esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In this paper, we report the crystallization and the influence of laser surface modification on the crystalline phases and optical response of Al\({}_{2}\)O\({}_{3}\)/glass-ceramic coatings. The ZrO\({}_{2}\)-SiO\({}_{2}\) glass ceramic on alumina coatings prepared using the sol-gel technique, deposited under the experimental conditions used in this study, can be used for applications where a more stable alpha-alumina structure is required. This is due to the zirconia incorporated in the system maintaining its tetragonal phase at room temperature. This stable tetragonal ZrO\({}_{2}\) phase at room temperature was obtained using annealing in an oven at 850 \({}^{\circ}\)C in the Al\({}_{2}\)O\({}_{3}\)/SiO\({}_{2}\)-ZrO\({}_{2}\) composite coating.  
Additionally, the results show that the use of CO\({}_{2}\) laser annealing allows the identification of the spectroscopic properties of the studied system. In this sense, different power densities of 0.69 W/cm\({}^{2}\), 1.04 W/cm\({}^{2}\) and 1.38 W/cm\({}^{2}\) were used to identify these properties. The annealing for 1 min allows the photoluminescence of the glass-ceramic system with optical emission to exhibit an intense double peak at 693 nm (1.789 eV) and 694 nm (1.786 eV) and weaker emission at lower energies. According to the surface micrographs and EDS analysis, the optical response is probably due to Al\({}_{2}\)O\({}_{3}\), with a weak contribution of the ZrO\({}_{2}\)-SiO\({}_{2}\) glass ceramic at lower energies. Although the study had a very important focus on the phase transformation of alumina associated with heat treatment in furnaces and lasers, it can be shown that the entire studied system has a good response to CO\({}_{2}\) laser annealing, since emission is well defined; thus, it could be of interest for various optical applications.  
Figure 9: Photoluminescence spectra of SiO\({}_{2}\)-ZrO\({}_{2}\) with CO\({}_{2}\) laser post-annealing for 1 min, using a power density of (**a**) 0.69 W/cm\({}^{2}\); (**b**) 1.04 W/cm\({}^{2}\) and (**c**) 1.38 W/cm\({}^{2}\).  
**Author Contributions:** Conceptualization, C.G.; methodology, J.C., J.M., J.J. and L.G.; investigation J.C.; formal analysis, L.T., H.C., J.E.D.; validation, A.C.; supervision, C.G.; resources, C.G., L.T., H.C., J.E.D. and A.C.; data curation, C.G.; writing--original draft preparation, C.G., L.T. and A.C.; writing--review and editing, C.G.; visualization, L.T. and A.C.; supervision, C.G.; project administration, C.G.; funding acquisition, C.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors are grateful to the IIC radiometry laboratory of Universidad del Quindio and the Universidad Autonoma de Occidente for funding (Project code No. 17 INTER-289).  
The authors declare no conflict of interest.
# Study of High-Frequency Pulsating Flow Control Valves
## 5 Conclusions  
In this paper, a HPFCV is proposed for dynamic flow measurement problems. After introducing the working principle of the high-frequency flow control valve, a block diagram of the HPFCV is established. Subsequently, the performance of the valve is experimentally investigated by building a principle prototype of the high-frequency flow control valve and a performance test bench. The main conclusions of this paper are as follows:  
(1) The experimental results show that the output flow amplitude of the HPFCV is about 24.5 L/min in the low-frequency state at 1 Hz and 10 Hz. After that, the amplitude of the resulting flow begins to gradually decay as the frequency continues to rise, and the prototype's \(-\)3 dB frequency response is about 23.5 Hz.  
(2) There are several limitations to our proposed solution. Firstly, the frequency response of the prototype may not suffice for high-frequency applications. Additionally, significant discrepancies between experimental and simulation results were observed, likely due to the longer rubber hoses at the inlet and outlet of the hydraulic cylinder. Moreover, the stroke length of the hydraulic cylinder may also influence valve performance, introducing variability in the measurements. Lastly, the current design lacks flexibility in controlling the output flow range, which may restrict its use in applications with variable flow rate requirements.  
Figure 6: Bode plot experimental results.  
Figure 7: Bode diagram corresponding to different Young’s modulus.  
(3) To address these limitations, future development directions will focus on several key areas. Improving the frequency response of the valve will be essential to extend its usability for high-frequency flow control applications. Investigating alternative materials or design adjustments for the rubber hoses can help mitigate their influence on measurement results. Additionally, optimizing the hydraulic cylinder design will ensure consistent performance across different stroke lengths. Integrating a proportional throttle valve will also enhance the versatility of the system by allowing for adjustable mean flow rates. Lastly, we plan to design and implement a unidirectional flow calibration test bench to facilitate continuous flow measurement. By addressing these areas, we aim to enhance the performance and applicability of the HPFCV in various fluid power systems.  
