Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Essential Oil of Thyme (Thymus vulgaris L.) or Increasing Levels of a Commercial Prebiotic (TechnoMOS®) on Growth Performance and Carcass Characteristics of Male Broilers

Simple Summary Since the ban of in-feed antimicrobial with auxin purposes, a wide range of herbal plants have been tested as growth promoters. In particular, thyme and prebiotic compounds, such as mannan-oligosaccharides, have been tested in animal production due to their antibacterial, antifungal, and antioxidant properties and antimicrobial, anticoccidial, and anti-inflammatory actions. Thyme essential oils and TechoMOS® positively affected the growth performance of Ross male broiler during the grower phase, reducing the feed intake and improving feed conversion ratio. However, increasing dose of TechoMOS® only affected the broiler performance on a week-to-week basis and no difference has been registered between same dosage of TechoMOS® and TEO. Dietary treatments, both TechoMOS® and TEO, did not affect the carcass characteristics at 42 days. Abstract To investigate the effect of thyme (Thymus vulgaris L.) essential oil (TEO) or increasing inclusion of a prebiotic (TechnoMOS®) on growth performance and carcass characteristics of Ross 308 broilers, 400 one-day-old male broilers (43.5 g, as mean of body weight) were placed in 20 pens (2.0 × 1.0 m, with a floor area of 0.10 m2 per bird) in groups of 20, and each pen cage was assigned to a specific dietary treatment (four replicates per each one). The dietary treatments included basic diet (no additive; CTR), basic diet including 0.025%, 0.075%, or 0.125% of TechnoMOS® (MOS025, MOS075, and MOS125, respectively), or basic diet including 0.075% thyme extract (TEO075). All dietary treatments were offered from the beginning of the study until the end of the trial. There were no effects of MOS or TEO on carcass characteristics. No significant effects of treatment on weight gain were obtained on a week-by-week basis; however, CTR birds gained less weight during the grower phase and overall compared with MOS birds. The same contrast for feed intake revealed that CTR birds had greater feed intake than MOS birds during both the grower phase and overall (492.18 g and 486.35 g, respectively). In conclusion, treated groups showed an improved feed conversion ratio.
Analytical development of single crystal Macro Fiber Composite actuators for active twist rotor blades

A Macro Fiber Composite (MFC) is a piezoelectric fiber composite which has an interdigitated electrode, rectangular cross-section and unidirectional polycrystalline piezoceramic (PZT) fibers embedded in the polymer matrix. A MFC actuator has much higher actuation performance and flexibility than a monolithic piezoceramic actuator. Moreover, the single crystal piezoelectric material exhibits much higher induced strain levels, energy density and coupling than those of polycrystalline piezoceramic materials. Thus, the performance of an MFC can be improved by using single crystal piezoelectric fiber instead of polycrystalline piezoceramic fiber. This study investigates the analytical modeling, material properties and actuation performance of an MFC using single crystal piezoelectric material (single crystal MFC). For single crystal MFC, the mechanical properties are calculated by the classical lamination theory, and the uniform fields model (UFM) is adopted to predict piezoelectric strain constants. In addition, the actuation performance of the single crystal MFC with the active twist rotor blade is studied. The material properties and actuation performance of single crystal MFC are compared with those of standard MFC.
Robust wake steering control design in a wind farm for power optimisation using adaptive learning game theory (ALGT) method

In this paper, the robust wake steering control concept for wind farms is presented based on the control functions of the neighboring wind turbines. In wind farms, to increase the total output power, the effects of wake on downstream wind turbines should be considered. Hence, in this research, for output power maximisation, a robust Adaptive Learning Game Theory (ALGT) optimisation method is developed. The proposed procedure is based on the game theory method, but that enables coordination via repeated interactions using control functions of the neighboring turbines in a wind farm for a squarely payoff-based scenario where the turbines have access only to measurements from their neighbors. This robust optimisation method in the presence of uncertainty enables an interaction framework that creates a set of joint control functions. In this method, each turbine makes an independent decision in every iteration based on the control laws of each localised areas.
A comparison of IGBT models for use in circuit design

