esa-sceva/satcom-chunk-collection huggingface dataset:
# Effects of Boundary Condition Models on the Seismic Responses of a Container Crane
## 1 Introduction
These behaviors were simulated by frictional contact elements programmed by OpenSees [7], in which the leg base works as pin support, until it uplifts when the coefficient of friction is sufficiently high. Based on the study of [PERSON] et al. [8], they proposed the friction coefficient of 0.75, in order to evaluate the seismic response of a modern jumbo container crane. In [PERSON] et al. 's experimental scale models, they also concentrated on treating the boundary condition, in which a friction-enhancing disk was placed between the bottom of the column and the top of the steel base plate on the shake table. The coefficient of friction between the disk and steel plate was in the range of 0.6 to 0.8. Another simpler link that uses an element was developed to model the dynamic impact of two nodes; this link is called an elastic-no-tension element. The element type allows only the generation of compressive forces, and movement in one direction. This element was proposed for a link between crane legs and rail by Liftech Consultants Inc. [9] to analyze the capacity of the non-uplifted side of the container crane. The report of [PERSON] et al. [10] on the seismic performance-based design method for container cranes also suggested the use of this element to simulate the link of crane legs and ground. This study investigated the effects of boundary condition models on the dynamic response of the container crane under seismic excitation by time history analysis. Nine horizontal response spectra of actual earthquakes are adjusted by scaling the amplitude of each response spectrum to a specific target response spectrum acceleration at the fundamental period of the container crane. Ten levels of target spectral acceleration are determined for evaluating the seismic response of the container crane. Some response characteristics, i.e., reaction of legs, portal drift, and movement of legs, are investigated by time history analysis. The different responses of the structure due to different types of boundary condition models are discussed as well.
# Vertical Force Monitoring of Racing Tires: A Novel Deep Neural Network-Based Estimation Method
## 4 Dataset Construction
### Data Collection and Labeling
#### 4.2.2 Preprocessing and Manual Labeling  
After the data collection phase and pre-labeling, the acquired signals were processed using a low-pass filter with a 350 Hz cut-off frequency, and normalization was applied to ensure consistency across all recorded signals. Subsequently, 30% of the data, corresponding to the first 18 s of each 60 s block for each state \((F_{i},P_{j},S_{k})\), was manually labeled as \((F_{i})\) to verify the accuracy of the pre-labeling and ensure the overall quality of the dataset. Each manually labeled data segment consisted of 251 data points. During the manual labeling, it was ensured that these segments matched the stable load, pressure, and speed values while filtering out any unhealthy or erroneous signals. As an example, a portion of the manually labeled acceleration data, corresponding to four rotations of the tire, is shown in Figure 7.  
Figure 6: Pre-labeled acceleration signal representing vertical acceleration over a 60 s period for a state \((F_{i},P_{j},S_{k})\) labeled as \((F_{i})\).  
This figure demonstrates how labeling was performed on four 251-point acceleration signal segments corresponding to a specific state with a force value \((F_{i})\).
# Fall Detection Based on Recurrent Neural Networks and Accelerometer Data from Smartphones
## 1 Introduction
### Aim  
In this study, we propose two deep learning models based on Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) for the task of fall detection. Unlike many existing studies that focus on general human activity recognition, our objective is to develop a solution explicitly dedicated to fall detection, which can be applied in real-world scenarios to protect elderly individuals and prevent health-related complications. The proposed models are evaluated on the UniMiB-SHAR dataset using the Leave-One-Subject-Out Cross-Validation (LOSO-CV) and \(k\)-Fold Cross-Validation (CV). The results demonstrate that our approach achieves the highest accuracy among the methods reported in the literature for this dataset under the LOSO-CV setting. Moreover, the proposed models exhibit low inference times, making them particularly suitable for deployment in real-time monitoring systems.  
The main contributions of this work are as follows:  
1. We introduce an RNN-based architecture specifically designed for fall detection, which achieves the highest accuracy than previously reported methods on the UniMiB-SHAR dataset, and publicly share all the data and code used in the experiments.
2. We demonstrate the effectiveness of the presented solution in terms of inference time, which is crucial for real-time applications.
3. We discuss potential future extensions, including the integration of multimodal sensor inputs and adaptation of the method to real-world deployment scenarios aimed at health monitoring and early intervention.  