Validation, Y.W.; Writing--original draft, D.Z. and K.Z.; Writing--review & editing, J.R. and C.D.; Visualization, R.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the Zhejiang Provincial Natural Science Foundation, grant number LY21E050013, and in part by the National Natural Science Foundation of China, grant number 51805480.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to Data non-disclosure is necessary for ethical reasons, to protect the rights and welfare of the study participants.  
The authors declare no competing interests.
###### Abstract  
Rotor airfoil design involves multi-point and multi-objective complex constraints. How to significantly improve the maximum lift coefficient and lift-to-drag ratio of rotor airfoil is a fundamental problem, which should be solved urgently in the development of high-performance helicopter rotor blades. To address this, discrete co-flow jet (DCFJ) technology is one methods with the most potential that can be harnessed to improve the performance of the rotor airfoil. In this study, wind tunnel experiments are conducted to study the effect of DCFJ technology on lift enhancement and drag reduction of OA312 airfoil. Furthermore, the performance improvement effects of the open co-flow jet (CFJ) and DCFJ technologies are studied. In addition, the influence of fundamental parameters, such as the obstruction factor and relative unit length, are analyzed. Results demonstrate that DCFJ technology is better than CFJ technology on the performance enhancement of the OA312 airfoil. Moreover, the DCFJ rotor airfoil can significantly reduce the drag coefficient and increase the maximum lift coefficient and the stall angle of attack. The maximum lift coefficient can be increased by nearly 67.3%, and the stall angle of attack can be delayed by about 12\({}^{\circ}\). The DCFJ rotor airfoil can achieve the optimal performance when the obstruction factor is 1/2 and the relative unit length is 0.025.  
discrete co-flow jet; rotor airfoil; active flow control; wind tunnel experiment; performance enhancement +
Footnote †: journal: Applied Sciences
## 5 Conclusions  
This study aimed to predict potential pallet collapse incidents using advanced data analytics proactively and to recommend preventative strategies based on these predictions to reduce the incidence of cargo loss. To achieve this goal, the CRISP-DM methodology was employed, which facilitated a systematic progression through six key stages that structured the research process and the development of the predictive tool.  
Two primary modelling techniques were employed: the Decision Tree and Random Forest models. These models were selected for their proven effectiveness in predictive analytics within similar contexts. The hyperparameters of both models were meticulously fine-tuned through Grid Search Cross-Validation, and the class imbalance problem was addressed using random oversampling to balance the dataset between the majority and minority classes.  
The conducted evaluation focused on _F1-score_, a metric chosen for its ability to harmonize the trade-off between _Recall_ and _Precision_. The results demonstrated that the Random Forest model consistently outperformed the Decision Tree model, aligning with previous studies that highlight the Random Forest model as superior for this type of prediction.  
Significantly, this study not only reaffirmed the importance of the destination country as a key predictor but also introduced novel insights into other influential factors. Variables such as container height, container diameter, and delivery date temperature emerged as crucial predictors of pallet collapse, marking an advancement in the literature.  
Future work should aim to expand the scope of this research by incorporating additional data sources and variables to refine further the predictive models, as well as exploring alternative machine learning techniques. Additionally, investigating the real-time application of these models in operational settings could provide practical insights and further validate their effectiveness. Addressing these areas will not only advance the current research but also contribute to more robust and adaptive solutions for the glass industry and beyond.  
Conceptualization, J.M.R.S.T. and M.C.F.; methodology, F.C., J.M.R.S.T. and M.C.F.; validation J.M.R.S.T. and M.C.F.; formal analysis, F.C.; investigation, F.C.; writing--original draft preparation, F.C.; writing--review and editing, J.M.R.S.T. and M.C.F.; supervision, M.C.F. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The datasets presented in this article are not readily available due to the company's confidentiality requirements.  
The authors declare no conflicts of interest.
# Recent Progress on Irradiation-Induced Defect Engineering of Two-Dimensional 2H-MoS2 Few Layers
## 6 Irradiation-Induced Properties  
Pure 2H-MoS\({}_{2}\) crystalline bulks are indirect band-gap semiconductors and show diamagnetic from 10 K to room temperature. Their physical properties are sensitive to structures and defects. Irradiation produces defects in MoS\({}_{2}\) few-layers and affects their properties significantly. Below, the optical properties, electronic properties, catalytic properties, and magnetic properties are summarized.