In choosing an accurate IGBT model for power electronic circuit design, physics-based models are frequently preferred due to their high accuracy. In this paper, an experimental comparison of two such models is made, using parameters extracted from experimental measurements. The comparison focuses on a particular IGBT, the BUP202, in three situations typical of low power (600 V, 10 A) applications.
Smart electromagnetic structures: a neural network antenna

Artificial neural networks(ANN5) and their ability to model and control dynamical systems for smart structures including sensors actuators and plants are being considered in our lab. Both linear and non-linear systems have been successfully modeled. We are presently working on two diverse regimes smart mechanical systems and smart electromagnetic systems. In order to better understand neural controllers as used in the smart electromagnetic structures we have directed our study of ANNs toward understanding the ability of the network to approximate system responses. We are training networks to mimic the desired output of the system. The damped sinusoid was chosen as the model and was approximated using a Jordan-like 8 iterative network. The results to date indicate that the ANNs can easily mimic these systemsthe question is whether the mechanism that the network applies can be related to the mechanisms that we understand for classical analysis. Sensor preprocessing represents a significant element in the smart material and structure concept. We are looking at certain network architectures as sensor preprocessors. Results from both these areas will be presented in this paper.
On the correction of the Bernoulli-Euler beam theory for smart piezoelectric beams

The present paper is devoted to the development of a simple Bernoulli-Euler type beam theory for smart piezoelectric composite beams. It is the scope of this paper to formulate a formally purely mechanical beam theory taking into account the coupling to the electric field by means of the direct piezoelectric effect. Different electric boundary conditions, electroded layers with either the electric potential or the total charge being prescribed, or non-electroded layers, are considered. Approximations for the electric field depending on the actually realized electric boundary conditions are then utilized in the present formulation. Finally a beam model is obtained taking into account the electromechanical coupling by means of effective stiffness parameters. Results obtained by using this simple model are compared to two-dimensional electromechanically coupled finite element calculations. A very good agreement for both the mechanical and the electrical response is found, showing that the accuracy of the present one-dimensional theory is comparable to that of the two-dimensional finite element calculations.
Operational Planning and Programming of Autonomous Underwater Vehicles

Future military autonomous underwater vehicles (AUVs) will perform multiple missions, handle many contingencies, and require broad domain knowledge. The intelligence of these multi-mission AUVs will require complex mission-contingent software. AB a result, programming an AUV for a mission promises to be an increasingly formidable task, even as it increasingly needs to be performed in the field by operational personnel, not computer scientists. We approached this problem by partitioning AUV programming into several software development stages and distributing the AUV intelligence in a hierarchical control system that supports partitioned programming. Our programming/control concept has three operational levels: 1) onshore development of operational tactics, standard rules of operation, and contingency responses; 2) pre-deployment programming by operational specifications that translate automatically into sortie programs made up of pre-defined tactics; 3) real-time dynamic situation assessment and planning according to the sortie programming. These programming/control operations are implemented in the Honeywell STASR AUV testbed, including: 1) an interpreted Control Planning Language that rep resents both tactics and sortie programs; 2) a graphical tactics and sortie programming system design; 3) a hierarchical tactics execution system. The STASR approach has been used to develop intelligent AUV transit tactics that have been tested in sortie programs for a variable mission environment.
Broadband Planar Superstrate Antenna for

In this paper, a new planar superstrate antenna concept suitable for integration with millimeter wave (mmWave) transceiver integrated circuits (ICs) is presented. The antenna is printed on the bottom of a dielectric superstrate with a ground plane below. The new design provides high bandwidth and high efficiency. Two different examples of the new concept have been designed and manufactured for the 60 GHz industrial scientific medical (ISM) band using folded dipoles. Simulated and measured input impedance matching and far field radiation patterns for both antennas will be shown and discussed. Both designs achieve over 10% bandwidth while maintaining better than 80% efficiency. Index Terms—Millimeter wave (mmWave) antenna, planar dipole, superstrate antenna.
Effectiveness of Origin-Destination Matrix Correction Procedure Using Traffic Counts

