Miracle-dz/UniFAR-FTUs huggingface dataset:
How the current ECSS standards are compatible with digitalization in space systems engineering

The European Space Agency (ESA) Agenda 2025 made the digitalization in the core of the future space projects. In this context, compatibility of ECSS (European Cooperation for Space Standardization) with the digitalization initiatives is gaining more attention in ESA. ECSS is a European initiative established in 1994 to develop and maintain a “coherent, single set of standards” to support all European space activities. This is reflected in various projects at ESA in which ECSS is analyzed as the reference for space system digitalization projects. From the ECSS standards, ECSS-E-ST-10 is a reference standard for Systems Engineering. The ESA SysML solution is a main project using ECSS specially ECSS-E-ST-10 as the input for Systems Engineering digitalization. This paper will present an analysis of ECSS-E-ST-10 and its compatibility with ESA digitalization. To illustrate this approach, the ESA SysML solution is presented as an implementation case for Systems Engineering standard.
Evaluation of Impedance Measurement Using Spread Spectrum Time Domain Reflectometry

We evaluate the feasibility of spectral time domain reflectometry (STDR) and spread spectrum time domain reflectometry (SSTDR) as a new modality for impedance measurement to test energized/noisy systems over a very broad frequency spectrum (near dc to gigahertz) as well as multiple channels in parallel. We simulate how the S/SSTDR signal parameters (signal-to-noise ratio (SNR) frequency and length of the pseudo-noise (PN) signals) affect the accuracy and usable frequency band for reflection coefficient and impedance measurement. An initial measurement validation is included. We conclude with a recommendation of what will be required for a viable multichannel impedance (and reflection, transmission coefficient) measurement system for either energized or nonenergized systems, in noisy environments, that can test multiple channels simultaneously.
Filtration of micro-particles within multi-fiber arrays by adhesive DEM-CFD simulation

A 3D multi-time scale discrete element method-computational fluid dynamic (DEM-CFD) coupling approach was applied to investigate the filtration of micron-sized particles by different types of fiber arrays. Both the pressure drop and the filtration efficiency were examined to indicate the filtration performance of the fiber arrays. Fibers that were uniformly arrayed in a parallel or staggered manner were compared. Results showed that the staggered array showed a better performance than the parallel array in terms of both pressure drop and filtration efficiency. Further, we compared the performance of different staggered arrays, i.e. a regular case, one densified in the front layers and another densified in the back layers. The front densified array was found to enter the clogging and cake filtration stage in the shortest time, leading to the highest filtration efficiency, but the highest pressure drop. The back densified array still achieved a much higher filtration efficiency, despite a much lower pressure drop comparable to that of the regular array. The results suggest that the two kinds of densified arrays may be suited for different purposes, e.g. baghouse filters or breathing masks. 摘要目 的微米细颗粒在不同纤维排列所组成的滤料中的沉 积和穿透行为仍然缺少研究。 本文通过离散元-计算流体动力学耦合 (DEM-CFD) 双向耦合方法, 研究前加密、后加密以及规则错列阵列纤维 在过滤压降和捕捉效率方面的特性。 创新点1. 使用DEM-CFD流固双向耦合方法, 建立了适用于多纤维阵列过滤微米颗粒的数值模拟方法; 2. 得到并对比了不同排列形式的过滤压降和捕捉效率。 方 法1. 通过数值模拟, 得到顺列和错列排布纤维的过滤压降及捕捉效率 (图2和3、表2); 2. 通过数值模拟, 分析前加密、后加密错列排布纤维与规则错列排列纤维的优劣 (图6 和7), 并得出颗粒 在滤料中的沉积分布 (图8)结 论1. 错列纤维比顺列纤维提前进入堵塞期, 在沉积相同颗粒数时具有更低的压降, 且在清洁滤料期 具有更高的捕捉效率; 2. 前加密错列排布比后加密错列排布更早进入堵塞期, 且总体穿透颗粒数 量更少; 3. 前加密错列排布适用于工业滤料, 而 后加密错列排布适用于一次性个人防护用品。
A virtual flow meter downstream of various elbow configurations

