Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative Perception Technology of Autonomous Driving in the Internet of Vehicles Environment: A Review

Cooperative perception, as a critical technology of intelligent connected vehicles, aims to use wireless communication technology to interact and fuse environmental information obtained by edge nodes with local perception information, which can improve vehicle perception accuracy, reduce latency, and eliminate perception blind spots. It has become a current research hotspot. Based on the analysis of the related literature on the Internet of vehicles (IoV), this paper summarizes the multi-sensor information fusion method, information sharing strategy, and communication technology of autonomous driving cooperative perception technology in the IoV environment. Firstly, cooperative perception information fusion methods, such as image fusion, point cloud fusion, and image–point cloud fusion, are summarized and compared according to the approaches of sensor information fusion. Secondly, recent research on communication technology and the sharing strategies of cooperative perception technology is summarized and analyzed in detail. Simultaneously, combined with the practical application of V2X, the influence of network communication performance on cooperative perception is analyzed, considering factors such as latency, packet loss rate, and channel congestion, and the existing research methods are discussed. Finally, based on the summary and analysis of the above studies, future research issues on cooperative perception are proposed, and the development trend of cooperative perception technology is forecast to help researchers in this field quickly understand the research status, hotspots, and prospects of cooperative perception technology.
Gases sanguíneos, electrolitos, variables metabólicas y determinantes del estado ácido-base en un grupo de Caballos Criollos Colombianos

Se determinaron y compararon los valores de los gases sanguineos, electrolitos, lactato, hematocrito y estado acido base tanto para sangre venosa como para arterial en 17 equinos del Centro de Veterinaria y Zootecnia CES; para lo que se utilizo el sistema Epoc Blood Analysis ®, analizador portatil de sangre que permite obtener resultados de gases, iones y metabolitos. Los resultados arrojados por este estudio muestran que hay una diferencia estadistica significativa (p< 0,05) para la glucosa arterial con respecto a la edad, para el lactato venoso con respecto al sexo y al comparar la sangre venosa contra la sangre arterial se obtuvo diferencia estadistica significativa en la presion parcial de oxigeno (pO 2 ), en la presion parcial de CO 2 (PCO 2 ), en la saturacion de oxigeno, cTCO 2, sodio, calcio ionizado, glucosa, bicarbonato, base exceso sanguineo (b), base exceso extracelular (ecf), PCO 2 (T)y PO 2 corregida por temperatura, lo que lleva a concluir que se deben tomar muestras arteriales para realizar valoraciones precisas de los pacientes y que las variables como la presion parcial de oxigeno, la presion parcial de dioxido de carbono y la saturacion de oxigeno dependen en gran medida de la temperatura ambiental, la temperatura del paciente y la altitud, condiciones que modifican las presiones parciales de los gases.
Nonautonomous solitons in the continuous wave background of the variable-coefficient higher-order nonlinear Schrodinger equation

We reduce the variable-coefficient higher-order nonlinear Schrdinger equation (VCHNLSE) into the constantcoefficient (CC) one. Based on the reduction transformation and solutions of CCHNLSE, we obtain analytical soliton solutions embedded in the continuous wave background for the VCHNLSE. Then the excitation in advancement and sustainment of soliton arrays, and postponed disappearance and sustainment of the bright soliton embedded in the background are discussed in an exponential system.
Parameter estimation for an internal variable model using nonlinear optimization and analytical

This paper demonstrates through examples that erroneous material constants for complex visco-plastic material models can be obtained from simultaneous parameter estimation by nonlinear optimization methods unless the laboratory load paths used in the fitting process give significant model response sensitivities to changes in all of the material parameters. A general procedure is proposed in which a nonlinear optimization algorithm is coupled with analytically/numerically derived response sensitivities to evaluate an unambiguous set of material parameters. Response sensitivities enter into the parameter estimation procedure in two ways. Relative response sensitivities are first used to identify an efficient test matrix that, when simulated with the model, give model responses that are sensitive to changes in each of the material parameters. Then the corresponding nonzero response sensitivities are used to construct the gradient and Hessian matrices in a gradient-driven optimization algorithm to evaluate the material parameters. A model for braze alloy is used to demonstrate that erroneous parameter values may result if not all of the relative response sensitivities are nonzero and distinct.
On the Averaging Principle

Typically, models with a heterogeneous property are considerably harder to analyze than the corresponding homogeneous models, in which the heterogeneous property is replaced with its average value. In this study we show that any outcome of a heterogeneous model that satisfies the two properties of differentiability and interchangibility is O(\epsilon^2) equivalent to the outcome of the corresponding homogeneous model, where \epsilon is the level of heterogeneity. We then use this averaging principle to obtain new results in queueing theory, game theory (auctions), and social networks (marketing).
Reconocimiento multimodal del estado emocional de un niño en un contexto educativo