The estimation and correction of the origin-destination (O-D) matrix from traffic counts is a classical procedure usually adopted in transport engineering by practitioners to improve the overall reliability of transport models. Recently, Papola and Marzano showed through laboratory experiments that this procedure is generally not able to provide an effective correction of the O-D matrix. This result can be justified from a theoretical standpoint because of the lower number of stochastic equations (independent observed link flows) with respect to the unknowns (O-D flows). The current study confirms, first, that this circumstance represents the main reason for failure of the procedure by showing that good correction is generally obtained when the number of equations is greater than the number of unknowns. Then, since this circumstance does not occur in practice, in which the number of O-D pairs is usually much greater than the number of link counts, the study explores alternative assumptions and contexts that allow for a proper balance between unknowns and equations. In more detail, this balance can be achieved by moving to within-day dynamic contexts, in which a much larger number of equations is generally available. Obviously, to bound the corresponding increase in the number of unknowns, specific reasonable hypotheses in O-D flow variation across time slices must be introduced. In that respect, the effectiveness of the O-D matrix correction procedure in the usually adopted linear hypothesis on the dynamic process evolution of O-D flows and under the assumption of constant distribution shares is analyzed.
MODELING AND SIMULATION OF PHYSICAL LAYER OF IEEE 802.22 OVER A MULTIPATH FADING CHANNEL

IEEE 802.22, also known as Wireless Regional Area Network (WRAN), is the newest wireless standard developed for remote and rural areas. In this work, an overview of the standard, and more specifically its physical (PHY) layer is evaluated. For this purpose the PHY layer is modeled using SIMULINK tool and derived the received constellation mapping of the system for different code rates and modulation schemes with multipath noisy channel. In this paper Rayleigh multipath channel model is used in addition of AWGN channel to analyze the 802.22 PHY layer for likely practical conditions.
Time domain equaliser design for DWMT multicarrier transceivers

A novel time domain equaliser (TEQ) design is proposed for discrete wavelet multitone (DWMT) systems. The proposed scheme is tested on a number of carrier-serving-area (CSA) loops. The results show the DWMT systems using the proposed TEQ outperform their discrete multitone (DMT) counterparts by 5 to 10 dB.
Design of a Fixed-Wing UAV Controller based on Adaptive Backstepping Sliding Mode Control method

In this paper, an advanced control method is proposed for a fixed-wing unmanned aerial vehicle (UAV) to maintain the stabilization of its altitude, attitude, and velocity. The mathematical model of a fixed-wing UAV is very complicated because of its characteristics of nonlinearity and large extent of multi-variable coupling. Thus, to design the relevant controller is also difficult. In addition, during the operation of a fixed-wing UAV, various uncertainties and disturbances will occur, which will make the control process harder to accomplish. To solve these problems, this study designs a variable-structure controller with multiple algorithm fusion. The design mainly adopts the backstepping sliding mode control method to simplify the complex nonlinear mathematical model, and an adaptive law is introduced to estimate the uncertainty and disturbance of the system. Subsequently, the tracking error of the controller is proved to converge to zero using Lyapunov’s second method. Finally, it is verified that the controller has the ability to stably control a fixed-wing UAV by numerical simulation and can overcome the disturbance and uncertainty. The buffeting also can be eliminated by an adaptive law.
Failure mechanism of winding insulations in inverter-fed motors