When flow meters are installed in disturbed flow conditions caused by pipe configurations such as junctions or elbows, significant measurement errors can occur. With existing knowledge of the flow conditions, those errors can be corrected using suitable calibration factors. This paper presents a surrogate model based on computational fluid dynamics simulation results that can predict velocity profiles downstream of single and double elbows in- and out-of-plane. The simulated flow profiles are decomposed into a fully-developed and a disturbed part, which allows changing the Reynolds number and roughness of the pipe wall without performing additional simulations. Furthermore, proper orthogonal decomposition and interpolation using piecewise linear splines enables the real-time evaluation of the model for a wide range of curvature radii and distances between the elbows. By incorporating a measurement principle, calibration factors for different flow meter designs can be predicted. The model is validated on the example of an ultrasonic flow meter by comparison with measurement data obtained from a clamp-on flow meter.
Nonparametric triple collocation

Triple collocation has found widespread application in the hydrological sciences because it provides information about the errors in our measurements without requiring that we have any direct access to the true value of the variable being measured. Triple collocation derives variance‐covariance relationships between three or more independent measurement sources and an indirectly observed truth variable in the case where the measurement operators are additive. We generalize that theory to arbitrary observation operators by deriving nonparametric analogues to the total error and total correlation statistics as integrations of divergences from conditional to marginal probability ratios. The nonparametric solution to the full measurement problem is underdetermined, and we therefore retrieve conservative bounds on the theoretical total nonparametric error and correlation statistics. We examine the application of both linear and nonlinear triple collocation to synthetic examples and to a real‐data test case related to evaluating space‐borne soil moisture retrievals using sparse monitoring networks and dynamical process models.
Ideal L2 Self, Self-Efficacy, and Pragmatic Production: The Mediating Role of Willingness to Communicate in Learning English as a Foreign Language

The role that individual difference factors play in pragmatic learning behavior has received increasing attention in second-language (L2) pragmatics. However, there is a dearth of studies exploring the relationship between learners’ motivational variables and their pragmatic production. To address this gap, the present study aims to examine a model of the ideal L2 self, self-efficacy, willingness to communicate (WTC), and pragmatic production among English-as-a-foreign-language (EFL) learners. The study also seeks to explore the mediating role of WTC within this structural model. For this purpose, a total of 427 undergraduate students at a public university in China were recruited for an online survey. The structural validity of the questionnaires was established using a confirmatory-factor analysis, while the hypothesized structural relations between the variables were tested through structural-equation modeling. The results demonstrated that self-efficacy and WTC significantly and directly predicated pragmatic production. Nevertheless, the ideal L2 self influenced pragmatic production indirectly, through the mediation of WTC. The study concludes by providing implications for teaching and by offering suggestions for future research.
Examining Body Fat Percentage, Galvanic Skin Response, and Muscle Grip Strength in Female Hypothyroid Patients

Background The thyroid gland is an indispensable organ exerting control over the activity of multiple organ systems including the autonomic nervous system. This study attempted to monitor the variations in autonomic function parameters such as galvanic skin response (GSR) and muscle grip strength (HGS) in conjunction with changes in body fat percentage (BFP). Methodology This case-control study was conducted among 40 female hypothyroid patients as cases and 40 age-matched female healthy volunteers as controls. Anthropometric data were collected using standard techniques. GSR and HGS were measured using Equivital Sensory Electronic Module and Grip Force Transducer, respectively. Data extraction and analysis were done using the LabChart software. Results The mean age of the 40 female hypothyroid patients was 30.14 ± 5.91 years, whereas the mean age of the female controls was 29.37 ± 6.59 years. The waist circumference of cases was 85.81 ± 10.39 cm while that of controls was 80.90 ± 11.18 cm. The BFP of cases was 35.38% ± 6.74% while that of controls was 31.72% ± 5.63%. The GSR amplitude showed a significant difference between hypothyroid and healthy volunteers with values of 1.34 ± 1.14 μS and 2.40 ± 1.86 μS, respectively. The HGS indices showed no significant difference between the two groups. A statistically negative correlation was noted between BFP and GSR amplitude (-0.32), whereas a positive correlation was noted between BFP and mean handgrip strength (0.31) in hypothyroid patients. Conclusions The changes in BFP and autonomic function through GSR and HGS were evaluated in female hypothyroid patients with respect to healthy females. The interrelationship between anthropometry and autonomic function was also explored in this study. The findings of this study can augment prognosis in patients and ensure timely corrective treatment for improving quality of life.
Synthesis and Properties of (1R(S),5R(S),7R(S),8R(S))-1,8-Bis(hydroxymethyl)-6-azadispiro[4.1.4.2]tridecane-6-oxyl: Reduction-Resistant Spin Labels with High Spin Relaxation Times

