esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Experimental Setup and Testing  
The hydro-pneumatic spring test platform, as shown in Figure 9, mainly consists of three parts: the test platform body, the hydraulic pump station, and the control cabinet. To fit the actual use, the hydro-pneumatic spring is connected and installed on the test bench with a pin shaft. The control cabinet is programmed to control the hydraulic system, to realize the reciprocating movement of the hydro-pneumatic spring driven by the hydraulic cylinder on the test bench. The test platform can detect the sealing condition of the hydro-pneumatic spring's sealing ring at different compression rates and assess the wear of the sealing ring after testing.  
Figure 8: Pressure impulse cycle.  
Figure 9: Hydro-pneumatic spring test bench.  
In practical usage, the hydro-pneumatic spring can be divided into two operating conditions: (1) When the vehicle is stationary, the high-pressure hydraulic fluid inside the hydro-pneumatic spring does not subject the sealing ring to high-pressure impacts. In this case, the sealing ring is subjected to static pressure loading. (2) When the vehicle is in motion, especially on uneven road surfaces, the hydro-pneumatic spring undergoes reciprocating motion, and the sealing ring starts to experience pressure impacts. To address these two scenarios, and based on the conclusions obtained from simulations, the following experimental studies were conducted.  
The experimental verification was divided into two parts. The first part verified the sealing conditions of the sealing ring when the compression rates were approximately 10% and 15% under static loading conditions of the hydro-pneumatic spring. The second part verified the sealing conditions of the sealing ring when the compression rates were approximately 10% and 15% under dynamic loading conditions of the hydro-pneumatic spring. These experiments were aimed at validating the sealing performance of the sealing ring at different compression rates, as determined in the simulation. It is important to note that due to machining errors during the actual manufacturing of the sealing grooves, there may be slight discrepancies in the actual compression rate of the sealing ring.
# Automatic Needle Route Proposal in Preoperative Neck CT for Injection Laryngoplasty
## 2 Methodology  
We compute the optimal needle route based on the vocal fold locations detected by the RL agent [7]. The input neck CT can be viewed as a 3D volume, where we denote the detected locations of the right and left folds by \(\mathbf{q}_{r}\) and \(\mathbf{q}_{l}\), respectively. Our goal is to find the optimal needle paths \(\overline{\mathbf{p}_{r}\mathbf{q}_{r}}\) and \(\overline{\mathbf{p}_{l}\mathbf{q}_{l}}\) to the vocal folds, where \(\mathbf{p}_{r}\) and \(\mathbf{p}_{l}\) represents the optimal needle insertion points in the neck skin for the right and left folds.  
Our needle route computation method consists of four major stages. First, we obtain the vocal fold locations in the neck CT using the previously proposed RL agent [7]. Second, we identify and segment the critical regions for injection. Third, we define the search space containing all possible routes. Finally, we define a cost function to find the optimal needle route. Figure 1 illustrates the proposed method. In the following, we describe each stage of our method in detail.
## 1 Introduction
Note that both materials are industrially scalable, economically viable, abundant (in the case of iron oxides), and environmentally compatible [37], so that a composite, based on these materials, which incorporates heterojunction effects into a thin-film design would be a breakthrough towards application. Regarding pharmaceutical contaminants specifically, CIP, a fluoroquinoline antibiotic used in medicine and veterinary practice both, is of particular interest: it is one of the most widely used antibiotics worldwide and standard wastewater treatments are largely ineffective for its removal, leading to its frequent detection in surface waters in many regions. It is thus considered a potential source of antimicrobial resistance (AMR), an increasingly severe threat to public health [38]. Note that, while the final target of solar-wastewater treatments is generally the complete removal of pollutants via mineralisation, avoiding AMR in principle only requires the inactivation of antibiotic residues in water instead [39]. To this end, solar-driven photocatalysis would be a potentially cost-effective, high-efficiency treatment process. In this paper, we investigate the production of \(Z\)-scheme composite thin films based on the combination of pulsed laser deposition (PLD)-produced urchin-like iron oxide (FeOx) nanostructured film with g-C\({}_{3}\)N\({}_{4}\) to be employed for ciprofloxacin (CIP) degradation. The urchin-like FeOx was recently developed in our lab and has been selected as a platform for the composite synthesis because it has good solar spectrum compatibility, with an energy bandgap E\({}_{\text{g}}\) = 2.2 eV; consists of hierarchical structures, which are beneficial for applications requiring high surface area [40; 41]; and finally, it is photo-Fenton active [42; 43]. Two different strategies were used to prepare FeOx/g-C\({}_{3}\)N\({}_{4}\) composite films. In the first case, we grew the petal-like g-C\({}_{3}\)N\({}_{4}\) over iron urchins by directly drop-casting the melamine solution followed by thermal treatment (in situ). In the second case, previously synthesized g-C\({}_{3}\)N\({}_{4}\) powder was spin-coated over iron urchins (ex situ). The photocatalytic performance of the coatings has been evaluated via the degradation of ciprofloxacin (CIP) under visible light. CIP is indeed an important emerging contaminant, but at the same time it is well-studied, its degradation mechanism well reported, and it can easily be followed by simple UV-visible methods; therefore, it can be used to evaluate and tune the performances of our new materials [44; 45; 46; 47; 48; 49].