By addressing the challenges of fall detection, our study contributes to the development of practical and deployable systems that can improve safety and quality of life, particularly for vulnerable populations. The proposed solution achieves the highest accuracy and the lowest inference time, making it suitable for real-time applications.
## 5 Applications of PCMs in Buildings
### PCM Passive Application Systems in Building
#### 5.1.1 PCMs in Wall  
The most general and effective solution for building energy saving is the incorporation of PCM into constructional materials that are applied either to the internal or the external surface of the walls. PCMs can be integrated into mortars, gypsum boards, concrete blocks, bricks, and panels.  
Mortars and plasters have been thoroughly investigated for PCM applications due to their use as coating materials for most of the building surfaces, along with their ability to have different compositions and their low cost. There are different kind of mortars, depended on the binder, such as gypsum, lime, and cement mortars [14]. The research that has been carried out about integration of PCMs in mortars and plasters is mostly about encapsulated PCMs, which involve high costs. As Cunha et al. [85] reported, nonencapsulated PCMs incorporated into mortar do not cause any significant enhancement to the mortar's properties. On the other hand, there are many studies showing that encapsulated PCMs into mortar and plaster have notable results for energy storage.  
Sandra Cunha et al. [86] investigated the effects on mechanical, physical, and thermal properties of four different innovative mortars, by the direct integration of pure PCM. The physical and mechanical properties were affected, for example water absorption was reduced and mechanical strength was significantly changed above 10% of PCM. Thermal behavior amplifies in proportion with PCM amount. A total of 20% of PCM showed very efficient thermal performance and mechanical properties suitable for interior mortar application. Cynthia Guardia et al. [87] incorporated an encapsulated PCM to cement-lime mortar and studied both its thermal and mechanical properties. The addition of 10% and 20% of the PCMs remarkably increased the thermal properties for energy storage, while decreased the mechanical properties within the permissible limits. Hamed Abbasi Hattan et al. [88] studied the integration of polyethylene glycol (PEG) shape-stabilized  
Figure 4: Charging process (working of PCM during daytime) and discharging process (working of PCM during nighttime).  
in silica fume PCM in cement mortar for plastering building external brick walls. The experiment included thermal performance tests on outdoor temperature walls in two different cities. The thermal performance of the mortar was high, and the demands could be fulfilled without incorporating an amount of PCM that could cause decrease in mechanical strength, density, and water absorption.
## 3 Results
### Metabolite Generation and Dissemination in Multiwell \(\mu\)Fluidic Culture System  
#### 3.6.1 Targeting APAP Metabolites  
Due to the extensive literature history on APAP metabolites [45; 46; 47], APAP was targeted onto HepaRG culture wells to evaluate metabolite generation across the \(\mu\)fluidic channel, i.e., occurrence trends. APAP was dispensed as a bolus dose (20 mM) into well 1, once daily, and downstream media were collected from each site to measure mutable concentrations of acetaminophen and generated APAP metabolites (Figure 8). LC/MS was used to quantify concentration intensities over a timeline 0\(\rightarrow\)72 h. \(\blacklozenge\)At 24 h (Figure 8(a1)), gradient concentrations of APAP range from 8.045\(\rightarrow\)0.088 mM (\(y\)-axis logarithmic scale) across the \(\mu\)fluidic wells 3-11 (\(x\)-axis). The metabolite APAP-glutathione (GSH) displays the lowest magnitude values, ranging 0.23\(\rightarrow\)0.0 uM (\(y\)-axis line graph) across the same \(\mu\)fluidic wells 3-11 (\(x\)-axis). Metabolite APAP-sulfate has elevated magnitude values ranging 13.26\(\rightarrow\)0.36 uM, while revealing activity in the last culture site, well 11. Metabolite APAP-glucuronide (APAP-Glu) has the highest magnitude values, ranging 67.7\(\rightarrow\)0.8 uM, while displaying a prominent decay curve in downstream wells 6-11. \(\blacklozenge\)h (Figure 8(a2)), gradient concentrations of APAP range from 17.048\(\rightarrow\)7.94 mM. The metabolite APAP-GSH  
