esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Laser-Driven Very-High-Energy Electron/Photon Beam Radiation Therapy System
### Design of Laser Plasma Accelerators for VHE Electron Beams
\begin{table}
\begin{tabular}{l c} \hline \hline
**Parameters** & **Symbols** \\ \hline Speed of light in vacuum & \(c\) \\ Laser wavelength & \(\lambda_{L}\) \\ Laser angular frequency & \(\omega_{L}\) \\ Laser intensity & \(I_{L}\) \\ Laser spot radius & \(r_{L}\) \\ Laser pulse duration & \(\tau_{L}\) \\ Laser peak power & \(P_{L}\) \\ Laser pulse energy & \(U_{L}\) \\ Normalized vector potential & \(a_{0}\) \\ Normalized matched spot radius & \(R_{m}\) \\ Critical power for relativistic self-focusing & \(P_{c}\) \\ Electron charge & \(e\) \\ Electron mass & \(m_{e}\) \\ Classical electron radius & \(r_{e}\) \\ Plasma electron density & \(n_{e}\) \\ Plasma electron frequency & \(\omega_{p}\) \\ Plasma wave number & \(k_{p}\) \\ Critical plasma density & \(n_{c}\) \\ Group velocity & \(\
u_{g}\) \\ Normalized group velocity & \(\beta_{\mathrm{g}}\) \\ Relativistic factor related to the group velocity & \(\gamma_{\mathrm{g}}\), \(\gamma_{\mathrm{g}0}\) \\ Correction factor of the group velocity & \(\kappa_{\mathrm{self}}\) \\ Bubble radius & \(R_{B}\) \\ Accelerating electric field with beam loading & \(E_{Z}\) \\ Accelerating electric field without beam loading & \(E_{M}\) \\ Non- relativistic wave-breaking field & \(E_{0}\) \\ Reduction factor of the accelerating field & \(a\) \\ Maximum energy gain & \(W_{\mathrm{max}}\) \\ Design electron beam energy & \(E_{b}\) \\ Normalized maximum energy gain & \(\Delta\gamma_{\mathrm{max}}\) \\ Dephasing length & \(L_{\mathrm{dp}}\) \\ Accelerator length & \(L_{\mathrm{acc}}\) \\ Pump depletion length & \(L_{\mathrm{pd}}\) \\ Electron beam charge & \(Q_{b}\) \\ Root mean square electron beam radius & \(\sigma_{\mathrm{b}}\) \\ Beam loading efficiency & \(\eta_{\mathrm{b}}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A list of symbols for designing laser plasma accelerators. For Case E, the laser system should be capable of delivering a 150 mJ drive pulse with 20 fs duration at 100 Hz to the laser plasma accelerator for producing a 10 pC electron bunch. The electron beam energy can be controlled by adjusting the laser pulse energy, plasma density, and accelerator length.
# Research on a Piezoelectric Pump with Flexible Valves
## 1 Introduction  
As an actuator, the micro-pump plays an irreplaceable role in numerous fields, such as biomedicine, aerospace, and so forth [1, 2, 3, 4]. The reason for this is that the micro-pump has the advantages of precision for controlling flow and a compact structure. The piezoelectric (PZT) pump is a PZT-driven micro-pump. By controlling its PZT film and valve body, the fluid can be transported unidirectionally, or the flow rate and pressure of the fluid can be changed [5, 6, 7]. With the continuous expansion of the application of the piezoelectric pump, its taxonomy is increasing in various fields. Among them, the PZT pump can be classified according to the type of valve body; the valve body can be either a movable valve or a no-moving-part valve.  
Movable valves include overall opening valves [8], cantilever valves [9], helical linear-shaped valves [10], and \"E\" type valves [11], and all of these can appear in valved PZT pumps. The movable valves listed above are soft structures made of rigid materials. Similarly, there are many types of no-moving-part valves, for instance, nozzle/diffuser tubes [12, 13], Tesla tubes [14], spiral tubes [15], vortex diodes [16], streamlined flow tubes [17], and raindrop-shaped tubes [18], and all of these can be fitted with valveless PZT pumps. Thus, a PZT pump with a movable valve is called a \"valued PZT pump\", and a PZT pump with a no-moving-part valve is called a \"valveless PZT pump\". These two types of pumps have their advantages and disadvantages. In general, because of the movable parts, the valved PZT pump has a complicated structure, and the closed valve reduces the survival rate of living organisms during transport, but it can obtain a higher flow rate and back pressure. On the contrary, the structure of the valveless PZT pump is simple, and it can decrease the probability of crushing damage to the transported substance, but the flow rate is small.  