The failure of magnet wires under repetitive pulses as seen in inverter-fed motors cannot be attributed to a single factor but is a result of the combined effects of partial discharge, dielectric heating, and space charge formation. Voltage overshoots produced by PWM drives may be above discharge inception voltage. Partial discharge may therefore be present in inverter-fed motors. In addition to partial discharge, pulses with a fast rise time and high frequency enable the insulation to generate local dielectric heating, which increases the local temperature. The degradation rate of the insulation is therefore increased. Furthermore, the fast rise and fall of pulses make it possible for space charges to accumulate in the winding insulation and on its surface.
Trade negotiations: teaching consensus

Abstract International negotiations, particularly in international organisations with a large number of members, can be long and fraught. Reaching consensus between a large number of countries is not an easy task and this point is often ignored in news reports relating to international negotiations. This article argues that when teaching students about the conduct of international negotiations, their understanding can be greatly enhanced by the use of active learning techniques such as role playing, simulations and games. However, much of the literature describes simulations which take time to prepare and are often run over several hours or days. This article argues that we need to develop shorter, seminar length simulations which students can relate to in order to help their understanding of the issues and processes around negotiations. Highlighting the consensus process in the World Trade Organisation (WTO) and drawing on experience of teaching students about the WTO, this article elaborates a seminar length exercise which can be used to illustrate some of the negotiation processes in the WTO while at the same time teaching students about the process and difficulties of consensus building with a familiar scenario.
PMSG‐based variable speed wind energy conversion system using Vienna rectifier

In this paper, a new variable-speed wind energy conversion system (WECS) with permanent magnet synchronous generator (PMSG), Vienna rectifier and three-level neutral point clamped (NPC) inverter is proposed. Vienna rectifier is used for flux vector control of PMSG, maximum power point tracking (MPPT) of wind turbine, PMSG efficiency optimization, and balancing of two rectified DC voltages. As power conditioner, a three-level NPC inverter is used to deliver energy to the grid. Vector control of the inverter provides the ability to regulate power factor to any desired value. The results of two simulations (for back-to-back inverter and the proposed topology) are presented and compared. The results verify improved efficiency of the proposed WECS compared to WECS using back-to-back inverter. Copyright © 2010 John Wiley & Sons, Ltd.
Teachers’ Perception of Advantages and Disadvantages of Kahoot!

Many instructors around the world have been using different Game-based Student Response Systems due to the rise in the variety and availability of digital educational and commercial games. Kahoot, one of the most popular among these systems, provides a game experience by combining theory of intrinsic motivation and game-flow with the help of audio/visual aids. In spite of the numerous attempts to evaluate this game-based tool according, limited research has focused on teachers’ perceptions of the potential strengths and weaknesses of Kahoot, specifically in GCC countries. Employing focus group interviews, this study attempts to shed some light on the potential advantages and disadvantages of Kahoot by gathering the views of teachers who work at the Center for Preparatory Studies at a university in Oman. Results indicate that although teachers believe that Kahoot is qualified with several positive features, it still suffers from several disadvantages in which it can definitely improve.
SelectiveEC: Towards Balanced Recovery Load on Erasure-coded Storage Systems

Erasure coding (EC) has been commonly used to offer high data reliability with low storage cost. Upon failures, the lost blocks are recovered in batches. Due to the limited number of stripes, the data layout within a batch is non-uniform. Together with the random selection of source and replacement nodes for recovery tasks, the recovery workload among live nodes is skewed within a batch, which severely slows down failure recovery. To solve this problem, We present SelectiveEC, a new recovery task scheduling module that provides provable network traffic and recovery load balancing for large-scale EC-based storage systems. It relies on bipartite graphs to model the recovery traffic among live nodes. Then, it intelligently selects tasks to form batches and carefully determines where to read source blocks or to store recovered ones, using theories such as a perfect or maximum matching and k-regular spanning subgraph. SelectiveEC supports single-node failure and multi-node failure recovery, and can be deployed in both homogeneous and heterogeneous network environments. We implement SelectiveEC in HDFS, and evaluate its recovery performance in a local cluster of 18 nodes and AWS EC2 of 50 virtual machine instances. SelectiveEC increases the recovery throughput by up to 30.68% compared with state-of-the-art baselines in homogeneous network environments. It further achieves 1.32x recovery throughput and 1.23x benchmark throughput of HDFS on average in heterogeneous network environments, due to the straggler avoidance by the balanced scheduling.
Travel motivations and constraints of Portuguese retirees