# High-Frequency Artifacts-Resistant Image Watermarking Applicable to Image Processing Models
## 3 Experimental Results and Analysis  
### Setup  
**Dataset.** To validate the effectiveness of our approach, we conducted evaluations on two distinct tasks: paint transfer [29] and de-raining [28]. To protect paint transfer model, we employed the Danbooru2019 dataset [27] and adopted the training methodology [29]. Following the training of our paint transfer model, we randomly sampled 4000 images (i.e., carrier images) generated by the network, with 3000 allocated for image watermarking training, 500 for validation, and 500 for testing. To protect de-raining model, we employed the dataset [28] and followed their training procedure. Following the training of our de-raining model, we randomly selected 2000 images (i.e., carrier images) generated by the network, with 1800 were allocated for image watermarking training, 100 for validation, and 100 for testing.  
**Parameter Setting.** All images were standardized to a size of \(256\times 256\times 3\). We respectively utilized \"Baboon\" and \"MDPI\" as watermark images, with a fixed watermark size of \(128\times 128\times 3\). Regarding adjustable parameters, we empirically set \(\alpha=5\times 10^{5}\), \(\beta_{1}=\beta_{3}=\beta_{4}=1\), \(\beta_{2}=5\). We used the Adam optimizer for training with a learning rate of \(2.0\times 10^{-4}\). Our method was implemented on a single TITAN RTX GPU with CuDNN acceleration.  
**Evaluation Metrics.** There are two commonly used metrics to assess the quality of marked images, Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM). Bit Error Rate (BER) is a measure of the quality of binary watermark reconstruction. In addition, to evaluate the performance of watermark extraction, we define a new metric called success rate (SR). Watermark extraction is considered successful if the corresponding PSNR is greater than 25 dB or the corresponding BER is less than \(1.0\times 10^{-2}\). Finally, the DCT detection results are utilized to measure the frequency-domain invisibility of the image watermarking system. We define the frequency domain invisibility performance (FP), which is expressed by calculating the Learned Perceptual Image Patch Similarity (LPIPS) [35] between the DCT detection result of the marked image and the DCT detection result of the ground-truth image, with the lower value of the metric being better.
###### Abstract  
This paper proposes a compact K-band dual-circularly polarized antenna that can be implemented on a non-linear tag based on third-order intermodulation (IM3) for bio-sensing applications. The proposed antenna has the characteristics of being low-profile and lightweight, with opposite circular polarizations (CP) between ports. The non-linear tag-based bio-sensing scenario utilizes K-band millimeter wave frequencies, which allows for compact non-linear tags for attachment to the body. Also, the proposed antenna features dual-CP, which are for the reception and re-radiation of incident transmit signals and the IM3 responses, respectively. To this end, a two-port traveling-wave series-fed patch array with coplanar proximity coupling is designed. Here, to minimize the size of the antenna, we use only four circular patch elements with a modified diamond-shaped microstrip feedline. Through simulation and measurement, we demonstrate that the proposed antenna has an axial ratio of less than 3 dB from 23.25 GHz to 24.1 GHz, with the reflection coefficients below \(-10\) dB and port-to-port coupling below \(-15\) dB. These results indicate the potential utility of the proposed antenna as a tag antenna for non-linear detection-based bio-sensing applications.  
t +
Footnote †: journal: Applied  
0000-0001-9313-3729
## 2 Materials and Methods
### Machine Learning Models  
Three powerful algorithms, Long Short-Term Memory (LSTM), XGBoost, and SVR, are provided for rigorous evaluation and to avoid potentially biased results.  
