Miracle-dz/UniFAR-FTUs huggingface dataset:
Second Order Extension of Optimistic Actor Critic

Optimistic Actor-Critic (OAC), an optimistic exploration algorithm based on Soft Actor Critc (SAC), addresses the problems of pessimistic un-derexploration and directional uninformedness of existing exploration strategies. We evaluate OAC and analyse its key exploration behaviour. In addition we show that the first order approximation of OAC has weaknesses and because of that, we introduce Optimistic Actor Critic with Second Order Approximation (OAC2), a second order extension of OAC. We highlight its theoretical advantages, which result in an exploration policy achieving higher exploitation ability, so that the exploitation/exploration trade-off of the exploration policy can be better balanced. We evaluate it on different robotic control tasks of the MuJoCo engine and show practical issues, but also discuss further potential for improvements.
EFFECT OF SOME NATURAL EXTRACTS AND BENZYLADENINE ON GROWTH AND PRODUCTIVITY OF WHEAT (Triticum estivam, L

Growth of wheat plants cv. Sakha 93 was significantly enhanced during 2003/04 and 2004/05 seasons by application of the natural yeast and garlic extracts (YE and GE) each at 50 and 100 ml/l as well as benzyladenine (BA) at 25 and 50 ppm. Since, significant increases in stem length, No. of both tillers and leaves, stems and leaves dry weights and total leaf area / plant were obtained with all applied treatments. Meanwhile, significant reduction in the assimilation rate was existed. Besides, different assigned treatments obviously increased the concentrations of photosynthetic pigments, NPK, crude protein and total carbohydrates in the flag leaf of treated plants as compared to those of untreated ones. In addition, all applied treatments caused positive alterations in many anatomical features of stem and flag leaf blade of treated plants. Among of these, the most important ones, increases of lamina thickness, length and width of vascular bundle and thickness of phloem and xylem tissues. Moreover, different applied treatments significantly improved the total grain yield/plant and its components as well as the straw yield/plant compared with those of untreated plants. The highest grain yield was attained by applying GE at 100 ml/l followed by BA at 50 ppm then YE at 100 ml/l. Hence, the present study strongly admit the use of natural yeast and garlic extracts and benzyladenine not only to improve growth and productivity of wheat plants but also to avoid all cautions (regarding human health) about the use of synthetic growth regulators and the excessive use of mineral nutrients specially on the nutritional crops.
The Selection of LASER as Surgical Instrument in Medical using Neutrosophic Soft Set with Generalized Fuzzy TOPSIS, WSM and WPM along with MATLAB Coding

Lasers are medical devises and widely used in surgery to treat; diseased blood vessels, reduce blood loss, infection reduction, and many other purposes. Whereas, Lasers has many types based on the construction materials. Thus, the right selection of laser for surgery is very important to accomplish complex medical tasks. With the development of MCDM techniques and neutrosophic soft set, this problem can be solved with more accuracy and precision. The aim of this paper is to select the right type of laser for specific surgeries. To, select the right choice, six different laser types and seven criteria are taken. To find the best alternative, generalized TOPSIS, WSM, and WPM along with MATLAB coding techniques are used. Results are the same and showing the right selection of the same alternative which is already being used in the field of surgery. This shows that in the future, these techniques can be applied in the selection of medical equipment too.
Learning to Walk Over Structured Terrains by Imitating MPC

Walking over structured terrain requires perception awareness of the environment. The robot needs to extract information from exteroceptive sensors and generate control signals by either model-based approaches, such as Model Predictive Control (MPC), or inferencing a neural network, trained with Reinforcement Learning (RL) or Imitation Learning (IL). While MPC can produce accurate solutions, it relies on an accurate perceptual sensor and is constrained by computational limits of onboard hardware. RL solves such problems by designing rewards for a successful traverse. But designing rewards can be tedious and training an RL policy often takes days. IL trains the policy by learning from the expert demonstration and requires less time if good demonstrations are available. MPC-Net is an IL approach that learns from an MPC expert. It minimizes the control Hamiltonian of the Optimal Control (OC) problem instead of imitating the observation-action mapping directly as Behavioral Cloning (BC). It explicitly encodes the constraints into the objective and achieves improved constraint satisfaction practically. In this work, we add perception to MPC-Net, using demonstrations from perceptive MPC, which can walk over structured obstacles. To train the policy, we use a teacher-student learning framework to incorporate noisy exteroceptive information. In the ﬁrst stage, we train a privileged teacher with MPC-Net in simulation, which observes the ground truth exteroceptive information. In the second stage, a student policy is trained with BC to imitate and robustify the privileged teacher by experiencing more realistic sensor data. We benchmark our MPC-Net teacher and validate our student policy on the hardware. We show that our student policy outperforms MPC expert under noisy perception inputs. We also show the necessity of using a two-stage “learning by cheating” framework. Moreover, we compare the performance of the robot when walking over a high step with Perceptive MPC-Net against blind MPC-Net policy.
On the Generalizability of Two-Layer ReLU-activated Neural Networks with a Fourier Feature Embedding