ABSTRACT Retirees have been growing in importance as a consumer segment targeted by the tourism industry, namely because they can minimize the typical seasonality of tourism and increase its sustainability. This study aims to contribute to a more in-depth knowledge of retirees’ behaviour and has two objectives: (i) describe tourist behaviour of seniors prior to and after retirement; (ii) identify and analyse retired consumers’ current motivations and constraints towards tourism. Qualitative research was conducted comprising interviews with 40 Portuguese retirees. The results indicate a diversity of experiences regarding tourism activities both before and after retirement, evidencing that past experience stands out as a determinant of retirees’ tourism behaviour. Moreover, three distinct segments of tourists emerge: the experts, the new tourists, and the non-tourists.
Dynamic modelling of recuperative gas turbines

Abstract This paper describes the mathematical model and the computational procedure adopted for the development of a modularly structured computer code able to simulate the dynamic behaviour of recuperative gas turbine power plants. For accurate simulation of the turbine components, the model includes a stage-by-stage procedure for the air-cooled turbine based on the blade geometry and the characteristics of the cooling system. The counter-flow surface heat exchanger, assumed as recuperator, is described by a set of partial differential equations, giving à One-dimensional description of the temperature for air, hot gas and metal. A single-shaft recuperated cycle gas turbine, provided with compressor variable inlet guide vanes, is analysed. The transient cases caused by a step variation in the fuel flow and compressor guide vanes geometry are simulated and a linearized model is obtained, in order to identify the dynamic behaviour of the gas turbine and to design a multivariable controller. Finally, the transient case of a controlled turbine after a sudden variation in the electric load is simulated.
A Novel Method for Quantitative Analysis of C-Reactive Protein Lateral Flow Immunoassays Images via CMOS Sensor and Recurrent Neural Networks

Objective: To design and implement an easy-to-use, Point-of-Care (PoC) lateral flow immunoassays (LFA) reader and data analysis system, which provides a more in-depth quantitative analysis for LFA images than conventional approaches thereby supporting efficient decision making for potential early risk assessment of cardiovascular disease (CVD). Methods and procedures: A novel end-to-end system was developed including a portable device with CMOS camera integrated with optimized illumination and optics to capture the LFA images produced using high-sensitivity C-Reactive Protein (hsCRP) (concentration level < 5 mg/L). The images were transmitted via WiFi to a back-end server system for image analysis and classification. Unlike common image classification approaches which are based on averaging image intensity from a region-of-interest (ROI), a novel approach was developed which considered the signal along the sample’s flow direction as a time series and, consequently, no need for ROI detection. Long Short-Term Memory (LSTM) networks were deployed for multilevel classification. The features based on Dynamic Time Warping (DTW) and histogram bin counts (HBC) were explored for classification. Results: For the classification of hsCRP, the LSTM outperformed the traditional machine learning classifiers with or without DTW and HBC features performed the best (with mean accuracy of 94%) compared to other features. Application of the proposed method to human plasma also suggests that HBC features from LFA time series performed better than the mean from ROI and raw LFA data. Conclusion: As a proof of concept, the results demonstrate the capability of the proposed framework for quantitative analysis of LFA images and suggest the potential for early risk assessment of CVD. Clinical impact: The hsCRP levels < 5 mg/L were aligned with clinically actionable categories for early risk assessment of CVD. The outcomes demonstrated the real-world applicability of the proposed system for quantitative analysis of LFA images, which is potentially useful for more LFA applications beyond presented in this study.