Miracle-dz/UniFAR-FTUs huggingface dataset:
Propagation Path Loss Modeling and Outdoor Coverage Measurements Review in Millimeter Wave Bands for 5G Cellular Communications

The global bandwidth inadequacy facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm-wave) frequency spectrum for future broadband cellular communication networks, and mmWave band is one of the promising candidates due to wide spectrum. This paper presents propagation path loss and outdoor coverage and link budget measurements for frequencies above 6 GHz (mm-wave bands) using directional horn antennas at the transmitter and omnidirectional antennas at the receiver. This work presents measurements showing the propagation time delay spread and path loss as a function of separation distance for different frequencies and antenna pointing angles for many types of real-world environments. The data presented here show that at 28 GHz, 38 GHz and 60 GHz, unobstructed Line of Site (LOS) channels obey free space propagation path loss while non-LOS (NLOS) channels have large multipath delay spreads and can utilize many different pointing angles to provide propagation links. At 60 GHz, there is more path loss and smaller delay spreads. Power delay profiles PDPs were measured at every individual pointing angle for each TX and RX location, and integrating each of the PDPs to obtain received power as a function of pointing angle. The result shows that the mean RMS delay spread varies between 7.2 ns and 74.4 ns for 60 GHz and 28 GHz respectively in NLOS scenario.
Parametric system identification and robust controller design for liquid–liquid heat exchanger system

This study provides a step-by-step analysis of a parametric system identification procedure which provides a singleinput single-output, linear time invariant time-delay model of a liquid-liquid heat exchanger system. Different linear and blockoriented models are used to develop a control relevant identification model. The prediction error method is used to estimate the model parameters. From the simulation results, it can be found that the output error model (linear model) and Hammerstain- Wiener model (block-oriented model) provide the best model validation for a heat exchanger system at 72.23% and 81.5 % goodness-of-FIT, respectively. To achieve the control objectives of the system, the classical proportional-integral-derivative (PID) controller is used. For controller design, the linear model is considered. An industrial process is prone to encounter different uncertainties. Considering the time delay of the estimated linear model as the uncertainty, a ℋ ∞ criterion is used to find out the robust parameters of the PID controller. The developed controller satisfies the sensitivity constraints. Stability boundary locus of (K p ,K i ), (K p ,K d ) and (K d ,K i ) of the PID controller have been plotted to illustrate the robust parameters of the PID controller.
Kernel methods for Monte Carlo

This thesis investigates the use of reproducing kernel Hilbert spaces (RKHS) in the context of Monte Carlo algorithms. The work proceeds in three main themes. Adaptive Monte Carlo proposals: We introduce and study two adaptive Markov chain Monte Carlo (MCMC) algorithms to sample from target distributions with non-linear support and intractable gradients. Our algorithms, generalisations of random walk Metropolis and Hamiltonian Monte Carlo, adaptively learn local covariance and gradient structure respectively, by modelling past samples in an RKHS. We further show how to embed these methods into the sequential Monte Carlo framework. Efficient and principled score estimation: We propose methods for fitting an RKHS exponential family model that work by fitting the gradient of the log density, the score, thus avoiding the need to compute a normalization constant. While the problem is of general interest, here we focus on its embedding into the adaptive MCMC context from above. We improve the computational efficiency of an earlier solution with two novel fast approximation schemes without guarantees, and a low-rank, Nystrom-like solution. The latter retains the consistency and convergence rates of the exact solution, at lower computational cost. Goodness-of-fit testing: We propose a non-parametric statistical test for goodness-of-fit. The measure is a divergence constructed via Stein's method using functions from an RKHS. We derive a statistical test, both for i.i. d. and non-i.i. d. samples, and apply the test to quantifying convergence of approximate MCMC methods, statistical model criticism, and evaluating accuracy in non-parametric score estimation.
Gaze Point Tracking Based on a Robotic Body–Head–Eye Coordination Method

When the magnitude of a gaze is too large, human beings change the orientation of their head or body to assist their eyes in tracking targets because saccade alone is insufficient to keep a target at the center region of the retina. To make a robot gaze at targets rapidly and stably (as a human does), it is necessary to design a body–head–eye coordinated motion control strategy. A robot system equipped with eyes and a head is designed in this paper. Gaze point tracking problems are divided into two sub-problems: in situ gaze point tracking and approaching gaze point tracking. In the in situ gaze tracking state, the desired positions of the eye, head and body are calculated on the basis of minimizing resource consumption and maximizing stability. In the approaching gaze point tracking state, the robot is expected to approach the object at a zero angle. In the process of tracking, the three-dimensional (3D) coordinates of the object are obtained by the bionic eye and then converted to the head coordinate system and the mobile robot coordinate system. The desired positions of the head, eyes and body are obtained according to the object’s 3D coordinates. Then, using sophisticated motor control methods, the head, eyes and body are controlled to the desired position. This method avoids the complex process of adjusting control parameters and does not require the design of complex control algorithms. Based on this strategy, in situ gaze point tracking and approaching gaze point tracking experiments are performed by the robot. The experimental results show that body–head–eye coordination gaze point tracking based on the 3D coordinates of an object is feasible. This paper provides a new method that differs from the traditional two-dimensional image-based method for robotic body–head–eye gaze point tracking.
Analyzing Attitudes to Promote Sustainability: The Adaptation of the Environmental Concern Scale (ECs) to the Italian Context