###### Abstract  
In this paper, a backstepping sliding mode controller based on a nonlinear disturbance observer (NDO-SMC) is proposed to realize the high-performance speed control of a permanent magnet synchronous motor (PMSM). This paper compares the advantages and disadvantages of the traditional backstepping sliding mode control algorithm (SMC) and integral backstepping sliding mode control algorithm (I-SMC) in the face of mismatched disturbances. In view of the shortcomings of these two algorithms, the idea of using a disturbance observer to observe disturbance and carry out dynamic compensation is proposed, and the composite controller is designed. The overshoot and settling time is improved by 30% and 8 s, respectively, for the proposed NDO-SMC controller compared with the SMC controller. The simulation and experimental results illustrate that the designed controller not only effectively solves the torque jitter problem of SMC, but also improves the overshoot problem caused by the integral module of I-SMC. There is also a better matching degree between the theoretical derivation, the simulation results, and experimental data. It also proves that the composite control algorithm proposed in this paper provides a meaningful solution to the operation disturbance suppression problem of the permanent magnet synchronous motor.  
PMSM control; backstepping sliding mode controller; nonlinear disturbance observer Article
# TSINet: A Semantic and Instance Segmentation Network for 3D Tomato Plant Point Clouds
## 2 Materials and Methods
### Network Architecture
#### 2.3.3 Dual Attention-Based Feature Enhancement Module (DAFEM)  
To effectively fuse and enhance task-relevant features prior to the final prediction, we propose a Dual Attention-Based Feature Enhancement Module (DAFEM), which integrates feature fusion and attention-based refinement within a unified framework. Specifically, the semantic feature map \(F_{S}\) and instance feature map \(F_{I}\) output from the decoder are first processed via 1D convolution layers and combined using element-wise addition to obtain the fused feature \(F_{f}\). In the semantic segmentation branch, the feature map from the previous layer of \(F_{S}\) is upsampled to match the number of points in \(F_{f}\) and concatenated with \(F_{f}\). A subsequent 1D convolution is then applied to extract more semantically expressive features. Similarly, in the instance segmentation branch, the previous-layer feature map  
Figure 5: The architecture of the semantic segmentation decoder branch, including skip connections between encoder and decoder layers for multi-scale feature fusion and spatial detail recovery.  
of \(F_{I}\) is upsampled and concatenated with \(F_{f}\), followed by a 1D convolution to generate features with stronger instance-level discriminability.  
The final fused features from each branch are then refined by two complementary attention mechanisms: spatial attention (SA) and channel attention (CA). The SA module generates a spatial attention map to emphasize geometrically salient regions, enhancing the model's capacity to perceive spatial structure and contextual dependencies. In parallel, the CA module models inter-channel dependencies by computing a channel attention matrix that quantifies the influence among channels, enabling adaptive re-weighting of feature channels based on their importance. This mechanism enhances the expressiveness and discriminability of the learned features.  
Ultimately, the attention-enhanced features from the two branches are used separately for semantic classification (via Argmax) and instance embedding (via MeanShift clustering). By jointly modeling both spatial and channel-wise dependencies, DAFEM improves global context modeling, strengthens feature representation, and enhances the robustness and accuracy of the network in both semantic and instance segmentation tasks.
## 5 Case Analysis
As can be seen from Figure 20, IMF1 is the high-frequency noise component; the characteristic frequencies appear in IMF2 and IMF3 with aliasing phenomena. In IMF2, the characteristic frequency is prominent, and there is no interference. However, there is a lot of interference noise around the characteristic frequency, and the characteristic frequency is weak in IMF3. Compared with the result of the inner ring fault envelope signal in Figure 19, the IMF order of EMD decomposition is reduced by two orders after the noise is reduced. As can be seen from Figure 21, the IMF1 is still high-frequency noise interference. In MF2, the characteristic frequency is prominent, there is no interference, and the mode aliasing phenomenon disappears. Compared with the first-order result in Figure 20, the IMF order of EMD decomposition decreases by one order after denoising is added. As can be seen from Figure 22, the characteristic frequency is in IMF1, and the characteristic frequency is very obvious and easy to identify, which indicates that the original signal has been fully denoised after the third-order stochastic resonance is carried out. The experimental results show that the CASTSR method can reduce the IMF order of EMD decomposition and eliminate mode aliasing. After three intervals of stochastic resonance are carried out, the characteristic frequency is in the IMF1 by EMD decomposition, and the characteristic frequency becomes more prominent and obvious with the increase in the order, which improves the quality of SNR and EMD decomposition of the output signal. Therefore, CASTSR based on the EMD method can accurately extract the fault features of weak signals for the inner ring of rolling bearings.
## 2 Related Work and State-Of-The-Art Technologies  
In the following section, related works are discussed. Additionally, existing concepts and state-of-art technologies shown in Figure 2 used for implementation of the framework are presented.
