esa-sceva/satcom-chunk-collection huggingface dataset:
# Nonlinear Trajectory Tracking Controller for Underwater Vehicles with Shifted Center of Mass Model
## 4 Numerical Simulations
### Results Using Indexes  
The tests performed were confirmed by the results collected in Table 2.  
Figure 7: QV controller results, stronger couplings, complex trajectory, and (27): (**a**) trajectories: \(p_{d}\)—desired, \(p\)—actual; (**b**) linear errors of position; (**c**) angular errors of position; (**d**) linear velocities; (**e**) angular velocities; (**f**) force and torque applied; (**g**) kinetic energy values; (**h**) errors of \(\Delta\zeta_{1},\Delta\zeta_{2},\Delta\zeta_{3}\). For a linear trajectory, it is enough to compare the values of the corresponding MIAE, mean, std, and RMS. On the other hand, the values of the applied forces and torques and the kinetic energy are comparable, which indicates that the controller effort for both algorithms (QV and CL) is also comparable. If either a linear or complex (1) trajectory is tracked, smaller tracking errors \(y_{e}\), \(z_{e}\) were obtained for the QV controller (than for CL), and therefore, in those directions for which there is no control signal. On the other hand, when there are control inputs, lower error values (\(x_{e}\), \(\theta_{e}\), \(\psi_{e}\)) were obtained for the CL algorithm. The total RMS value of linear errors is lower for the QV controller, while the RMS for angular errors is lower for the CL controller. However, by comparing the time histories of these quantities (shown previously), it can be seen that the CL scheme is less effective than the QV. For the complex trajectory in case (1), as shown in Table 2, the linear position errors (according to MIAE) are also smaller for the QV controller compared to CL, although the angular errors have slightly larger values (but not significantly). The mean values and standard deviations do not support this for \(x_{e}\), but overall, the RMS confirms the higher tracking accuracy of linear variables for the QV controller. The kinetic energy consumption is slightly lower for it. There is also little difference in the average values of force and torques (MIAC index). For the complex trajectory (2), performance improvements were obtained for the QV controller. Some values of the MIAE, mean, std, MIAC, and RMS indexes were reduced. The movement took place with less control input and the kinetic energy consumption was slightly lower (it is worth noting that these increased the gains responsible for reducing the effects of inaccurately known model parameters, as for the CL controller). The omission of indexes for the CL controller in the case of the complex trajectory was due to the fact that previously worse results than those for the QV control scheme related to tracking accuracy were obtained. It is also worth noting that although some index values are smaller for the CL controller, this does not mean that it performs better than the QV-based controller. For linear position errors, the performance of the QV controller is definitely better. On the other hand, for an
###### Abstract  
Assessment of the placental cord insertion (PCI) is a vital component of antenatal ultrasound examinations. PCI can be complex, particularly in cases of abnormal PCI, and requires proficient sonographer spatial perception. The current literature describes the increasing potential of three-dimensional (3D) modelling to enhance spatial awareness and understanding of complex anatomical structures. This study aimed to evaluate sonographers' confidence in ultrasound assessment of the PCI and the potential benefit of novel 3D-printed models (3 DPMs) of the PCI in ultrasound education. Sonographers employed at a large private medical imaging practice in Western Australia were invited to participate in a face-to-face presentation of two-dimensional (2D) ultrasound images, ultrasound videos, and 3 DPMs of normal cord insertion (NCI), marginal cord insertion (MCI), and velamentous cord insertion (VCI). Our objective was to determine the benefit of 3 DPMs in improving sonographers' confidence and ability to spatially visualise the PCI. Thirty-three participants completed questionnaires designed to compare their confidence in assessing the PCI and their ability to spatially visualise the anatomical relationship between the placenta and PCI, before and after the presentation. There was a significant association between a participant's year of experience and their confidence levels and spatial awareness of the PCI prior to the demonstration. The results showed the 3 DPMs increased participant confidence and their spatial awareness of the PCI, with no significant association with years of experience. Additionally, participating sonographers were asked to rate the 3 DPMs as an educational device. The 3 DPMs were ranked as being a more useful educational tool for spatially visualising the NCI, MCI, and VCI than 2D ultrasound images and videos. Most participants responded favourably when asked whether the 3 DPMs would be useful in ultrasound education, with 75.8%, 84.8%, and 97% indicating the models of NCI, MCI, and VCI, respectively, would be extremely useful. Our study has demonstrated a potential role for 3 DPMs of the PCI in ultrasound education, supplementing traditional 2D educational resources.  