The aim of this study was to examine the psychometric properties of the Environmental Concern scale (ECs) in the Italian context. Three studies were conducted. In Study 1, we carried out an exploratory factor analysis and a 2-factor solution-biospheric concern and egoistic concern—was confirmed. In Study 2, we tested the structure of the eight-items version of the ECs, using confirmatory factor analysis. The 2-factor structure was the best factorial solution. In this study we correlated the dimensions of ECs with life satisfaction and climate change worry. As expected, biospheric concern was significantly related to climate change worry, and egoistic concern was significantly related to life satisfaction. In Study 3, we tested the gender invariance. The ECs structure was the same for men and women. These studies demonstrate that the ECs possess good construct validity, factor structure, and invariance between genders. The measure can be used in the Italian context for future research.
The Traveling Salesman Problem with Drones: The Benefits of Retraversing the Arcs

In the traveling salesman problem with drones (TSP-mD), a truck and multiple drones cooperate to serve customers in the minimum amount of time. The drones are launched and retrieved by the truck at customer locations, and each of their flights must not consume more energy than allowed by their batteries. Most problem settings in the literature restrict the feasible truck routes to cycles (i.e., closed paths), which never visit a node more than once. Revisiting a node, however, may lower the time required to serve all the customers. Additionally, we observe that optimal solutions for the TSP-mD may retraverse arcs (i.e., optimal truck routes may contain the same arcs multiple times). We refer to such solutions as arc retraversing and include them in our solution space by modeling the truck route as a closed walk. We describe Euclidean instances where all the optimal solutions are arc retraversing. The necessity of arc retraversals does not seem to have been investigated in previous studies, and those that allow node revisits seem to assume that there always exists an optimal solution without arc retraversals. We prove that under certain conditions, which are commonly met in the literature, this assumption is correct. When these conditions are not met, however, excluding arc-retraversing solutions might result in an increase of the optimal value; we identify cases where a priori and a posteriori upper bounds hold on such increase. Finally, we prove that there is no polynomial-time heuristic that can approximate the metric TSP-mD within a constant factor, unless P = NP. We identify a (nonconstant) approximation factor explicitly when the truck can visit all the nodes.
Predicting Recurrence in Pancreatic Ductal Adenocarcinoma after Radical Surgery Using an AX-Unet Pancreas Segmentation Model and Dynamic Nomogram

This study aims to investigate the reliability of radiomic features extracted from contrast-enhanced computer tomography (CT) by AX-Unet, a pancreas segmentation model, to analyse the recurrence of pancreatic ductal adenocarcinoma (PDAC) after radical surgery. In this study, we trained an AX-Unet model to extract the radiomic features from preoperative contrast-enhanced CT images on a training set of 205 PDAC patients. Then we evaluated the segmentation ability of AX-Unet and the relationship between radiomic features and clinical characteristics on an independent testing set of 64 patients with clear prognoses. The lasso regression analysis was used to screen for variables of interest affecting patients’ post-operative recurrence, and the Cox proportional risk model regression analysis was used to screen for risk factors and create a nomogram prediction model. The proposed model achieved an accuracy of 85.9% for pancreas segmentation, meeting the requirements of most clinical applications. Radiomic features were found to be significantly correlated with clinical characteristics such as lymph node metastasis, resectability status, and abnormally elevated serum carbohydrate antigen 19-9 (CA 19-9) levels. Specifically, variance and entropy were associated with the recurrence rate (p < 0.05). The AUC for the nomogram predicting whether the patient recurred after surgery was 0.92 (95% CI: 0.78–0.99) and the C index was 0.62 (95% CI: 0.48–0.78). The AX-Unet pancreas segmentation model shows promise in analysing recurrence risk factors after radical surgery for PDAC. Additionally, our findings suggest that a dynamic nomogram model based on AX-Unet can provide pancreatic oncologists with more accurate prognostic assessments for their patients.
Trajectory Planning in Frenet Frame via Multi-Objective Optimization