\begin{table}
\begin{tabular}{c c c c} \hline
**Valid Obj Counts (Figure 7(a1,b1,c1))** & **Well 3** & **Well 7** & **Well 11** \\ \hline DMSO Vehicle Controls (Days 1, 3, 5) & (2.1\%, 11.4\%, 7.8\%) & (2.6\%, 13.0\%, 0.64\%) & (9.8\%, 7.2\%, 14.8\%) \\ \hline APAP (Days 1, 3, 5) & (2.8\%, 20.1\%, 12.8\%) & (8.6\%, 6.3\%, 12.8\%) & (1.9\%, 8.2\%, 5.8\%) \\ \hline NEF (Days 1, 3, 5) & (7.5\%, 23.1\%, 11.4\%) & (3.3\%, 5.8\%, 0.04\%) & (3.5\%, 5.6\%, 3.3\%) \\ \hline
**Tracing Fluid Flow Movements [23] (First Dose and Repeat Dosing)** & **Upstream (Wells 3–5)** & **Midstream (Wells 6–8)** & **Downstream (Wells 9–11)** \\ \hline \(\leq\)1 h after each dose into well 1 (acute hydrodynamic forces in action) & not appraised & not appraised & not appraised \\ \hline \(1\) h \(>\) dosing \(\leq\) 3.3 h (transitional forces creating stability) & 5–8\% & 5–6\% & 4–6\% \\ \hline \(>\)3.3 h till re-dosing (sustained equilibrium forces) & 4–5\% & 4–5\% & 4–5\% \\ \hline \end{tabular}
\end{table}
Table 2: Coefficient of Variation for Intra-Plate Robustness.  
retains comparable 24 h displays ranging 0.21\(\rightarrow\)0.0 uM. Both APAP-Sulfate 6.98\(\rightarrow\)20.7 uM and APAP-Glu 39.9\(\rightarrow\)103.3 uM exhibit increased levels across downstream wells 4-11, an indication of ongoing generation of metabolites. Contrastingly, well 1 reveals lower magnitudes (~0.5-fold) with the recognition that well 1 encounters highest APAP exposures. Of note, for trending appraisals, data in well 9 show a reduction in concentrations for APAP-sulfate and APAP-Glu, being possible data outliers or potential special cell-function outcomes.
# Microgravity, Bone Homeostasis, and Insulin-Like Growth Factor-1
## 7 IGF-1 and Bone Homeostasis  
IGF-1 is the most abundant growth factor in bone matrix [42] where it is synthesized by osteoblast mesenchymal precursors, mature osteoblasts, osteoclasts and osteocytes [44; 45]. Osteoblasts also produce all the IGFBPs [45]. Hepatocyte synthesized IGF-1 is distributed to the matrix via the bone's nutrient and periosteal arteries located within the Volkmann and Haversian canals.  
In bone, IGF-1 regulates periosteal bone expansion (radial bone growth) by its effects on osteoporosis at the periosteal or endocortical bone surfaces. Linear bone growth is controlled by growth hormone which stimulates chondrocyte precursors to produce IGF-1 which then acts in an autocrine fashion to induce the production of type II collagen1a via activation of the phosphatidylinositol 3-kinase/phosphoinositide-dependent kinase-1 pathway. With progression of chondrocytes to terminal differentiation, IGF1R signaling is terminated [46]. IGF-1 regulates bone mass by activation of mTOR in mesenchymal stem cell progenitors of osteoblasts [47].  
IGF-1 has pro-differentiating and pro-survival effects on osteoblasts and their mesenchymal precursors and is essential for the anabolic actions of parathyroid hormone (PTH) on bone [48]. Activation osteoblast IGF1R initiates the expression of the run-related transcription factor 2 (Rumx2) which stimulates the transition of mesenchymal stem cells into osteoporosis. Downstream of Runx2 is asterix (osx) which controls the maturation of osteoporosis into mature osteoblasts. Osteoblasts are responsible for the production and secretion of the extracellular matrix and expresses genes involved in matrix calcification [45].  
Osteoclasts differentiate from mononuclear progenitors in the presence of macrophage colony stimulating factor (M-CSF) and RANKL. [PERSON] and associates found that mRNA expression of RANKL, RANK, and M-CSF was diminished by 35-60% in IGF-1 knockout mice and led to a reduction in osteoclastogenesis [49]; the results confirm the importance of IGF-1 in promoting osteoclast differentiation from hematologic stem cell precursors.  
Both animal and human studies have shown that circulating levels and locally produced autocrine/paracrine sources of IGF-1 each play an important role in achieving peak bone mass and strength [7; 44].