We would like to analyze the generalizability bounds of binary coordinate-based multi-layer perceptrons (MLPs) with an input Fourier Feature encoding using Rademacher analysis. Coordinate-based MLPs are a form of artificial neural network (ANN) that take in as input a low-dimensional input (usually a 2D or 3D coordinate), and they can be increasingly found in many problems in computer graphics and computer vision, such as 3D shape regression, 2D image regression, CT, MRI and more. However, MLPs with a raw coordinate input usually do not perform well in practice, as they fail to learn high-frequency features. Recent work by Tancik, et al. [19] introduced the Fourier Feature embedding, which is a generalization of the sinusoidal positional encoding found in many papers [21, 13, 20] that maps an input coordinate v ∈ R onto the surface of a hypersphere as follows:
Intra- and Interspeaker Repetitiveness in Locative Variation

A long research line in quantitative sociolinguistics has been aimed at understanding how persistence, the tendency for people to repeat a linguistic variant they have just used, influences language variation and change. Previous studies have variously attributed variant repetitiveness to priming in the psycholinguistic sense, socially-motivated style-shifting, or interspeaker accommodation, implying that intraspeaker persistence and interspeaker convergence are potentially different phenomena. This study reports both interspeaker convergence and intraspeaker persistence in a morphological variable that has been recently documented in the Chengdu dialect of Mandarin, a variety which is subject to language contact with standard Mandarin. We compare the relationship between repetitiveness within and across speakers. Results from mixed-effect logistic regression show that there is a persistence effect within speakers and a convergence effect across speakers; however the size of the effect varies according to different meaning contexts. Findings further shed light on the understanding of language change from psycholinguistic perspectives. This working paper is available in University of Pennsylvania Working Papers in Linguistics: https://repository.upenn. edu/pwpl/vol27/iss1/16 Intraand Interspeaker Repetitiveness in Locative Variation Aini Li and Meredith Tamminga∗
The cask age: the technology and history of wooden barrels

This paper explores the use of wooden casks (barrels). It shows the principles of their construction, organization of the cooper industry over time and examples of how barrels facilitated trade and logistical activities throughout the 2000 years in which they were a predominant shipping container form. The paper finds that, although the shape and construction are very different from today's shipping containers, the same design considerations apply. Package shape and weight were designed to promote material handling productivity. The geometry facilitated transport by maximizing cube utilization and tight stowage in ships and wagons. The materials and technology were readily available at low cost. The construction provided protection from handling and transit forces. Trade associations cooperated to set standards for quality control, developed educational programs and worked with governments to regulate standards. Printing identified product and stock keeping units (product and brand). The shelf‐life of food products was extended. The closure permitted easy filling and closing, stayed closed during transit, and facilitated opening and emptying. Containers were widely reused or recycled. The reasons for the end of the barrel era relate to changes in technology, logistics, markets and overall economic activity. The industrial revolution created an increase in demand and stimulated mechanization, resulting in lower quality barrels as well as the development of other substitutes. The trend to paper‐based substitutes was enabled by the invention of the papermaking machine and the process for pulping wood in the 1800s. Rail transport changed the geometry of transport vehicles and enabled mechanical handling practices that favoured the box shape. These innovations enabled a shift in marketing and retailing, ushering in the consumer packaging revolution. Copyright © 2005 John Wiley & Sons, Ltd.
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming

Recent advances in machine learning have led to growing interest in Explainable AI (xAI) to enable humans to gain insight into the decision-making of machine learning models. Despite this recent interest, the utility of xAI techniques has not yet been characterized in human-machine teaming. Importantly, xAI offers the promise of enhancing team situational awareness (SA) and shared mental model development, which are the key characteristics of effective human-machine teams. Rapidly developing such mental models is especially critical in ad hoc human-machine teaming, where agents do not have a priori knowledge of others’ decision-making strategies. In this paper, we present two novel human-subject experiments quantifying the beneﬁts of deploying xAI techniques within a human-machine teaming scenario. First, we show that xAI techniques can support SA ( p < 0 . 05) . Second, we examine how different SA levels induced via a collaborative AI policy abstraction affect ad hoc human-machine teaming performance. Importantly, we ﬁnd that the beneﬁts of xAI are not universal, as there is a strong dependence on the composition of the human-machine team. Novices beneﬁt from xAI providing increased SA ( p < 0 . 05 ) but are susceptible to cognitive overhead ( p < 0 . 05 ). On the other hand, expert performance degrades with the addition of xAI-based support ( p < 0 . 05 ), indicating that the cost of paying attention to the xAI outweighs the beneﬁts obtained from being provided additional information to enhance SA. Our results demonstrate that researchers must deliberately design and deploy the right xAI techniques in the right scenario by carefully considering human-machine team composition and how the xAI method augments SA.
Optimizing Profit by Mitigating Recurrent Churn Labeling Issues: Analysis from the Game Domain