Site-directed spin labeling followed by investigation using Electron Paramagnetic Resonance spectroscopy is a rapidly expanding powerful biophysical technique to study structure, local dynamics and functions of biomolecules using pulsed EPR techniques and nitroxides are the most widely used spin labels. Modern trends of this method include measurements directly inside a living cell, as well as measurements without deep freezing (below 70 K), which provide information that is more consistent with the behavior of the molecules under study in natural conditions. Such studies require nitroxides, which are resistant to the action of biogenic reductants and have high spin relaxation (dephasing) times, Tm. (1R(S),5R(S),7R(S),8R(S))-1,8-bis(hydroxymethyl)-6-azadispiro[4.1. 4.2]tridecane-6-oxyl is a unique nitroxide that combines these features. We have developed a convenient method for the synthesis of this radical and studied the ways of its functionalization. Promising spin labels have been obtained, the parameters of their spin relaxation T1 and Tm have been measured, and the kinetics of reduction with ascorbate have been studied.
Robust Emotion Recognition Across Diverse Scenes: A Deep Neural Network Approach Integrating Contextual Cues

The emotional context of a given environment can profoundly influence an individual’s feelings and responses. Nonetheless, current emotion recognition methodologies primarily concentrate on analyzing the target subject’s features and inadequately integrate these features with the contextual information of the scene. To tackle this challenge, we introduce a novel emotion recognition model that employs three independent and prioritized deep convolutional neural networks, alongside a feature fusion enhancement technique, to effectively merge facial information, body pose information, and subject features within the overall image. By amalgamating the performance of object detection models and deep convolutional network models, our framework capitalizes on the strengths of multiple approaches. Experiments with the Emotic dataset validate that our proposed model is technically innovative and surpasses existing methods and benchmark models in terms of feature fusion performance. Moreover, our evaluation of the proposed method on the Emotic dataset underscores the significance of environmental contextual information in shaping human emotions.
Short communication A step-by-step tutorial to use HierFstat to analyse populations hierarchically structured at multiple levels

The populations of parasites and infectious agents are most of the time structured in complex hierarchy that lies beyond the classical nested design described by Wright’s F-statistics (F IS, F ST and F IT). In this note we propose a user-friendly step-by-step notice for using recent software (HierFstat) that computes and test fixation indices for any hierarchical structure. We add some tricks and tips for some special data kind (haploid, single locus), some other procedure (bootstrap over loci) and how to handle crossed factors. # 2007 Elsevier B.V. All rights reserved.
Translator’s Creativity in Fiction: A Corpus-based Study of the Chinese Versions of Nineteen Eighty-Four

: On the basis of Aixela’s theory of translation approaches and strategies for culture-specific items as well as self-compiled parallel corpus model in Sketch Engine, this research sets out to investigate the creative employments of typical four-character Chinese idioms (chengyu and sizige) in the three Chinese translations of Nineteen Eighty-Four respectively by Dong Leshan, Sun Zhongxu, as well as Lau Shiu-ming. In accordance with the manual annotation of particular translation methods in each chengyu and sizige, and the aid of parallel corpus, the characteristics of chengyu and sizige uses in the three separate versions, as well as the circumstances of the translation approaches and strategies adoptions and their corresponding ratios are quantitatively revealed. Afterwards, the author further makes qualitative analysis on the motivations of three translator’s creative applications of chengyu and sizige from the main social translation specification in the society as well as their personal views for literary translation. The main purpose of this corpus-based study of translator’s creativity is to provide a new lexical perspective – typical four-character Chinese idioms – for the research on translator’s creativity.
Flow topologies in primary atomization of liquid jets: a direct numerical simulation analysis

