that the NAF control performs better than the PI control.
The RUVIFIST project: preliminary experimental results with a Reconfigurable Underwater Vehicle for Inspection, Free Floating Intervention, and Survey Tasks

The development of vehicles incorporating both the Autonomous Underwater Vehicle (AUV) and the Remotely Operated Vehicles (ROV) intervention functionalities can be considered one of the most investigated tasks of the underwater industry and the scientific community. A feasible solution can be the development of Autonomous Underwater Reconfigurable Vehicles (AURVs), i.e. vehicles that can change their current configuration depending on the demanded task. Driven by these considerations, an innovative AURV has been developed by the Department of Industrial Engineering of the University of Florence (DIEF), Italy, capable of efficiently reconfiguring its shape according to the task at hand. In particular, the RUVIFIST (Reconfigurable Underwater Vehicle for Inspection, Free-floating Intervention and Survey Tasks) vehicle has been provided with two extreme configurations: a slender ("survey") configuration for long navigation tasks and a stocky ("hovering") configuration designed for challenging goals as intervention operations. Consequently, this work presents the results obtained during several experimental campaigns conducted to accurately test the vehicle reconfigurable system and how the standard Guidance, Navigation and Control (GNC) strategies must be adapted for AURVs.
Privacy Preserving Demand Side Management Method via Multi-Agent Reinforcement Learning

The smart grid utilizes the demand side management technology to motivate energy users towards cutting demand during peak power consumption periods, which greatly improves the operation efficiency of the power grid. However, as the number of energy users participating in the smart grid continues to increase, the demand side management strategy of individual agent is greatly affected by the dynamic strategies of other agents. In addition, the existing demand side management methods, which need to obtain users' power consumption information, seriously threaten the users' privacy. To address the dynamic issue in the multi-microgrid demand side management model, a novel multi-agent reinforcement learning method based on centralized training and decentralized execution paradigm is presented to mitigate the damage of training performance caused by the instability of training experience. In order to protect users' privacy, we design a neural network with fixed parameters as the encryptor to transform the users' energy consumption information from low-dimensional to high-dimensional and theoretically prove that the proposed encryptor-based privacy preserving method will not affect the convergence property of the reinforcement learning algorithm. We verify the effectiveness of the proposed demand side management scheme with the real-world energy consumption data of Xi'an, Shaanxi, China. Simulation results show that the proposed method can effectively improve users' satisfaction while reducing the bill payment compared with traditional reinforcement learning (RL) methods (i.e., deep Q learning (DQN), deep deterministic policy gradient (DDPG), QMIX and multi-agent deep deterministic policy gradient (MADD PG)). The results also demonstrate that the proposed privacy protection scheme can effectively protect users' privacy while ensuring the performance of the algorithm.
Long-term & short-term bike sharing demand predictions using contextual data

Bike Sharing Systems (BSSs) have gained popularity in the last two decades, becoming an integrated part of our mobility ecosystem. One of the major issues BSS operators struggle to deal with is forecasting the mobility demand, namely how many bikes are needed, when, and where. To deal with this challenge, this paper introduces a novel deep learning architecture that combines Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and contextual data to predict hourly demand in large-scale bike-sharing systems one day ahead. Specifically, the CNN layer captures spatio-temporal trends and is used to model long-term demand patterns, while the LSTM layer focuses on short-term mobility strategies. A separate Neural Network is used to include contextual data, such as weather data or special events. Predictions are provided for the next 24 hours at a frequency of one hour. The modular structure of the model ensures that the framework can be used in different situations and that individual components can be replaced. Similarly, additional contextual information can be included with limited effort. Results show that such a modular framework, where each module captures different dynamics (weather effects, long-term mobility patterns, short-term mobility patterns) outperforms the baseline models and also reduces their computational times.
Predicting Parking Occupancy with Deep Learning on Noisy Empirical Data

Parking is a contributor to urban traffic. According to a survey by the International Parking Institute (IPI), over 30% of cars cruising in the cities are looking for parking space, which highly contributes to urban congestion. Besides, an increase or decrease of parking occupancy is an indicator for decreasing or increasing car travel demand. Therefore, predicting urban parking occupancy can be beneficial for routing and urban traffic management. However, precision parking prediction solutions often require, e.g., investments in real-time detection technologies or access to big volumes of floating car data. However, parking data is rarely available in the form in which it is required. In this paper, we work with data of a small city in Germany that contains the occupancy of eleven parking lots recorded over one year. We implement a Long-Short-Term Memory (LSTM) model to predict parking occupancy, focusing on the following topics: challenges and limitations of the given data, performance and sensitivity to meteorological and event features and time sequence selection for training. The highest accuracy is reached when choosing two days data - the day to predict for and the corresponding day of the preceding week - within one week time window for parking prediction.
Optimal Control for Discrete-Time Step Backward High-Order Fully Actuated Models