Churn can be interpreted as customer defection and can be considered one of the most critical challenges in the Game Analytics domain because of its impact on the game industry's profit. When predicting churn, the first step is defining what is considered churn, which can change depending on the players' behaviors and approaches. This work studied related works and revealed two recurrent issues in the labeling process: limitations on the adopted labeling approaches (1) and the static definition of churn (2). To mitigate the first issue, an individualized labeling approach was deployed. To address the second one, a novel evaluation method, based on the impact of a change in the churn definition, was proposed. This method allowed the proposition of two new labeling approaches, which were included in the analysis. By comparing the labeling approaches in two games using a profit perspective, it was identified that the new ones present statistically significant benefits compared to the traditional ones. Regarding the evaluation method, its usage can justify when the redefinition of churn and the classifier's retraining should happen to improve profit. The results are valuable for the game context, potentially extended to other contexts by delivering more reliable labels and more validated classification performance.
Impact of Fish Oil on Intestinal Permeability, Inflammation, and Performance in Swine

III PUBLIC ABSTRACT . V ACKNOWLEDGMENTS . VI LIST OF TABLES . I LIST OF FIGURES . II CHAPTER 1. REVIEW OF LITERATURE . 1 The Gastrointestinal Tract and Nutrient Digestion . 2 Intestinal Barrier . 6 The Gastrointestinal Microbiota . 8 Immune Response and Animal Performance . 8 Omega-3 Polyunsaturated Fatty Acids . 10 Conclusions . 12 2. IMPACT OF FISH OIL ON INTESTINAL PERMEABILITY, INFLAMMATION, AND PERFORMANCE IN SWINE . 20 Introduction. 20 Materials and Methods . 22 Results . 25 Discussion . 28 Conclusions . 35 Tables . 36 Figures . 40 References. 48 i LIST OF TABLES Table Page 1-1 Summary of the effects of omega-3 PUFA on growth, nutrient digestibility, and inflammation in swine. 12 2-1 Nutrient levels of the diets fed to the piglets. 36 2-2 Fatty acid composition of the fish oil fed to the piglets. 37 2-3 Production parameters of piglets supplemented with or without fish oil for four weeks. 38 2-4 Plasma inflammatory mediators of LPS challenged piglets supplemented with or without fish oil for four weeks. 39
Estimation of Signal Parameters in Maritime Environment Using Extended Sub-Space Based Approach

During the past few years there has been an increasing interest in applying sub-space methods to a wide range of Signal Processing and RADAR system theory problems, due to their computational simplicity. However, these techniques are not efficient to resolve closely parameters of signals embedded in maritime environment characterised by correlated non-Gaussian clutter, which is modelled in this paper as a compound Gaussian process. We propose in this paper an extended sub-space based approach for frequency estimation of a signal in K-distributed clutter, using the Fixed Point Covariance Estimation of the clutter. Numerical results obtained by Monte Carlo Simulation demonstrate the effectiveness and efficiency of the proposed method.
Reliability-Based Analysis and Design of Eccentrically Loaded Footings

This paper presents a reliability-based approach for the analysis and design of a shallow strip footing subjected to an eccentric load. Only the punching failure mode of the ultimate limit state is considered in this paper. The deterministic model used is based on two rotational double-spiral failure mechanisms in limit analysis. The random variables used are the soil shear strength parameters. The hypothesis of uncorrelated shear strength parameters was found conservative in comparison to the one of negatively correlated variables. The coefficient of variation of only the angle of internal friction has a significant effect on the failure probability. For design, an iterative procedure is performed to determine the breadth of the footing for a target failure probability. ABSTRACT: This paper presents a reliability-based approach for the analysis and design of a shallow strip footing subjected to an eccentric load. Only the punching failure mode of the ultimate limit state is considered in this paper. The deterministic model used is based on two rotational double-spiral failure mechanisms in limit analysis. The random variables used are the soil shear strength parameters. The hypothesis of uncorrelated shear strength parameters was found conservative in comparison to the one of negatively correlated variables. The coefficient of variation of only the angle of internal friction has a significant effect on the failure probability. For design, an iterative procedure is performed to determine the breadth of the footing for a target failure probability.
Learning Robot Skills From Video Data