In contrast to the traditionally defined valved PZT pump and the valveless PZT pump, our research group proposed a PZT pump with built-in compliant structures [19]. Based on this, the structure of the valve was improved in this study; a new type of PZT pump with flexible valves (PPFV) is proposed. The valve body of the pump imitates the structure of the venous valve and its characteristics of passive opening and closing with changes in heart pressure, which makes it set a valved state and valveless state in one. Thus, this kind of pump can realize the reciprocal conversion of the large flow rate, high pressure difference and the small flow rate, low pressure difference.
# Hybrid LSTM-Attention and CNN Model for Enhanced Speech Emotion Recognition
## 1 Introduction
* Comprehensive evaluations were conducted using two benchmark datasets, TESS and RAVDESS. The results clearly highlight the superior effectiveness of our method in emotion detection. Together, the findings of this study have greatly deepened our understanding of SER, providing key perspectives for the creation of advanced speech recognition systems. The implications of these discoveries extend across multiple disciplines, from emotion detection in human-robot interactions to advancements in speech therapy techniques and improvements in mental health assessments. The layout of this paper is organized as such: Section 2 delves into a thorough examination of contemporary research on SER models using deep learning techniques and attention mechanisms focused on speech characteristics. Sections 3 and 4 meticulously explain our suggested SER model and provide evidence for its efficiency, juxtaposed with existing standards. Our intention is to give readers a detailed insight into the model's framework and its capabilities while contextualizing it within the wider SER landscape. Section 5 offers a conclusive recap and touches upon potential directions for upcoming research. The paper concludes with a bibliography that encompasses a range of the latest scholarly works in the SER field.
# WDS-YOLO: A Marine Benthos Detection Model Fusing Wavelet Convolution and Deformable Attention
## 4 Experiments
### Experiment Results
#### 4.2.2 Comparative Experiment  
We perform a comprehensive assessment of the effectiveness of various mainstream object detection models in underwater settings, including the newest versions: YOLOv9-t, YOLOv10n, and YOLO11n. The evaluation metrics comprised the mean average precision (mAP@50), model size (M), and computational complexity (GFLOPs) to assess the performance of each model in terms of accuracy and efficiency. The experimental results are presented in Table 3.  
This study conducted a comprehensive comparative analysis of mainstream object detection models. The evaluation metrics comprised mAP@50, parameters, and computational complexity, providing a holistic assessment of model performance across accuracy and efficiency dimensions.  
Regarding detection accuracy, WDS-YOLO demonstrated superior performance, achieving an mAP@50 of 85.6%. This represents a substantial improvement of 1.0 to 7.0 percentage points compared to most models, particularly exhibiting enhanced robustness in complex underwater environments. Concerning model complexity, WDS-YOLO maintained a modest parameter count of 3.2 M, substantially lower than traditional two-stage detectors, while remaining competitive with lightweight models (e.g., YOLOv8n and YOLOv9-t).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**WTConv** & **DASPPF** & **SF-PAFPN** & **P/\%** & **R/\%** & **mAP@50/\%** & **Params/M** & **FPS/(f\(\cdot\)s\({}^{-1}\))** \\ \hline \multirow{4}{*}{\(\surd\)} & \multirow{4}{*}{\(\surd\)} & & 81.5 & 77.8 & 83.5 & 3.0 & 114.1 \\  & & & 82.4 & 76.0 & 83.7 & 2.6 & 118.3 \\  & \(\surd\) & & 83.6 & 77.2 & 84.3 & 3.2 & 113.1 \\  & \(\surd\) & & 83.2 & 78.1 & 84.7 & 3.3 & 109.5 \\  & \(\surd\) & & 82.6 & 77.2 & 84.6 & 3.5 & 107.1 \\ \(\surd\) & & & 82.7 & 77.9 & 84.9 & 2.9 & 105.5 \\ \(\surd\) & \(\surd\) & & 83.8 & 78.6 & 85.6 & 3.2 & 104.5 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Results of ablation experiment.  
While the computational cost of 11.4G FLOPs represents a trade-off for improved accuracy, being marginally higher than some models, WDS-YOLO maintains real-time performance for underwater detection tasks, striking an optimal balance between accuracy and efficiency. Collectively, these results demonstrate that WDS-YOLO excels in both detection accuracy and computational efficiency, making it particularly well-suited for resource-constrained underwater detection scenarios. The model's exceptional accuracy coupled with low computational overhead underscores its remarkable generalization capability in complex underwater environments.