This paper concerns the optimal control problem for dynamic systems represented by the discrete-time step backward high-order fully actuated (HOFA) models. A quadratic performance index of the system states is first proposed, and then for the finite-time output tracking problem and the infinite-time output regulation problem, the corresponding optimal controllers in the state feedback form are obtained as a combination of two sub-controllers: one is designed by utilizing the inherent full-actuation feature of the HOFA model to covert the original model into a linear constant model, while the other is further designed for this converted linear constant model to minimize the quadratic performance index. Finally, two simulation examples are provided to illustrate the effectiveness and superiority of our proposed optimal controllers.
A Swarm Flocking Control Method of Spacecraft Cluster Flight

Most conventional cooperative control methods are based on the top–down mechanisms. These mechanisms are usually centralized. In order to improve the viability of spacecraft cluster, a novel distributed flocking control combining the exponential function and the piecewise function is proposed to organize and guide spacecraft monomers to achieve the coordinated flocking behavior and the stable orbit operation. In addition, the spacecrafts can achieve the stable space to avoid collision. As the relative motion dynamics model of spacecraft is considered in the design of the flocking local rules, the proposed flocking model is practical in theory. Finally, a numerical simulation is carried out, which verifies the feasibility and effectiveness of the proposed flocking model.
An evolutionary spectrum approach to modeling non-stationary fading channels

To evaluate mobile communication systems, it is important to develop accurate and concise fading channel models. However, fading encountered in mobile communication is usually non-stationary, and the existing methods can only model quasi-stationary or piecewise-stationary fading instead of general non-stationary fading. To address this, this paper proposes an evolutionary spectrum (ES)-based approach to modeling non-stationary fading channels. Our ES approach is more general than the existing piecewise-stationary models and is capable of characterizing a general non-stationary fading channel that has an arbitrary ES (or time-varying power spectral density); our ES approach is parsimonious and is also able to generate stationary fading processes. As an example, we show how to apply our ES approach to generating stationary and non-stationary correlated Nakagami-m fading channel processes. Simulation results show that the ES of the channel gain process produced by our ES-based channel model agrees well with the user-specified ES, indicating the accuracy of our ES-based channel model. Copyright © 2011 John Wiley & Sons, Ltd.
Lectures on compact Riemann surfaces

This is an introduction to the geometry of compact Riemann surfaces. We largely follow the books [8, 9, 10]. 1) Defining Riemann surfaces with atlases of charts, and as locus of solutions of algebraic equations. 2) Space of meromorphic functions and forms, we classify them with the Newton polygon. 3) Abel map, the Jacobian and Theta functions. 4) The Riemann-Roch theorem that computes the dimension of spaces of functions and forms with given orders of poles and zeros. 5) The moduli space of Riemann surfaces, with its combinatorial representation as Strebel graphs, and also with the uniformization theorem that maps Riemann surfaces to hyperbolic surfaces. 6) An application of Riemann surfaces to integrable systems, more precisely finding sections of an eigenvector bundle over a Riemann surface, which is known as the "algebraic reconstruction" method in integrable systems, and we mention how it is related to Baker-Akhiezer functions and Tau functions.
Chewed Versus Swallowed Ticagrelor in P2Y12 Inhibitor-Naïve Patients Undergoing Percutaneous Coronary Intervention.

Purpose Dual antiplatelet therapy is standard for patients undergoing percutaneous coronary intervention (PCI) with stents. Traditionally, patients swallow the loading dose of a P2Y12 inhibitor before or during PCI. Time to achieve adequate platelet inhibition after swallowing the loading dose varies significantly. Chewed tablets may allow more rapid inhibition of platelet aggregation. However, data for this strategy in patients with stable ischemic heart disease or non-ST-elevation acute coronary syndrome (NSTE-ACS) are less robust. Methods In this single-center prospective trial, 112 P2Y12-naïve patients with stable ischemic heart disease or NSTE-ACS on aspirin therapy and who received ticagrelor after coronary angiography but before PCI were randomized to chewing (n=55) or swallowing (n=57) the ticagrelor loading dose (180 mg). Baseline variables were compared using 2-sample t-test and chi-squared/Fisher's exact tests as appropriate, with alpha set at 0.05. P2Y12 reaction units (PRU) were compared at baseline, 1 hour, and 4 hours using Wilcoxon rank-sum test. Patients then received standard ticagrelor dosing. Results After exclusions, P2Y12 PRU in the chewed and swallowed groups at baseline, 1 hour, and 4 hours after ticagrelor loading dose were 243 vs 256 (P=0.75), 143 vs 210 (P=0.09), and 28 vs 25 (P=0.89), respectively. No differences were found in major adverse cardiac events (MACE) or major bleeding at 30 days and 1 year. Conclusions In patients with stable ischemic heart disease or NSTE-ACS, chewing rather than swallowing ticagrelor may lead to slightly faster inhibition of platelet aggregation at 1 hour with no increase in MACE or major bleeding.
An outbreak of Streptococcus equi subsp. zooepidemicus in layers: evidence of fecal transmission.