placental cord insertion; 3D-printed model; 3D printing; 3D obstetric ultrasound; sonographer; education; ultrasound
# SemABC: Semantic-Guided Adaptive Bias Calibration for Generative Zero-Shot Point Cloud Segmentation
## 4 Experiments
### Ablation Studies  
#### 4.4.1 Module Effectiveness  
Table 2 evaluates the effectiveness of the proposed visual-semantic fusion branch and the adaptive bias calibration module, especially their collaborative mechanism. The first baseline, denoted as _Fixed Calibration_, directly adopts the prediction results of the existing generative segmentation network SV-Seg [19]. Note that here, deviation calibration is performed by subtracting the fixed calibration value. The second experiment, i.e., _w/o BCM_, employs our dual-branch network architecture to calibrate bias by averaging the predictions of the two branches, rather than using our adaptive calibration module. The third experiment, i.e., _w/o VSFM_, removes the core fusion module of the visual-semantic branch, directly calculates the similarity matrix between visual and semantic features as the output segmentation probability of this branch, and then applies our adaptive bias calibration scheme.  
The experimental results reveal that the most significant improvement in the performance occurs when the VSFM and BCM modules work together, resulting in an increase of 0.8% in HmIoU. The absence of the VSFM module (_w/o VSFM_) leads to a more noticeable decline in the performance of seen classes, whereas the lack of BCM (_w/o BCM_) causes a more substantial decrease in the performance of unseen classes. These results suggest that the two proposed modules establish a bidirectional compensatory system with complementary characteristics: on one hand, the VSFM module employs the channel and spatial attention mechanism to facilitate dynamic interaction and fusion between visual-semantic features, effectively enhancing the spatial separability of visual features for both seen and unseen classes. On the other hand, the BCM module implements a confidence-based weight adjustment strategy that dynamically regulates the contribution of auxiliary predictions while adaptively incorporating these results into the predictions of the main branch.
# Optimization of Protection Level of GBAS with Gaussian Mixture Model
## 6 Conclusions  
In order to balance the minimization of the GBAS protection level and the ease of operation of airborne equipment, a multi-hypothesis protection level optimization algorithm under the GMM distribution is proposed. Actual airport data verified that the GBAS ranging error obeys the GMM model, and the simulation results of multiple scenarios showed that the proposed method basically eliminates the loss of protection level in the Gaussian over-bounding method. It should be pointed out that satellite navigation errors generally obey the heavy-tailed distribution, so the new method proposed in this paper is also applicable to other integrity engineering techniques such as SBAS and ARAIM.  
Although the protection level of the new method is significantly lower than that of the existing Gaussian over-bounding method, the protection level can be further reduced. Since the B value, which reflects the current GBAS ranging error, can be calculated in real time and a priori GMM distribution of the ranging error is known, a posteriori distribution of the ranging error, which is a more precise error model and results in a lower protection level, can be obtained by a Bayesian approach or an expectation-maximum algorithm.  
Conceptualization, [PERSON]; methodology, J.Z.; validation, S.H. ([PERSON]); formal analysis, J.Z.; investigation, J.Z.; data curation, S.H. ([PERSON]); writing--original draft preparation, J.Z.; writing--review and editing, S.H. ([PERSON]); supervision, B.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the State Key Laboratory of Satellite Navigation System and Equipment Technology, grant number 22684X023.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to industrial reservations.  
Figure 11: Latitude correlation chart of global CAT II/IIIIa GBAS vertical protection level reduction under 99% availability of this method with traverse depth of 6 compared with Gaussian over-bounding method.
## 4 KGs Evaluation
### Extrinsic Evaluation
#### 4.2.2 Extrinsic Evaluation Across Diverse Knowledge Graph Applications  
In the field of public transportation, a quantitative analysis was conducted comparing a CSV-based mapping tool with Morph-KGC and SPARQL Anything, using GTFS public transportation data to determine whether the same results were generated [166]. Another study constructed an application pipeline that evaluated various link prediction techniques under the same conditions to analyze their impact on a real-world knowledge graph evaluation workflow [167]. In the question-answering task, the integration of large-scale language models with knowledge graphs was shown to improve Mean Average Precision and Mean Reciprocal Rank using both Chinese and English QA datasets (NLPCC2017, cMedQA, TREC-QA, and WikiQA) [181].  
In the medical application field, the use of the MIMIC-III and MIMIC-IV datasets demonstrated that a patient similarity search model achieved high accuracy and F1-score [171], while in multilingual entity alignment, performance improvements across languages were quantitatively verified using the DBP15K dataset [173]. In the legal domain, a judgment prediction model based on the ECHR and CAIL2018 datasets achieved superior Accuracy and Area Under the Curve for Receiver Operating Characteristic (AUC-ROC) compared to conventional legal AI models [177]. In the biomedical field, studies using the KEGG50k, Hetionet, SuppKG, and ADInt datasets have demonstrated improved link prediction performance [178]. In agricultural applications, research based on Bangladesh agricultural data (BBS) reported that after KG generation, OLAP queries and business intelligence analyses experienced significantly reduced query response times [179], and in railway defect detection, evaluations using the NEU RSDDS-AUG dataset quantitatively verified the benefits of external applications [180]. Additionally, evaluations through RDF triple store benchmarks [182] and open-world KG completion assessment via extended pretrained language models [134], as well as multilingual KG alignment performance evaluation [183] and studies that quantitatively analyzed the effects of relation-based graph attention and mutual information maximization techniques [184; 185; 186] are presented as extensive applications of extrinsic evaluation.  