Autonomous vehicles are an essential tool for promoting the development of intelligent transportation systems (ITS) and can effectively reduce traffic accidents caused by human errors. As an important part of the automatic driving software system, path planning is responsible for generating the motion trajectory of the vehicle, which is the primary factor determining driving quality. However, solution space construction and optimization problem formulation remain challenging research areas in the field of path planning. In this paper, we propose a multi-objective optimization algorithm for static obstacle avoidance to improve the comfort, safety and anti-deviation of the planned trajectory. We decouple the lateral and longitudinal motion of the vehicle using the Frenet frame and discretize the driving state space to generate target states of the vehicle. Based on the initial and target states, we generate a set of lateral and longitudinal motion trajectories using quintic and quartic polynomials, respectively. In addition, we design a cost function that comprehensively considers the comfort, safety, and deviation distance of the road center line by combining an acceleration check, curvature check, and collision check. As part of the cost function, we propose a novel method to quantify the safety of candidate trajectories considering the size of obstacles. The experimental results show that the proposed algorithm can quantize the safety of candidate paths and improve comfort 13.47%, 32.19%, 59.36% and 18.60% on a straight road, curvy road, intersection and U-shaped road, respectively. Furthermore, the algorithm can improve anti-deviation by 63.72%, 13.86%, 44.36%, and 45.56% on a straight road, curvy road, intersection and U-shaped road, respectively.
Exact Modal Methods

A rigorous formulation of the Exact Modal Method for lamellar structures is presented. A special attention is paid to the continuation of the electromagnetic field inside a lamellar layer that provides a large class of solutions of Maxwell's equations in presence of lamellar gratings. Next, it is shown that in each lamellar layer, there is a decoupling of the vector field equations into two independent scalar equations, which correspond to those of a multilayered stack. The techniques used for the calculation of the exact modes and eigenvalues are presented in detail. Finally, a numerical illustration shows the efficiency of the method.
SIMULAÇÃO DE ESCOAMENTOS SOBRE AEROFÓLIOS DE ALTA SUSTENTAÇÃO UTILIZANDO SOFTWARES LIVRES

The present work shows part of the results obtained in the final work of the first author, and the main objective is to obtain the coefficients of force on airfoils with high camber for the development of aircraft wings for aerodesign competition. Then, it presents a methodology that uses three open source softwares: FreeCAD to design the airfoil, Salome-Meca to generate the unstructured mesh over airfoils with high camber and OpenFOAM to perform the calculations of Computational Fluid Dynamics and obtain the force coefficients. The results obtained in the present work are compared with those obtained in a structured mesh and in experiments, for two airfoils, NACA 4415 and EPPLER 423. The simulations presented convergence and are close to the references, reaching a difference around 6.75% for the airfoil EPPLER 423. Finally, with the use of free software it is possible to obtain results very close to material experiments, being important tools in the development of projects.
Portable Microelectrochemical Sensors for Rapid and Sensitive Determination of Hesperidin in Citrus reticulate ‘Chachi’ Peel

Portable and low-cost analytical devices are essential for rapid detection of bioactive substrates in agricultural products. This study presents the first highly integrated microelectrochemical sensor based on pencil graphite for rapid and sensitive detection of hesperidin in Citrus reticulate ‘Chachi’ peel. The surface morphology and characterization as well as the electrochemical property of pencil graphite was investigated and discussed. A high electrocatalytic efficiency of hesperidin has been found at used pencil graphite-based microelectrodes. Kinetic analysis was carried out to further understand the electrochemical process of hesperidin at a pencil graphite microelectrode. Consequently, a portable and highly-integrated microelectrochemical sensor exhibits a sensitivity of 0.7251 μA cm−2 μM−1 and a detection limit as low as 25 nM (S/N = 3), and high selectivity was fabricated. Proposed microelectrochemical sensors were applied to electrochemically determinate the hesperidin content in the extract of Citrus reticulata “chachi” peel. As a result, the concentration of hesperidin in the actual real sample detected electrochemically with the proposed portable and low-cost microelectrochemical sensors is highly consistent to that obtained with a common chromatographic method, thus indicating the good reliability and that it can be used in practical applications.
Pullback attractor for a nonautonomous parabolic Cahn-Hilliard phase-field system

Our aim in this paper is to study generalizations of the Caginalp phase-field system based on a thermomechanical theory involving two temperatures and a nonlinear coupling. In particular, we prove well-posedness results. More precisely, the existence of a pullback attractor for a nonautonomous parabolic of type Cahn-Hilliard phase-field system. The pullback attractor is a compact set, invariant with respect to the cocycle and which attracts the solutions in the neighborhood of minus infinity, consequently the attractor pullback (or attractor retrograde) exhibits a infinite fractal dimension.
Power Measurement Using Adaptive Chirp Mode Decomposition for Electrical Vehicle Charging Load