Este trabajo propone una arquitectura para el reconocimiento multimodal de emociones de un niño relevantes al proceso de aprendizaje en un contexto educativo. La arquitectura propuesta incorpora las modalidades verbal, corporal, de tarea y fisiológica. En el desarrollo de la investigación, se exploran conceptos de educación y robótica, estados mentales, modelos de emociones e investigaciones efectuadas respecto al reconocimiento de emociones, en particular con técnicas y dificultades relativas al reconocimiento multimodal. Se exploran posibilidades de software existente y se aplican en la construcción de una solución integrada que implementa la arquitectura propuesta para el reconocimiento multimodal de emociones.
Pattern recognition using multi-dimensional hybrid feature extraction scheme in optical fiber distributed vibration sensing system

A multi-dimensional hybrid feature extraction scheme for optical fiber distributed vibration sensing system has been proposed in this work. Firstly, the hybrid features are extracted through using zero-crossing rate, wavelet packet energy entropy, empirical mode decomposition based kurtosis, skewness and multiscale permutation entropy. Secondly, an effective feature vector are built based on all the above-mentioned features. Finally, the established features are classified and recognized by a radial basis foundation neural network. A series of experiments have been implemented to validate the effectiveness of the proposed scheme. Results show that the proposed scheme can efficiently and accurately identify five common sensing patterns. Specifically, the average recognition accuracy of 99.2 % is achieved and the response time can be limited less than 1 s. Therefore, it is believed that the proposed pattern recognition scheme has a good potential in the application of the optical fiber distributed vibration sensing system.
The effect of spaceflight on the otolith-mediated ocular counter-roll

The otoliths of the vestibular system are seen as the primary gravitational sensors and are responsible for a compensatory eye torsion called the ocular counter-roll (OCR). The OCR ensures gaze stabilization and is sensitive to a lateral head roll with respect to gravity and the Gravito-Inertial Acceleration (GIA) vector during e.g., centrifugation. This otolith-mediated reflex will make sure you will still be able to maintain gaze stabilization and postural stability when making sharp turns during locomotion. To measure the effect of prolonged spaceflight on the otoliths, we measured the OCR induced by off-axis centrifugation in a group of 27 cosmonauts before and after their 6-month space mission to the International Space Station (ISS). We observed a significant decrease in OCR early post-flight, with first- time flyers being more strongly affected compared to frequent or experienced flyers. Our results strongly suggest that experienced space crew have acquired the ability to adapt faster after G-transitions and should therefore be sent for more challenging space missions, e.g., Moon or Mars, because they are noticeably less affected by microgravity regarding their vestibular system.
Digital Storytelling for Early Childhood Creativity: Diffusion of Innovation "3-D Coloring Quiver Application Based on Augmented Reality Technology in Children's Creativity Development"

One of the important activities in children's learning that is rarely explored is creativity. This is an important concept for the successful implementation of early childhood education programs. Every child's creative talent must be developed. Opportunities and learning resources in the form of an environment to explore sources and media need to be given to children in realizing their creative potential. The growing digital world and children's interest in devices such as smartphones are an opportunity for teachers to take advantage of interactive and interesting ICT-based learning resources and media through audio, visual and audio visual media. Utilization through the wise use of digital resources and media for children is an important part of learning. Digital Storytelling in coloring activities through the “Quiver 3-D Coloring based on augmented reality technology” application offers the integration of virtual objects into a real environment forming three-dimensional animations on smartphones, color pictures for children, presenting digital stories at the end of the activity, so that children have an interest so that their creativity will develop. The purpose of this research is to spread "augmented reality technology with Quiver-3D coloring application in developing children's creativity" by presenting digital stories. The approach used in this research is descriptive analysis method through a qualitative-quantitative approach. The data in this research were obtained by direct observation and research-related questions to informants. The results of the research show that: "children's creativity develops well through digital storytelling learning with 3-D Coloring based on Augmented Reality applications".
Une conjecture pour la cohomologie des diviseurs sur les surfaces rationelles génériques.