The local flow topology analysis of the primary atomization of liquid jets has been conducted using the invariants of the velocity-gradient tensor. All possible small-scale flow structures are categorized into two focal and two nodal topologies for incompressible flows in both liquid and gaseous phases. The underlying direct numerical simulation database was generated by the one-fluid formulation of the two-phase flow governing equations including a high-fidelity volume-of-fluid method for accurate interface propagation. The ratio of liquid-to-gas fluid properties corresponds to a diesel jet exhausting into air. Variation of the inflow-based Reynolds number as well as Weber number showed that both these non-dimensional numbers play a pivotal role in determining the nature of the jet break-up, but the flow topology behaviour appears to be dominated by the Reynolds number. Furthermore, the flow dynamics in the gaseous phase is generally less homogeneous than in the liquid phase because some flow regions resemble a laminar-to-turbulent transition state rather than fully developed turbulence. Two theoretical models are proposed to estimate the topology volume fractions and to describe the size distribution of the flow structures, respectively. In the latter case, a simple power law seems to be a reasonable approximation of the measured topology spectrum. According to that observation, only the integral turbulent length scale would be required as an input for the a priori prediction of the topology size spectrum.
An approach to recognize air spring failure of high-speed trains using Lipschitz exponents

this paper addresses monitor of air spring failure of high-speed trains. A method using Lipschitz exponents and support vector machine is proposed. Key idea of the method is to obtain a singularity of carriage vibration signals, which is depicted by Lipschitz exponents. A continuous wavelet transforms modulus maxima are used to calculate singularity exponents. And air spring status is identified by support vector machine using the singularity feature vectors, which contain the number of the singular exponents, the maximum singular values, the minimum singular values, the mean of singular values and the relative standard deviation of the singular exponents. Experimental results prove that the proposed method is effective.
Fault diagnosis for high voltage circuit breaker based on VMD energy entropy and support vector machine

A new fault diagnosis method based on variational mode decomposition (VMD) is proposed in order to realize the fault identification of high voltage switches. Firstly, after preprocessing vibration signal, the feature extraction based on VMD energy entropy is analyzed. Subsequently, SVM is utilized to calculate fault type by utilizing the extracted features. Parameter optimization is solved by grid search algorithm to improve the performance of SVM. Verification of the scientific nature of this method for fault diagnosis is provided by field data, which was obtained through an experiment on a SF6 circuit breaker with a high 35kV voltage. The break vibration data was measured under normal operation, actuator fault, buffer spring invalidity, and loosing of base screw.
Disturbance-Induced Changes in Population Size Structure Promote Coral Biodiversity

Reef-building coral assemblages are typically species rich, yet the processes maintaining high biodiversity remain poorly understood. Disturbance has long been thought to promote coral species coexistence by reducing the strength of competition (i.e., the intermediate disturbance hypothesis [IDH]). However, such disturbance-induced effects are insufficient to inhibit competitive exclusion. Nevertheless, there are other mechanisms by which disturbance and, more generally, environmental variation can favor coexistence. Here, we develop a size-structured, stochastic coral competition model calibrated with field data from two common colony morphologies to investigate the effects of hydrodynamic disturbance on community dynamics. We show that fluctuations in wave action can promote coral species coexistence but that this occurs via interspecific differences in size-dependent mortality rather than solely via stochastic fluctuations in competition (i.e., free space availability). While this mechanism differs from that originally envisioned in the IDH, it is nonetheless a mechanism by which intermediate levels of disturbance do promote coexistence. Given the sensitivity of coexistence to disturbance frequency and intensity, anthropogenic changes in disturbance regimes are likely to affect coral assemblages in ways that are not predictable from single-population models.
A novel iterative PCA–based pansharpening method