# Collecting Sensed Data with Opportunistic Networks: The Case of Contact Information Overhead
## 2 Problem Background
### Overhead in Exchanging Contact Information  
The PRoPHET routing approach is as follows. When two nodes encounter each other, they exchange summary vectors that contain: (i) a message vector, which is a list of message identifiers in their buffers; and (ii) a contact vector, which is a list of every known node (i.e., directly encountered nodes as well as their neighbors) and the corresponding forwarding utility for each node. With the information received from the contact vector (i.e., the contact information), each node updates its knowledge about the network by re-computing forwarding utilities for nodes in its list as well as for new ones provided by the other node. It is after this process that the nodes in contact decide which messages to request from the other.  
Certainly, an amount of overhead is incurred in exchanging contact information, which varies directly with the number of nodes and encounters in the network. First, since known nodes do not necessarily have to be directly encountered, the size of the list containing contact information eventually converges with the total number of nodes in the network [47]. Second, the overhead incurred in exchanging the information in this list (i.e., sending plus receiving) increases with the number of encounters in the network. Although portable handheld devices of recent times may possess enough storage space and processing capabilities (to maintain and update contact information, respectively), insight regarding the impact of contact information size on data exchange success and energy consumption is lacking in literature. This leads to our first contribution, in which we model contact information overhead and then investigate its impact on data exchange success and the energy consumption on portable handheld devices.
# A Lightweight Crop Pest Detection Method Based on Convolutional Neural Networks
## 3 Results  
### Model Training Process  
All experiments were performed on an ubuntu system with NVIDIA RTX A4000 and Intel Xeon Gold 5320. The system had 32 GB of RAM. Python 3.8.13 and pytorch 1.10.1 were used to implement the source code.  
In order to avoid drastic oscillations of the model during training, this study uses the Adam optimizer with an initial learning rate of 0.001, beta1 of 0.937 and beta2 of 0.999. The input resolution during training is 416 \(\times\) 416, the batch size is 32 and the training epoch is 200 rounds. We enabled 12 threads to read the data to reduce the IO time by as much as possible.  
The loss changes and mAP changes of the training process are shown in Figure 10. The trend of the loss curve and mAP curve shows that there is no large model oscillation during the training process. Especially in the later period, the two curves are smoother, which is largely due to the fact that the Adam optimizer can dynamically adjust the learning rate. From an overall perspective, the model tends to converge after 50 epochs, and finally reaches a stable convergence state near 190 epochs.  
Figure 9: The complete architecture for crop pest detection using our method.
###### Abstract
The 5G network is the future of mobile networks, and C-RAN is the 5G network component that groups all BBUs in a centralized BBU pool. In order to enhance C-RAN resource utilization while protecting the minimum QoS required for each 5G slice, an efficient radio resource allocation method is necessary and critical to controlling the coexisting 5G slices. This motivated us to propose a priority-based radio resource allocation method for 5G C-RAN with different coexisting 5G network slices. This method differentiates between the different slices based on their required QoS. The queuing model is used to store the delay-tolerant slices. This will decrease their forced termination rate and increase C-RAN resource utilization without degrading the QoS of the higher-priority slices. The proposed model allows the interrupted slice with the lowest priority to be restored in its queue in order to provide a chance to reattempt the service later. Therefore, it will increase its service completion rate without degrading the higher-priority slices. The performance measures of the proposed model are conducted and derived using a continuous-time Markov chain (CTMC) model. Figure 1: 5G network slicing concept. The proposed scheme distinguishes the 5G use cases (eMBB, mMTC, and uRLLC) based on their priority level and uses a queuing system with a feedback queue to accommodate the arriving 5G slice requests with lower priority (eMBB, mMTC) or interrupted mMTC services. The queuing system with feedback will improve the service completion rate of eMBB and mMTC without degrading the uRLLC services, thereby increasing the BBU pool utilization of C-RAN. The contributions that distinguish this research from most of the previous works are as follows:  
* A priority-based resource allocation scheme with a queuing model is proposed for 5G C-RAN with eMBB/mMTC/uRLLC coexistence. * The priority queuing model is used to buffer the lower priority slices, and the interrupted non-delay-sensitive mMTC services are allowed to be returned to their queue to reattempt the service. * Mathematical equations are derived for the main performance measures of the proposed scheme using a continuous-time Markov chain (CTMC) model. * A simulation model is developed to compare with and validate the results of the proposed analytical model. * The proposed system is compared with the traditional queuing system to verify its main objectives. The remainder of this paper is organized as follows: In Section 2, related works are described. The system model and assumptions are explained in Section 3. In Section 4, the proposed work is explained. Furthermore, Section 5 provides the performance analysis of the proposed scheme. In Section 6, we provide the numerical results of the proposed scheme. Finally, concluding remarks are made in Section 7.