0. Introduction. Soient pl5. , pr des points suffisamment generaux (ou generiques) du plan projectif et ml9 . , mr des entiers positifs. Quelle est la dimension du Systeme lineaire des courbes planes de degre d passant par chaque pf avec la multiplicite m,? Dans [aHl], on a etudie certains aspects de cette question, faisant apparaitre des exceptions qu'on a eu la faiblesse de ne pas chercher ä comprendre. La presente note comble cette lacune, en eclairant ces exceptions par une conjecture, qu'on espere plus convaincante que celle avancee dans [aHl]. La nouvelle conjecture est naturelle des qu'on traduit le probleme initial en termes de diviseurs sur une surface rationnelle generique Sr: eile dit, grosso modo, qu'un diviseur sur Sr dont la trace sur toute courbe exceptionnelle de Sr est positive doit avoir la cohomologie naturelle, autrement dit doit etre non special (voir la definition plus bas). Cette conjecture est une Variante, qu'on espere plus expressive, d'une conjecture proposee par Harbourne ([bH2], 1.6.2). On explique ci-dessous comment cette conjecture permettrait de calculer la cohomologie de tous les diviseurs sur les surfaces rationnelles generiques et on recense les quelques cas ou la conjecture est demontree.
Markov chain Monte Carlo algorithms

We briefly describe Markov chain Monte Carlo algorithms, such as the Gibbs sampler and the Metropolis-Hastings (1953, 1970) algorithm, which are frequently used in the statistics literature to explore complicated probability distributions. We present a general method for proving rigorous, a priori bounds an the number of iterations required to achieve convergence of the algorithms.
The Value Relevance of Corporate Sustainability Performance (CSP)

There are two opposite views about corporate sustainability in the existing literature. Sustainability activities are considered as a source of long-term value creation for the shareholders’ interest whereas they also occupy scarce corporate resources and become an extra burden at the expense of shareholders. To examine these contradictory views, this study investigated the value relevance of CSP using a sample of 113 firms belonging to twelve (12) highly sustainable economies as ranked by the Global Sustainability Competiveness Index for the period 2015–2020. The CSP was measured through a Sustainability Index (SI) developed in this study using the GRI framework which takes into account all the three dimensions of sustainability, i.e., economic, environmental, and social. The results of the study showed that CSP significantly explains the variation in stock market prices and hence is value relevant in supporting the shareholders’ value-enhancing role of corporate sustainability. The results are useful for practitioners and policy makers in the field of corporate sustainability.
A Characterization of the Symmetric Square of a Curve

In this paper a new intrinsic geometric characterization of the symmetric square of a curve and of the ordinary product of two curves is given. More precisely it is shown that the existence on a surface of general type S of irregularity q of an effective divisor D having self- intersection D 2 > 0 and arithmetic genus q implies that S is either birational to a product of curves or to the second symmetric product of
The corona theorem in algebras of bounded analytic functions

A fuel supply manifold having a first sidewall with an opening extending therethrough and a control device sealingly disposed against the first sidewall. The manifold further has second and third sidewalls adjacent to the first sidewall which each have an indentation therein forming a lip extending from each edge of the first sidewall. Rigid fingers extend from the control device around the lips. Finally, a screw is threaded through one of the fingers so that it engages the manifold tightly securing the control device on the manifold.
Prognositc Significance of Microcystic Elongated and Fragmanted (MELF) Myometrial Invasion Pattern: A Retrospective Study

Objective: Endometrioid endometrial carcinomas (EEC) are the most commonly diagnosed malignancies of the female genital tract. Myometrial invasion depth is one of the most significant pathological prognostic parameters. Different morphological invasion patterns have been characterized. This study aimed to investigate the prognostic significance of the microcystic elongated and fragmented (MELF) myometrium invasion pattern in patients with EEC and its relationship with other clinicopathological parameters. Methods: This study included 101 patients with EEC in our institution between 2011 and 2020. The MELF pattern was evaluated in hematoxylineosin- stained sections. Pan-cytokeratin staining was performed on paraffin-embedded blocks of lymph nodes for cases without lymph node metastasis. Results: The MELF pattern was observed in 29 (29.8%) patients. It was significantly associated with lymphovascular invasion (p<0.001), pathologic stage (p=0.048), infiltrative pattern (p<0.001), and necrosis (p=0.005). No significant correlation was observed between the MELF pattern and overall and disease-free survival rates. Conclusions: The MELF pattern is associated with other prognostic parameters, but its prognostic significance for survival has not been found. If the MELF pattern is observed in the hysterectomy material for cases without lymph node dissection during the first surgery, these patients may need additional surgery or adjuvant therapy due to the high risk of lymphovascular invasion and lymph node metastasis.
Reinforcement Learning for Pass Detection and Generation of Possession Statistics in Soccer