Due to nonlinear components in the charging piles of electric vehicles, harmonics and nonstationary signals in the electric vehicle charging load bring voltage and current distortion, seriously affecting the accuracy of the power-related calculation in nonsinusoidal environments. This paper proposed a new approach to calculate the active power and root mean square values from decomposed components using the adaptive chirp mode decomposition (ACMD) method on voltage and current. The advantage of the ACMD-based method is that it correctly provides the power-related quantities of harmonics or nonstationary components for the electric vehicle charging load. The performance of the proposed method was verified using synthetic signals and simulation tests. The experimental results presented better estimations for each quantity defined in IEEE Standard 1459-2010, compared with the discrete wavelet transform approach.
Interaction Between A Tethered SphereAnd A Free Surface Flow

This paper analyses the vibrations and the flow field around a tethered sphere in a free surface flow in order to study the influence of the vortex shedding process on the dynamic response of the obstacle and on its oscillation frequency. The system is characterized by a low value of the mass ratio (ratio between the mass of the system and the added mass), a low value of damping and a low value of relative submergence (ratio between the depth of the current and the diameter of the sphere). The experiments are set up to measure the movements of the sphere in the main and transversal directions of the fluid flow with laser sensors and image analysis, whereas the description of the main wake structures of the flow downstream of the sphere are provided using the PIV technique.
Was COVID-19 the end of B2B Sales as We Know it? Understanding the New Skills and Competencies of the B2B Salesperson After a Disruption Event Such as COVID-19

Purpose: The aim of this study is to examine despite Covid-19 pandemic, several companies managed to grow their sales. This leads us to our research questions: what selling competencies make best salespeople post Covid-19 disruption? And, which of the sales competencies make to be most important toward their job performance? Theoretical framework: The B2B selling abilities post Covid-19 as the subject of this study has been little research by the academy and without a dominant theoretical framework, but rather a partial vision. This article contributes to integrating the scarce academic literature, which, as we demonstrate, is mainly empirical, with a theoretical domain. Design/methodology/approach: The use of established generic scales capturing each of the constructs of interest by surveying Key Account Managers in a B2B industry setting. Descriptive statistics, psychometric properties, pairwise correlations, and partial least squares structural equation modeling (PLS-SEM) where deployed. Findings: The results suggests that there is a positive direct effect of salesperson bricolage, adaptive selling, resiliency, salesperson' self-efficacy, and psychological flexibility with salesperson post-disruption performance. Lastly, a negative indirect effect is found between learning orientation, salesperson creativity, and salesperson grit. Research, Practical & Social implications: The study has focused on the proposal of what are the new sales competencies that B2B key account managers must develop to achieve a better sales performance, so managers must train and coach their B2B Key Account Managers (KAM) considering the new abilities needed (salesperson bricolage, adaptive selling, resiliency, salesperson' self-efficacy, and psychological flexibility) for sales success. Originality/value: The value of this study is a novel effort to understand what skills are needed to succeed in the post Covid-19 B2B selling environment.
Corporate hierarchies and workplace voice

Abstract We investigate whether workplace voice through institutionalized forms of employee representation (ER) affects the design of firm hierarchies. We look at the role of ER within a knowledge-based view of hierarchies, where the firm's choice of hierarchical layers depends on the trade-off between communication and knowledge acquisition costs. Using a sample of more than 20,000 private-sector firms in 32 countries, we find that the presence of ER is positively associated with the number of organizational layers, though the relationship is tempered by firm size. ER positively correlates with job training, skill development and enhanced internal communication via staff meetings. The analysis of managers' perceptions suggests the higher frequency of meetings in firms with ER does not lead to more delays in the implementation of organizational changes. Taken together, our findings point to ER as facilitating the flow of information to top decision-makers and hence reducing communication costs. This may enable the firm to economize scarce cognitive resources without retarding the accumulation of new shop-floor capabilities. We contribute to recent literature on organizational design by suggesting ER institutions as possibly relaxing the trade-off between communication and knowledge acquisition costs within firms.
Editorial: Genetic markers identification for animal production and disease resistance

Anhui Province Key Laboratory of Embryo Development and Reproduction Regulation, Anhui Province Key Laboratory of Environmental Hormone and Reproduction, School of Biological and Food Engineering, Fuyang Normal University, Fuyang, China, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China, Anhui Provincial Laboratory of Local Livestock and Poultry Genetical Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, China, Department of Animal Breeding and Genetics, Faculty of Veterinary and Animal Sciences, The University of Agriculture, Dera Ismail Khan, Pakistan