Figure 5: Outlier processing: (**a**) before processing and (**b**) after processing.  
LSTM, cut out for time-series problems, is famous for its cheap computational cost and high performance. Before [PERSON] et al. developed LSTM, recurrent backpropagation was haunted by the time-consuming issue when it tried to store information over extended time intervals, mainly due to insufficient decaying error backflow [27]. To eliminate this issue, LSTM, also known as the gradient-based method, truncated the gradient that will cause no harm and dedicated to linking up to 1000-time steps by making constant error flow to constant error carousels within special units. Multiplicative input and output gates were used to protect the constant error flow from irrelevant inputs and other units from unimportant memory contents [27].  
XGBoost has gained success and has been booming in some competitions, such as Kaggle 2015 and KDDCup 2015. At Kaggle, 17 out of 29 winning teams utilised XGBoost, while a great success could also be seen at KDDCup 2015, which the top 10 teams all employed XGBoost [28]. From [29], the researchers have proposed four crucial factors that make XGBoost great success: highly scalable, a theoretically justified weighted quantile sketch for efficient proposal calculation, a new sparsity-award algorithm for parallel tree learning, and an effective cache-aware block for out-of-core tree learning. These techniques enable XGBoost to run ten times faster than common models on an individual machine.
## 3 Conceptual Framework and System Overview  
### Theoretical and Developmental Basis of the User Experience Design  
#### 3.1.1 Developmental Challenges in Early Childhood Self-Regulation  
Understanding the developmental limitations that hinder early childhood self-regulation is essential for designing effective digital interventions. This section outlines the cognitive and emotional characteristics that hinder the ability of preschoolers to voluntarily disengage from screen use.  
Preschoolers struggle to develop digital self-regulation due to their ongoing cognitive and emotional development. A key factor is their immature executive function (EF) system [58]. EF comprises cognitive skills such as inhibitory control, attention shifting, and working memory--emerging abilities in early childhood that are essential for regulating digital behaviour [58]. Consequently, young children often struggle to disengage from highly stimulating content such as smart devices, even when they know they should.  
Another developmental limitation is episodic future thinking (EFT)--the ability to vividly imagine and plan future scenarios. Preschoolers often perceive future benefits less vividly than present pleasures [59], making it difficult to delay gratification [60]. For example, a child may understand that turning off the tablet could lead to a more rewarding activity later, but still lack the emotional drive to prioritise future gain over immediate enjoyment.  
Egocentric thought, described by [PERSON] [5], further complicates transitions away from screen use. Young children typically interpret the world from their own perspective and struggle to consider the viewpoints of others. This makes it hard for them to reconcile external requests--such as a parent saying 'it's time to stop'--with their own internal desires, often causing resistance or frustration.  
Additionally, the understanding of time in preschoolers remains underdeveloped; abstract units such as '10 min' or vague cues, including'soon', often hold little meaning for them. This creates a gap between verbal warnings and the ability to mentally prepare for screen transitions. Similarly, unstable object permanence and future continuity may lead children to believe that ending screen use means the experience is gone forever, increasing anxiety.  
These developmental traits must guide the design of interventions aimed at promoting voluntary, emotionally safe disengagement from digital content, in line with the self-regulated learning framework that emphasises metacognitive awareness, strategic action, and motivation [61].