We propose a reinforcement learning (RL) based technique to detect passes from the video of a soccer match. The detection of passes determines ball possession statistics of a soccer match. A sequence of video frames is mapped to a sequence of states, such as ball with team A or team B or ball not possessed either by team A or B. The agent of RL learns the frame-to-state mapping and the optimal policy to decide the mapping task. We propose a novel reward function by utilizing contextual information of the soccer game in order to help the agent decide the optimal policy. In this context, the advantage of RL is in the integration of a reward system in choosing an action that maps a video frame of a soccer match to one of three possible states. Unlike competing methods, we design the RL model in a way so that explicit identification of team labels of players is not required. We introduce a deep recurrent $Q$ -network (DRQN) to learn the optimal policy. For efficient training of the DRQN, we have proposed decorrelated experience replay (DER), a strategy that selects important experiences based on the correlations of the experiences stored in the replay memory. Experimental results show that at least 5.75% and 2.1% better accuracy are achieved in calculating pass and possession statistics, respectively, compared to similar approaches.
Feature Normalization Reweighting Regression Network for Sugar Content Measurement of Grapes

The measurement of grape sugar content is an important index for classifying grapes based on their quality. Owing to the correlation between grape sugar content and appearance, non-destructive measurements are possible using computer vision and deep learning. This study investigates the quality classification of the Red Globe grape. The number of collected grapes in the range of the 15~16% measure is three times more than in the range of <14% or in the range of the >18% measure. This study presents a framework named feature normalization reweighting regression (FNRR) to address this imbalanced distribution of sugar content of the grape datasets. The experimental results show that the FNRR framework can measure the sugar content of a whole bunch of grapes with high accuracy using typical convolution neural networks and a visual transformer model. Specifically, the visual transformer model achieved the best accuracy with a balanced loss function, with the coefficient of determination R = 0.9599 and the root mean squared error RMSE = 0.3841%. The results show that the effect of the visual transformer model is better than that of the convolutional neural network. The research findings also indicate that the visual transformer model based on the proposed framework can accurately predict the sugar content of grapes, non-destructive evaluation of grape quality, and could provide reference values for grape harvesting.
Librería de DEC usando Quad-Edge para CGAL

Este documento explica el proceso para construir una librería de Quad-edge que trabaja junto con una librería de DEC construida, para dar a CGAL una poderosa herramienta de simulación sobre sistemas de fluidos. Dando un resumen de la experiencia adquirida en el proceso y una metodología formal para probar la librería. Al final de este documento son dadas algunas conclusiones de este proceso.
Novel Quadratic High Gain Boost Converter With Adaptive Soft-Switching Scheme and Reduced Conduction Loss

In this article, an improved soft-switching quadratic boost converter is proposed. Instead of inserting an additional active clamp or auxiliary zero-voltage transition circuit at the switching node, the proposed topology connects the high-voltage switching node to the input diode node by replacing one of the input diodes with a low-rated switch. The proposed topology can attain soft-switching condition for all the switches and input diode turns-off under zero-current switching (ZCS). The operation of input-side switch not only aids zero-voltage switching (ZVS) turn-on for the main switch but also helps in reducing the conduction loss. Also, the input-side switch operates under ZCS turn-on and ZVS turn-off, making it a loss economical solution. An adaptive timing scheme for driving the input switch is proposed, which can ensure soft-switching condition under varying gain and load range. The detailed operational modes, analysis, and design considerations of the proposed topology are presented. A 250 W hardware prototype is built to validate the performance of the proposed converter operating at 100 kHz switching frequency. Results with adaptive soft-switching scheme shows that the converter is modulated to achieve its best efficiency condition under various system conditions. A peak efficiency of 96.1% at 155 W and efficiencies above 95.75% over a wide load range are achieved using all Si devices.
School Food Programming across Canada during the COVID 19 Pandemic: Program Reach and Modalities

ABSTRACT In 2020, after the COVID-19 pandemic resulted in widespread school closures and a consequent pause in school food programs (SFP), stakeholder groups soon found alternate methods for delivering meals and snacks to students. This paper examines the breadth of school food programming in Canada during the pandemic. SFPs collectively offered meals (breakfast was most frequent), food boxes, and gift cards and average weekly distributions were over 10,000 meals. In most cases, the programs provided enough food/coupons to feed multiple or all household members. Almost half the programs received funding from provincial/territorial governments and around two-thirds received charitable contributions.
Information integration for accurate foreground segmentation in complex scenes

The authors propose a hybrid framework that combines frame difference and background subtraction to integrate complementary sources of information for monocular video segmentation. This framework is modelled as an optimisation process of an energy function, which is established on a Markov random field (MRF) and optimised by Gibbs sampling. It provides a way to exploit different kinds of information obtained from frame difference and background subtraction. Central to the proposed method are two facts - that shape prior can be flexibly obtained from frame difference, and shadow removal can be integrated into the framework with a background texture model. The experiments show that this approach reliably and accurately performs on sequences that include different scenarios (indoors, outdoors) and also addresses several canonical segmentation problems, such as camouflage, foreground aperture and so forth.