Imitation learning is a common way to teach new skills to robots by learning from human demonstrations. While many existing approaches deploy kinesthetic teaching or teleoperation to gather demonstrations, these methods make data collection cumbersome and laborious for the user. In contrast, learning from external observation provides a potentially more intuitive way of teaching new skills to a robot. Here, the robot can only observe a human demonstrating the task, without any physical interaction or direct target action information given. In this work, we present a method to learn new robotic skills in task space by extracting hand trajectories from human demonstration videos. Afterwards, robotic movement skills are encoded with Probabilistic Movement Primitives from the recorded human trajectories. Our sys-tem provides a simple data collection pipeline and requires only few demonstrations to teach a new skill. We show the feasibility of our approach with a simulated 7-DOF Franka Emika Panda arm by learning to draw digits and on a pick-and-place task.
Link Analysis in Graphs: PageRank

• Set notation. A representation of a graph that follows the definition above. Example. G = 〈{A,B,C,D,E}, {(A,B), (A,C), (A,E), (B,C), (B,E), (C,D)}〉. • Graphical representation. A graph can be represented as a drawing. Each node is drawn as a point or circle on a plane, and each edge is a line connecting the representations of its two vertices. To draw a directed graph, arrows are added to the edge lines to point from the first vertex in the edge to the second. Example. Figure 1 shows the graphical representations of G in the cases when G is directed and undirected.
CAPACITY ENHANCEMENT OF MIMO SYSTEM UNDER DIFFERENT FADING CHANNELS

An efficient technique to maximize the channel capacity of MIMO system in case of practical fading channel has been designed for efficient data transmission. Beneath pragmatic fading environment, transmitted signal suffers phase and magnitude deterioration. Hence it becomes imperative to dodge the effect of fading in any communication channel and to make an efficient system. Rayleigh fading is studied and a comparison is being made among BPSK, QPSK and 16 QAM modulation technique in Rayleigh fading environment. An efficient model is created in which data transmission can take place with least fading effect. Moreover channel capacity of MIMO system depends upon number of half wave dipole antenna used in antenna array. At small SNR values capacity increases linearly and channel matrix coefficients are studied to further optimize the channel characteristics. There are many factors which pragmatically decide the channel capacity of MIMO system like number of antenna elements at transmitting and receiving side, power fed at antenna section, channel matrix coefficients etc. In the proposed system it is proved that as number of antenna elements increases there is significant increase in channel capacity.
Supplemental Material for “PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric”

In this section, we visualize more primitive instance segmentation results produced by our method. Figure 1 and Figure 2 shows our predictions on ABC dataset [5] and our self-collected scene dataset, respectively. Our method can extract small instances with complex structures correctly (Figure 1). By learning only local surface properties, our features are rich enough to recover unlimited number of instances in challenging scene environments shown in Figure 2. Finally, we can merge chunks of scenes seamlessly to handle input at very large scale. Figure 3 primitive segmentation of several merged large scenes using our methods.
Non-model-based control for a wheeled mobile robot towing two trailers

In this paper, trajectory tracking control of a wheeled mobile robot (tractor) with two trailers including three nonholonomic constraints is analyzed. This system is a nonlinear, under actuated mechanical system subjected to nonholonomic kinematic constraints. First, system dynamic equations are obtained. A non-model-based control algorithm using PD-action filtered errors has been used in order to control the wheeled robot. Non-model-based controllers are always more appropriate than model-based algorithms due to lower dependency on dynamic models, lower computational costs, and also robustness to uncertainties. Asymptotic stability of the closed-loop system has been investigated using Lyapunov method and Barbalat’s lemma. Finally, in order to show the effectiveness of the proposed approach simulation and experimental results have been presented. Obtained results show that without requiring a priori knowledge of plant dynamics, and with reduced computational burden, the tracking performance of the presented algorithm is quite satisfactory.
Challenges and Solutions for the Use of Flywheel Energy Storage in High Power Applications

The Center for Electromechanics (UT-CEM) is currently developing and testing a 2 MW, 130 kWh flywheel energy storage system as a critical element of the Advanced Locomotive Propulsion System (ALPS) Program. [1] The hybrid electric locomotive propulsion system consists of two major sub-systems: a gas turbine prime mover directly coupled to a 3 MW high speed synchronous generator and a 480 MJ flywheel energy storage system. Figure 1 is a simplified block diagram showing the major components of the propulsion system; the shaded elements are being actively developed by the ALPS program. The ALPS energy storage system consists of a high speed energy storage flywheel, a 2 MW high speed induction motor/generator, and a high frequency bi-directional power converter. In the course of developing the energy storage system for this demanding mobile application, UT-CEM identified and developed effective solutions for several critical technical issues which have challenged the use of high speed flywheels for high power energy storage applications. Ongoing work on other UT-CEM programs is also relevant to high power flywheel energy storage applications [2,3]. Although these designs were typically developed for a more challenging mobile environment, they are also appropriate for stationary installations. UT-CEM energy materials focus performance energy storage