## 1 Introduction
In the few cases, where uniaxial strain data were considered, the primary focus was on reconstructing simple membrane or bending deformations of the structure [27; 30]. Due to the high measurement density and operational convenience of a fiber optic system, there is enormous potential in using fiber optic strain measurements for the iFEM reconstruction. A possible application is for the SHM of plates or shells, where potential damage can cause local perturbations in the strain field. An accurate reconstruction of these 2D strain perturbations can provide useful information to identify the size, position, and orientation of the damage. However, in comparison with a strain rosette, strain measurements from a fiber optic sensor are uniaxial, i.e., only the component of strain along the local fiber direction is measured. iFEM reconstruction using only uniaxial strain data could lead to errors due to insufficient information regarding the strain field of a structure. This work addresses the problem of damage detection in a thin cracked plate under the action of in-plane loading. Strain reconstruction is performed using the iFEM methodology in the presence of the discrete uniaxial strain data resulting from several fiber-optic strain sensor patterns. The approach also examines the use of a one-dimensional smoothing algorithm for generating additional input strain data along the paths of the fiber optic sensors. The paper is organized as follows. In Section 2, an iFEM formulation for plate/shell structures is briefly described. In Section 3, the use of iFEM for strain field reconstruction using uniaxial strain data is demonstrated using an example problem of a biaxially loaded thin plate under various internal damage scenarios. The effect of position and orientation of uniaxial strain data are investigated, and the damage detection performance of the reconstructed strain field is also discussed. Finally, Section 4 presents the major conclusions and directions for future work.
# A Benchmark for Morphological Segmentation in Uyghur and Kazakh
###### Abstract
In the unsupervised model, character embedding, pre-trained using the word2 vec model, was fed into an encoder-decoder structure composed of an LSTM network with n-gram correlations and masked multi-head attention. This reduces the interference of characters outside the n-gram in determining morphological boundaries. Finally, the paper further comparatively analyzes the performance of recent stemming and morphological segmentation models on languages Uyghur and Kazakh from several different perspectives. The contributions of this paper can be summarized as follows:  
1. This paper redefines evaluation metrics in morphological segmentation and stemming tasks from a morphological perspective. Then, a comparison is made between recently proposed stemming and morphological segmentation models across various criteria, providing a comprehensive performance analysis. 2. For the second issue, this paper proposes two models employing different training approaches: supervised and unsupervised. Both models utilize character features, contextual features, and correlations between them to improve the model's generalization ability in complex scenarios (such as phonological harmony). 3. The two models proposed in this paper achieve SOTA results in morphological segmentation and stemming for Uyghur and Kazakh, updating the benchmark models and evaluation metrics.
## 2 Methodology
\right]^{T} \tag{9}\]  
Next, the extended Kalman filter (EKF) is used to estimate the parameters, and the corresponding state factor as:  
\[\mathbf{X}_{k+1}=\mathbf{\varphi}_{k+1,k}\mathbf{X}_{k}+\omega_{k+1},\ \ \ \ \ \omega_{k+1}\in N(0,\mathbf{Q}_{k+1}) \tag{10}\]  
where \(\mathbf{\varphi}_{k+1,k}\) is the transition matrix; \(\omega_{k+1}\) denotes state parameters' noise, and \(\mathbf{Q}_{k+1}\) is its covariance. The steps for performing Kalman filter are as follows:  
_Step 1_: Calculate the state vector \(\mathbf{X}_{k+1}\) and its covariance matrix \(\mathbf{P}_{k+1,k}\) according to Equation (10):  
\[\mathbf{X}_{k+1}=\mathbf{\varphi}_{k+1,k}\mathbf{X}_{k}+\omega_{k+1} \tag{11}\]  
\[\mathbf{P}_{k+1,k}=\mathbf{\varphi}_{k+1,k}\mathbf{P}_{k,k-1}\mathbf{\varphi}_{k+1,k}^{T}+\bm {Q}_{k+1} \tag{12}\]  
_Step 2_: the gain matrix \(\mathbf{K}_{k+1}\) given by:  
\[\mathbf{K}_{k+1}=\mathbf{P}_{k+1,k}\mathbf{H}_{k+1}^{T}(\mathbf{H}_{k+1}\mathbf{P}_{k+1,k}\mathbf{H}_{k +1}^{T}+\mathbf{R}_{k+1})^{-1} \tag{13}\]  
_Step 3_: Measurement update:  
\[\mathbf{X}_{k+2}=\mathbf{X}_{k+1}+\mathbf{K}_{k+1}(\mathbf{Z}_{k+1}-\mathbf{H}_{k+1}\mathbf{X}_{k+1}) \tag{14}\]  
\[\mathbf{P}_{k+2,k+1}=(\mathbf{I}-\mathbf{K}_{k+1}\mathbf{H}_{k+1})\mathbf{P}_{k+1,k} \tag{15}\]  
This paper uses a more robust formula to calculate \(\mathbf{P}_{k+2,k+1}\) than Equation (15) [19]:  
\[\mathbf{P}_{k+2,k+1}=(\mathbf{I}-\mathbf{K}_{k+1}\mathbf{H}_{k+1})\mathbf{P}_{k+1,k}(\mathbf{I}-\mathbf{K} _{k+1}\mathbf{H}_{k+1})^{T}+\mathbf{K}_{k+1}\mathbf{R}_{k+1}\mathbf{K}_{k+1}^{T} \tag{16}\]