ABSTRACT Image pansharpening methods are usually grouped into two main classes: the spectral methods and the spatial methods. For the first class, the multispectral image undergoes a spectral transformation and then one of the resultant components is totally substituted with the panchromatic image, hence leading to a considerable color distortion compared with the second class. In the literature, this issue is addressed by integrating the wavelet transform to the spectral methods in order to transfer only the spatial details of the panchromatic image. Furthermore, the spatial information quantity transferred during the fusion is usually defined by the resolution ratio between the multispectral and panchromatic images, and this is, however, not necessarily the optimal quantity providing the best images. Therefore, a simple iterative Principal Component Analysis (PCA) based method is proposed in this letter, to continuously transfer the spatial information from the panchromatic to the multispectral image until the best fused image is obtained. The spatial distortion Ds of the Quality with No Reference (QNR) index is used as a stopping criterion. The experiments applied on the Worldview–3 images show that the suggested method presents the best visual and numerical results comparatively to the PCA and the Additive Wavelet Principal Component (AWPC) methods.
Arabic Diacritics Restoration Using Maximum Entropy Language Models

Restoring the input text's diacritics is crucial in developing Arabic text-to-speech systems. A few rules can be used to implement phonetic transcription when diacritics are present. The preferred method for recovering Arabic diacritics is based on scoring $n$-gram language models. By utilizing maximum entropy (MaxEnt) language models, a novel procedure is presented in this work for restoring Arabic diacritics. The MaxEnt language models are used to score the diacritized words given previous words in a given sequence. Hence, dynamic programming (DP) efficient decoder retrieves the most probable word sequence conditioned on the input undiacritized word sequence. The Tashkeela corpus was used to evaluate the effectiveness of the suggested technique. Our methods were more efficient than the most sophisticated algorithms available at the time.
A Method of Converting ANN to SNN for Image Classification

Spiking neural networks (SNNs) is a deep-learning model with ultra-low power consumption, which have shown great potential on edge devices. Because of the non-differentiable problem, the SNN model is not easy to train. The most common way to build an SNN is ANN-to-SNN conversion. This work gives a method for conversion, which will have low accuracy loss and low latency on image classification task. The main idea of the conversion is to create a connection between the dynamics of SNN neurons and the activation of ANN neurons. Then the parameters in SNN are replaced by the ANN parameters after training. To improve accuracy while reducing latency, there is a clipping layer added after ReLU layers in ANN structure. To reduce the latency, the part special potential of the SNN neurons is initialized to a higher value. To verify the effectiveness of the algorithm, MNIST dataset is used for classification experiments. The trained ANN and converted SNN are tested on a testing set with size 10000. The accuracy of SNN will reach 96.18% with only 2 time steps, and will rise to 97.68% in 16 time steps. The accuracy loss is only 0.02%.
The Strategies for Improving the Efficiency of Content Marketing in the Field of E-Commerce

Since the development of the Internet and digitization in modern time, with more powerful big data analysis capabilities, people’s lifestyles, especially their shopping habits, have mainly transformed from offline to online. Having seen the huge benefit hidden behind the internet, many e-commerce enterprises appear and join in the competition. They are taking much more control over the Internet and taking up growing market share in the whole market. In the meanwhile, customers are requiring more autonomy. Therefore, it’s essential for e-commerce enterprises to improve the efficiency of content marketing in order to attract more potential customers and build a better relationship with them. However, with the upgrade of content marketing, the marketing requirements of e-commerce enterprises are raised, and many related problems arise. By reviewing some relevant research and analyzing the data, this paper aims to offer some useful suggestions to e-commerce enterprises about the improvement of the efficiency of content marketing. This paper finds that there are still some problems existing in the process of improving efficiency and the most effective methods include content quality improvement, customer-oriented content creation, regulatory system completion, talents’ help and enterprise synergy. Enterprises are bound to pay attention to not only their inbound effort, but also some outbound help.