Other applications, such as software bug triaging, clinical decision support, mobile app recommendation, literature-based research hypothesis generation, cybersecurity, federatedlearning in healthcare, link prediction under few-shot conditions, and storage space savings through normalization techniques, have also been evaluated.
## 2 Methods
### Linear Convolution Decoder Module  
As shown in Figure 3, this paper employs a multi-stage decoder corresponding to the encoder, enabling comprehensive multi-scale image understanding and enhancing the model's ability to distinguish between background and road pixels. The gradual restoration of spatial information minimizes loss of positional and spatial details during upsampling, improving reconstruction accuracy and detail retention. This multi-stage approach also effectively reduces checkerboard artifacts, which can otherwise impair model performance, and enhances output quality through layered processing. Additionally, the decoder retains edge information and fine details during feature fusion, improving edge detection accuracy. The encoder-decoder structure, augmented with skip-connections, preserves the spatial structure and contextual information of the original feature maps, ensuring robust and detailed reconstructions.  
The ground-truth in road datasets reveals the continuous distribution and broad spans of roads in images, typically exhibiting linear characteristics and shapes like 'Y', 'T', and '+' [4]. CCNet [27] utilizes criss-cross attention to model horizontal and vertical context, balancing computational efficiency with contextual integration. To more effectively capture these linear road features, the decoder incorporates a specialized module using parallel linear convolutions. This module applies parallel linear convolutions in four directions: horizontal, vertical, left diagonal, and right diagonal. The features from these convolutions are then fused and output after adjusting channel dimensions. Horizontal convolutions use \(1\times n\) kernels, vertical convolutions use \(n\times 1\) kernels, and diagonal convolutions apply weights only along the diagonal of an \(n\times n\) kernel. The first two configurations expand the receptive field to better match road shapes while maintaining parameter efficiency. Diagonal convolutions further reduce the parameter count while effectively capturing road features.
# The Vibration Response Characteristics of Neighboring Tunnels Induced by Shield Construction
## 5 Discussion
### Significance of Vibration Control and Mitigation  
This research offers valuable insights and guidance for vibration control in shield tunneling construction. The spatial limitations of vibration impact highlight the need to prioritize monitoring and mitigation measures within 5 m of the vibration source, with special attention given to critical structures near the source. Furthermore, since vibration energy is predominantly concentrated in the low-frequency range of 3-5 Hz, implementing vibration filtering for this frequency range is crucial to effectively reduce its impact on the surrounding environment.  
The observed directional differences in vibration responses provide important clues for optimizing vibration control strategies. In the construction-side tunnel, where axial vibration predominates, adjusting shield machine parameters--such as thrust uniformity and cutterhead design--can help reduce axial vibration intensity. For adjacent tunnels, focusing on radial vibration mitigation through stronger segment reinforcement or the use of high-damping materials can enhance vibration absorption and dissipation.  
Additionally, numerical simulation validation strengthens the reliability of the theoretical model, facilitating the development of more accurate vibration control plans. Identifying localized energy dissipation anomalies through simulations enables targeted mitigation measures in critical areas, thus improving vibration control efficiency. Optimizing construction parameters--such as advancing speed, cutterhead rotation, and excavation pressure--based on simulation results can further minimize the vibration impact on surrounding structures.  
These findings contribute to a deeper understanding of vibration characteristics during shield tunneling construction, providing theoretical support for the development of more effective vibration control strategies.
###### Abstract  
This paper reports on a pulsed coding technique based on optical Ultra-wideband (UWB) modulation for wireless implantable biotelemetry systems allowing for high data rate link whilst enabling significant power reduction compared to the state-of-the-art. This optical data coding approach is suitable for emerging biomedical applications like transcutaneous neural wireless communication systems. The overall architecture implementing this optical modulation technique employs sub-nanosecond pulsed laser as the data transmitter and small sensitive area photodiode as the data receiver. Moreover, it includes coding and decoding digital systems, biasing and driving analogue circuits for laser pulse generation and photodiode signal conditioning. The complete system has been implemented on Field-Programmable Gate Array (FPGA) and prototype Printed Circuit Board (PCB) with discrete off-the-shelf components. By inserting a diffuser between the transmitter and the receiver to emulate skin/tissue, the system is capable to achieve a 128 Mbps data rate with a bit error rate less than \(10^{-9}\) and an estimated total power consumption of about 5 mW corresponding to a power efficiency of 35.9 pJ/bit. These results could allow, for example, the transmission of an 800-channel neural recording interface sampled at 16 kHz with 10-bit resolution.  