# LCA as a Tool for the Environmental Management of Car Tire Manufacturing
## 2 Life Cycle of a Car Tires
### The Use Stage  
Each element of the tire can have a significant impact on fuel consumption and also on the reduction or increase of the negative environmental impact. On 1 November 2012, the obligation to label car tires was introduced in the European Union. The labels provide information on the most important aspects of tire performance, such as rolling resistance, wet grip, and noise emissions allowing for the quick and easy comparison of different products. They are designed to encourage manufacturers to act towards reducing rolling resistance, which leads to a reduction in carbon dioxide emissions to the atmosphere. Tires, mainly due to the rolling resistance, are responsible for 20-30% of the fuel consumption in passenger cars. Reducing fuel consumption allows for the reduction of the emission of CO\({}_{2}\) and other harmful compounds into the environment. The other parameters on the labels are intended to force tire manufacturers to care for all performance metrics equally. Labels are to encourage consumers to make more informed choices and mobilize manufacturers to create products of the highest quality [20].  
Tire wear contributes significantly to the flow of (micro) plastics into the environment. The particles generated during their use, emitted on the roads, can be dispersed in the environment through various routes. Smaller ones are usually emitted into the air, while large particles settle on the road surface and due to rainwater runoff, get into the soil, sewage, and surface waters. It is estimated that the relative share of tire wear in the total global amount of plastics ending up in our oceans is 5-10%. In the air, 3-7% of particulate matter (PM2.5) is made up of tire wear, indicating that it can contribute to the global health burden of air pollution, which can only be effectively addressed if awareness increases in this area [21].
# The Usage of Virtual and Augmented Reality in Underwater Archeology
## 5 Use of Augmented and Virtual Reality in Underwater Archeology--Example Solutions
### Vr Cave  
Work under the project titled \"A State-of-the-Art VR CAVE facility for the Advancement of Multi-Disciplinary Research & Development in Cyprus\" was carried out in 2012-2014 and financed by the Cyprus Foundation for the Promotion of Research using EU structural funds [113]. The project aimed to use VR in various aspects, including underwater archeology [113].  
In terms of underwater archaeology, the project focused on the Mazotos wreck, which dates back to the 4 th century BC [13]. Currently, the archaeological site is only an outline of the wreck and the amphore collected there. Data for the project were obtained on the basis of previously conducted archaeological works. The VR site itself was developed to make the interpretation and analysis of the wreck easier and more effective. The created application was intended to serve as a scientific tool for underwater archeology [113].  
The project's application was designed to provide an intuitive work environment for users and enable researchers to easily interact with archaeological data, which required a high level of accuracy and authenticity in the reflection of the wreck [13]. It was intended not only to enable the simultaneous and easy to manage viewing and comparison of the results of the documentation process of an underwater archaeological site, but also to introduce a virtual environment in which spatial analysis can be performed in three dimensions. Such a visualization allows one to see the relationship between artifacts and the surrounding environment and thus enable the exploration of alternative perspectives and interpretations [13]. An additional feature of the application was that it must also enable the addition of new information from future research work carried out at the site and the updating of existing data [13].  
The created VR CAVE station consisted of four projection screens (three projections on the walls and one on the floor), which allowed the use of stereo projection technology. Additionally, the tracking of the user's head movement was used to enable interaction with the virtual environment [13]. Stereoscopic glasses were used to ensure the proper perception of 3D images. An Xbox controller was used as an interaction device in the VR CAVE application, which allowed for great freedom in navigation control when using the application, including manipulating virtual objects [13]. The application interface consists of menus, icons and information panels through which the user can load various data and supporting materials into the virtual environment, e.g., photos corresponding to each artifact [13]. The application also has the potential to be used as an educational tool, in particular for training archeology students [13].