## 4 An Indoor Positioning Algorithm Combining IMU and LBP-FFT-CNNs
### Inertial-Based Positioning Algorithm Using IMU
#### 4.1.6 EKF Derivation and Parameter Settings  
The EKF is applied in this work to fuse inertial and visual positioning data. The algorithm follows the standard predict-update structure based on a nonlinear system model.  
The state vector is expressed as follows:  
\[X_{t}=[P_{t},\ V_{t},\theta_{t}]^{T} \tag{24}\]  
where \(P_{t}\) is position, \(V_{t}\)  
obstacles \(O_{1}\), \(O_{2}\), and \(O_{3}\) were designed with varying material properties to evaluate the system's robustness against differences in laser beam reflections.
# Multi-Stage Prompt Tuning for Political Perspective Detection in Low-Resource Settings
## 4 Experimental Setup
### Evaluation Results  
Table 2 shows the performance of our model and the baselines in full data settings. We run five random restarts and report the median accuracy (Acc) and macro-F1 (MaF) scores. As shown in Table 2, MP-tuning outperforms the baselines in terms of the accuracy and macro-F1 score for both datasets. Specifically, MP-tuning achieves 8.0% and 7.0% increases in terms of accuracy and macro-F1, respectively, compared to MAN, the best-performing fine-tuning method on the SemEval dataset. We observe that MP-tuning outperforms MAN in the AllSides dataset as well. Furthermore, MP-tuning outperforms the state-of-the-art prompting method P-tuning v2 in terms of accuracy and macro-F1 score by 1.6% and 2.1%, respectively, on the SemEval dataset and by 2.5% and 4.1%, respectively, on the AllSides dataset.  
We also investigate the effects of MP-tuning in low-resource settings. We compare MP-tuning with fine-tuning (i.e., original RoBERTa) and the original P-tuning v2. We conduct experiments several times using random sampling on the AllSides and SemEval datasets and report the median F1 score. We systematically evaluate the effect of the number of examples on our models' performance for both datasets, from using 32 examples for training to using 512 examples. As shown in Figure 3, MP-tuning outperforms fine-tuning and P-tuning v2 for each setting. In particular, MP-tuning shows a significant performance improvement compared with fine-tuning, even in significantly low-resource settings (32, 64, 128), whereas P-tuning v2 shows lower performance than fine-tuning. These results demonstrate that our domain-specific prompt tuning on MP3 task alleviates the distribution shift problem of prompt tuning by learning political domain knowledge and adapting a frozen language model. In particular, the outstanding performance of MP-tuning in low-resource settings is advantageous in real-world applications where it is difficult to obtain training data for political perspective detection in news media.  
\begin{table}
\begin{tabular}{l l c c c c} \hline \multirow{2}{*}{**Setting**} & \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{**SemEval**} & \multicolumn{2}{c}{**AllSides**} \\ \cline{3-6}  & & **Acc** & **MaF** & **Acc** & **MaF** \\ \hline \multirow{3}{*}{Fine-tuning} & BERT \(*\) & 86.92 & 80.71 & 80.80 & 79.71 \\  & RoBERTa \(*\) & 87.08 & 81.34 & 81.80 & 80.51 \\  & MAN \(\dagger\) & 84.66 & 83.09 & 81.41 & 80.44 \\ \hline \multirow{3}{*}{Prompting} & [PERSON]’s prompt tuning \(*\) & 82.72 & 81.35 & 76.42 & 74.38 \\  & P-tuning v2 \(*\) & 90.06 & 87.12 & 81.18 & 79.27 \\  & MP-tuning (Ours) & **91.47** & **88.92** & **83.21** & **82.54** \\ \hline \end{tabular}
\end{table}
Table 2: Political perspective detection performance on the SemEval and AllSides dataset. The results marked with \(*\) are from our implementations, whereas results marked with \(\dagger\) are reported in each reference.