high data rate low power link; optical ultra-wideband modulation; pulsed coding technique; wireless implantable biotelemetry
# Adoption of Multiphase and Variable Flux Motors in Automotive Applications
## 2 Literature Review
### Variable Flux Motors  
To have a wider torque-speed envelope and more efficient high-speed performance, VF motors have been suggested in the literature in the last few years. The objective with these motors is to somehow vary the permanent magnet flux linkage to operate with different flux levels at different regions, thus obtaining good performance at low speed as well as high speed, as illustrated in Figure 1, where the circles inside the envelopes represent the highest-efficiency regions.  
Several publications review the different ways to achieve a variable flux [46; 47; 48; 49]. They agree that there are three main ways to obtain a variable flux field. Using hybrid excitation (HE) motors is the most known one, where the field windings allows to adjust the flux linkage. Another way to vary the flux linkage is by demagnetising and magnetising low coercive field magnets. Last, flux can be mechanically varied in different ways. Next, the three motor types will be reviewed.
## 3 Results
### Myogenic Protein Expression of Directly Reprogrammed Myogenic Cells by RV/bMyoD  
To further observe the efficiency of direct conversion using RV/_bMyoD_, the expression of representative myogenic proteins [53; 54; 55] was analyzed through immunocytochemistry (Figure 5). According to the results, RV/_bMyoD_-treated BDFs showed obviously increased expression of myogenic proteins, represented as MyoD, MyoG, and Desmin, compared with the control (Figure 5A,C,E). In addition, the morphology of the fluorescent cells was different from the original BDFs. Cells showed protrusions, connecting to neighboring cells, shown in Figure 5A. In Figure 5C,E, cells with green fluorescence were observed in the form of fused cells, which indicates myogenic morphology. Specifically, in Figure 5C, myotubes are observed clearly. The intensity of each fluorescence was quantified using ImageJ (Figure 5B,D,F). Directly reprogrammed myogenic cells with RV/_bMyoD_ showed a statistically significant increase in the expression of all the proteins. The early myoblast marker proteins, such as MyoD and MyoG, showed 60-fold and 12.5-fold increases compared to each control, respectively (Figure 5B,D). Similarly, the late myotube marker protein, Desmin, showed a 35-fold increase compared to the control. As a result, RV/_bMyoD_ treatment induced improvement in expression of early myoblast proteins and also, late myotube proteins, resulting in direct conversion of BDFs to myogenic cells.  
Figure 5: Observation of myogenic protein expression in directly reprogrammed myogenic cells. (**A**) Immunocytochemical analysis to confirm the expression of MyoD (red fluorescence). (**B**) Quantified value of MyoD protein expression. (**C**) Immunocytochemical analysis to confirm the expression of MyoG (green fluorescence). (**D**) Quantification of MyoG expression. (**E**) Immunocytochemistry to confirm the expression of Desmin (green fluorescence). (**F**) Quantification of Desmin expression. \(n=3\) per group. Statistical significance was determined using one-way ANOVA in comparison with the control. *** \(p<0.001\). Scale bars, \(100\) μm.
## 4 Discussion
### The Performance of Decision Tree Techniques in Characterizing Nitrogen-Saturated Grassland Plots  
The RF classification algorithm (overall accuracy of 91%) noticeably outperformed the CART analysis (overall accuracy of 79%) in characterizing nitrogen-saturated plots. These observations are in agreement with findings by [PERSON] et al. [91], [PERSON] et al. [92] and [PERSON] et al. [93] who report that because CART methods are stand-alone decision trees, they are often prone to a high variance caused by a heavy dependence upon the training data. The RF model circumvents this through a form of regularization provided via a multitude of decision trees [77; 92]. The resultant lower variance facilitated an increase in discriminatory power and accuracy [94]. However, although decision tree model accuracy can be improved through increased iteration, the resultant model can easily overfit the data if cross validation is not applied [95]. [PERSON] et al. [94] arrived at a similar conclusion during their study of improving landcover mapping using Landsat TM imagery in China. They found that in addition to their RF model (91.3%) outperforming their CART model (89.2%), the RF model was also more resilient to a reduction in training data and amplified noise [94].  
This study has shown that nitrogen-saturated grassland plots can be successfully identified using Worldview-3 imagery and the RF classification algorithm. This provides a platform to assist rangeland managers in identifying grasslands within the initial stages of nitrogen saturation and facilitate the rehabilitation and management of both degraded and pristine South African grasslands.