Now and then, major disease outbreaks caused by Streptococcus equi subsp. zooepidemicus are reported in poultry. Besides acute septicemia, infection can result in a peracute or chronic form of disease with described mortality rates of 11% to 80%. Previously, source of infection in poultry was linked to horses in which this bacteria can be present as an opportunistic pathogen on mucus membranes. The main route of spreading and maintaining within a poultry flock, after entering the stable, however, remains unclear. This case report describes an outbreak of Streptococcus equi subsp. zooepidemicus affecting a flock of 28,500 layer hens housed in an aviary system with free-range. Efforts to reveal the route of dissemination of the Streptococcus bacteria within the flock assume fecal excretion by clinically healthy chickens.
Wind Stress Parameterisation in the SouthernOcean

Wind stress is often parameterised in ocean-atmosphere coupled models by a simple drag law, which depends quadratically on the atmospheric velocity at a reference height. Strictly speaking, this drag law should be written as a quadratic function of the difference between the ocean and atmosphere velocities. The two different cases give very similar magnitudes of stress, however recent studies have shown that including the ocean velocity in the calculation of stress leads to a significant reduction in wind power input to the ocean. While this effect has previously been modelled in gyre circulations, this work is the first to investigate it in the Southern Ocean, using the eddy-resolving quasi-geostrophic coupled model Q-GCM. In this model, including the ocean velocity in the stress calculation is found to reduce power input, but paradoxically the circumpolar transport is increased. The increase in transport is a consequence of two main factors: eddy saturation of the Antarctic Circumpolar Current, and eddy damping under the ocean velocity dependent stress. This result is unique to the Southern Ocean, and it adds to the substantial body of evidence that the Southern Ocean can only be modelled accurately if eddies are resolved. The wind stress parameterisation scheme is also modified to include temperature coupling in the Southern Ocean. Scatterometer observations have established a strong link between wind stress gradients and sea surface temperature (SST) gradients, due to convection in the atmospheric boundary layer caused by SST fronts. A simple modification to the wind stress is implemented, coupling the quadratic drag law to the temperature difference between the ocean and atmosphere. This simple representation is shown to be consistent with scatterometer observations, and the coupling constant is calibrated using known correlations between stress and SST in the Southern Ocean. Unlike the ocean velocity dependent stress, the temperature coupled stress is found to have a negligible effect on the mean flow in this model.
63x-Öl-Erste Erfahrungen mit IMSI

: First Experiences with IMSI. In a routine ICSI procedure each oocyte is injected with a single sperm selected at a 200–400x magnification. As anomalies of the nucleus, especially vacuoles, cannot be detected at this magnification a new method was developed by the group of Prof. Bartoov. This method allows the real-time assessment of spermatozoa at a > 6000x magnification and therefore minimizes the risk of injecting an morphologically abnormal sperm. It was demonstrated that this method elevated the clinical pregnancy in a selected patient group from 25% to 60%. In the same way the abortion rate was reduced from 40% to 14%. The study
Delayed exponential fitting by best tensor rank-(R/sub 1/, R/sub 2/, R/sub 3/) approximation

We present a subspace-based scheme for the estimation of the poles (angular-frequencies and damping-factors) of a sum of damped and delayed sinusoids. In our model each component is supported over a different time frame, depending on the delay parameter. Classical subspace based methods are not suited to handle signals with varying time-support. In this contribution, we propose a solution based on the best rank-(R/sub 1/, R/sub 2/, R/sub 3/) approximation of a partially structured Hankel tensor on which the data are mapped. We show, by means of an example, that our approach outperforms the current tensor and matrix-based approaches in terms of the accuracy of the damping parameter estimates.
Design of a THz Antenna with Broadband Radiation Characteristics for 6G Applications

In this paper, the design of a Terahertz (THz) antenna for broadband wireless high-data-rate communication is proposed. Several antenna designs are presented here that are better suited to short-range THz communication in 6G applications. The initial implementation will be a 310 GHz single-element dipole reflector antenna. With a gain of 4.82 dBi, this antenna can cover the frequency range of 295 GHz to 400 GHz with an impedance bandwidth of 33.8%. Second, to improve gain while keeping nearly the same impedance bandwidth, a new design is presented that is based on the same dipole structure but adds directors in the shape of a half circle. When three half-circle-shaped directors are used, the gain increases to 7.27 dBi. All in all, the results obtained make the proposed designs strong contenders for 6G wireless communication systems that prioritize speed over range.
Time Variant Circularly Polarized CPW Antenna for WIFI/ISM/Wi-Max/Wi-LAN Communication Applications

A Triple band triple sensed CPW-Fed Circularly polarized Antenna is presented in this article. The rectangular parasitic elements mainly responsible for the generation of circular polarization (LCHP, RCHP) in lower (2.4GHz) and upper (5.8GHz) bands. The antenna covers modern commercial applications such as 2.4GHz (Wi-Fi band), 3.5GHz (WI-MAX),5.8GHz(WLAN) Applications. The proposed model gives Triple band circular polarization of below 3dB axial ratio tells proposed model is a good candidate for Targeted applications.