###### Abstract  
This research proposes a compact indirect slot-fed wideband patch array antenna for a missile seeker application. The proposed single antenna consists of three dielectric layers for a radiator, an air substrate-integrated waveguide (SIW) cavity, and an indirect feeding network. The rectangular patch is used as a radiator on the first substrate layer, and the air SIW cavity (ASIWC) is employed to obtain high directivity and low mutual coupling characteristics in the second substrate layer. In the third layer, an indirect feeding structure is used to achieve the wideband characteristics in the Ka-band. The single element is extended to a \(4\times 1\) linear array with fabrication, and the fabricated array characteristics are measured in a full anechoic chamber. The measured operating fractional frequency bandwidth is 9.2%, and the measured array gain is 11.7 dBi at the bore-sight direction (\(\theta_{0}=0^{\circ}\)).  
cavity-backed antenna; missile seeker; Ka-band; phased array +
Footnote †: journal: Applied  
composed of three dielectric layers for a radiator, an air SIW cavity (ASIWC), and an indirect feeding network. The rectangular patch radiator is printed on a dielectric substrate, and it is co-operated with the ASIWC to achieve a high-directive pattern and a narrow half-power beamwidth (HPBW). An indirect feeding structure is used to obtain the wideband impedance-matching characteristics in the Ka-band. The parametric studies of the proposed single element are conducted, and the essential design parameters of it are then optimized using the HFSS full electromagnetic (EM) simulation software tool [23]. In addition, the mutual coupling characteristics can be enhanced by using the ASIWC when observing the nearfield distributions of a 2 \(\times\) 1 array antenna. Based on the results, the single element is extended to a 4 \(\times\) 1 linear array antenna. To verify the antenna performances, the proposed array is fabricated, and its antenna characteristics, such as the reflection coefficients, radiation patterns, and bore-sight gains, are measured in a full anechoic chamber. The result that the proposed array antenna has a high directivity and low mutual couplings is suitable for applying to the missile seeker applications.
_applied_  
_sciences_  
_Article_  
**Improving Prediction of the Potential Distribution Induced by Cylindrical Electrodes within a Homogeneous Rectangular Grid during Irreversible Electroporation**  
**[PERSON] 1,2**\({}^{\text{(}}\)\({}^{\text{(}}\)\), [PERSON] 3, [PERSON] 2, [PERSON] 2, [PERSON] 1,1**\({}^{\text{(}}\)\({}^{\text{(}}\)\)  
**and [PERSON] 1,**\({}^{\text{(}}\)\),**\({}^{\text{(}}\)\)**  
**These authors contributed equally to this work.**  
**Featured Application: The Electric-Potential Estimation (EPE) method provides the possibility to considerably shorten the simulation time of treatment planning within a uniformly distributed rectangular grid by using large voxel-sized models without largely affecting the accuracy of the electric-field distribution. Thus, real-time clinical IRE treatment planning in realistic heterogeneous target volumes becomes feasible.**  
**Abstract: Background: Irreversible electroporation (IRE) is an ablation technique based on the application of short, high-voltage pulses between needle electrodes (diameter: -1.0 \(\times\) 10\({}^{-3}\) m). A Finite Difference-based software simulating IRE treatment generally uses rectangular grids, yielding discretization issues when modeling cylindrical electrodes and potentially affecting the validity of treatment planning simulations. Aim: Develop an Electric-Potential Estimation (EPE) method for accurate prediction of the electric-potential distribution in the vicinity of cylindrical electrodes. Methods: The electric-potential values in the voxels neighboring the cylindrical electrode voxels were corrected based on analytical solutions derived for coaxial/cylindrical electrodes. Simulations at varying grid resolutions were validated using analytical models. Low-resolution heterogeneous simulations at 2.0 \(\times\) 10\({}^{-3}\) m excluding/including EPE were compared with high-resolution results at 0.25 \(\times\) 10\({}^{-3}\) m. Results: EPE significantly reduced maximal errors compared to analytical results for the electric-potential distributions (26.6-71.8%-0.4%) and for the electrical resistance (30%-1-6%) at 3.0 \(\times\) 10\({}^{-3}\) m voxel-size. EPE significantly improved the mean-deviation (43.1-52.8%-13.0-24.3%) and the calculation-time gain (>15,000\(\times\)) of low-resolution compared to high-resolution heterogeneous simulations. Conclusions: EPE can accurately predict the potential distribution of neighboring cylindrical electrodes, regardless of size, position, and orientation in a rectangular grid. The simulation time of treatment planning can therefore be shortened by using large voxel-sized models without affecting accuracy of the electric-field distribution, enabling real-time clinical IRE treatment planning.**  
**Keywords: irreversible electroporation; computational electroporation; numerical treatment planning; thermal ablation**