## 3 Discussion
recently performed a larger study based on a sample of 170 patients treated with Invisalign(r) clear aligners. Of these, 90 patients were in the study group also undergoing PBM therapy with the Orthopulse(r) device, while the remaining 80 patients were placed in the control group. Again, a significant increase in weekly tooth displacement was observed in the study group, with an average of 0.33 mm/week compared to 0.21 mm/week in the control group, resulting in a reduction in treatment time of 57.7 weeks [18]. In a very recent review, [PERSON] et al. stated that the evidence from randomized controlled trials concerning the effectiveness of nonsurgical interventions to accelerated orthodontic treatment is of low to very low certainty [28]. From the limited evidence available, they did not find a benefit from the use of light vibrational forces or photobiomodulation for a reduction in orthodontic treatment duration. However, there could be a potential benefit from photobiomodulation to reduce the length of the early stage of orthodontic treatment only and increase the speed of orthodontic tooth movement; it is important to realize that the results from discrete phases do not necessarily have a similar impact on the full orthodontic treatment duration. Further well-designed studies with longer follow-upare needed because, in any case, the use of photobiomodulation is still limited and the results are limited. In addition, the case reported in this article is to be considered perfectly in line with the results available in the relevant literature and presents itself as a further example of the effectiveness of photobiomodulation in accelerating orthodontic tooth movement. Reducing the treatment time also made it possible, in this case, to maintain good patient compliance throughout the duration of the therapy, and, in this way, it was possible to achieve all the set clinical goals. Of all the acceleration systems available in the orthodontic field today, photobiomodulation is certainly the least invasive and the most easily exploited, together with clear aligners for therapy managed at home by the patient autonomously, following the definition of the simple modalities of use. In addition, the possibility of wirelessly connecting the OrthoPulse(r) device to the respective digital application allows the physician to monitor therapy progress remotely, opening up to a modern and increasingly contemporary concept of telemedicine also associated with the dental field (teledentistry) [27; 29]. In addition, a shortened aligner replacement timing thanks to PBM and, consequently, a reduced use of each aligner over time can reduce the risk of deformation and aging of the aligners themselves due to being in the mouth and contact with food, drink, or substances, e.g., from smoking habits, as in the present case.
# On Microservice Analysis and Architecture Evolution:
## 4 Review of the Selected Studies
### Challenges and Goals
#### 4.2.1 Architectural Analysis  
Most of these papers use architectural analysis to address a specific goal within pre-existing microservice architectures, such as improving security or detecting faults. This is often done by creating tools or frameworks that take a white-box approach to analyze the architecture. Some papers, however, do not focus on analyzing the architectures of microservices. The scopes of these papers tend to be broader, and most of them do not present a new tool or framework. However, of those that do, the approach is often black-box and serves goals not specific to a single microservice, such as identifying the optimal configuration for a microservice application. A few papers discussed key differences between analyzing microservice architecture in comparison to other architectures. [PERSON] et al. [14] discuss some pitfalls that traditional code analysis has with addressing microservice systems, namely that it overlooks important enterprise development framework constructs, which are key for building enterprise microservice systems. Some papers treat the relationships between Service-Oriented Architecture (SOA) and microservices differently. For instance, [PERSON] et al. [47] does not necessarily distinguish differences between SOA and Microservices since the paper's proposed approach of graph-based root cause analysis can be used on both types of systems. [PERSON] et al. [1] discusses the key differences between SOA, microservices, and Self-Contained Systems (SCS). One of the major differences it mentioned was that services are brought to production independently of each other in a microservice architecture, whereas this is not the case with most SOA solutions. [PERSON] et al. [63] begins by comparing SOA and microservice architectures. For example, there are concepts and techniques from microservice architecture that were borrowed from SOA, such as scalability. Microservices, however, differ in their emphasis  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Tool** & **Reference** & **Newly Developed** & **Purpose** \\ \hline Arcan & [29] & No & Code smells detection \\ MSExtractor & [16] & Yes & Monolithic decomposition \\ MSANose & [27] & Yes & Code smells detection \\ MICROLYZE & [34] & Yes & Architecture reconstruction \\ Dapper & [44] & No & Query tracing \\ Zipkin & [44] & No & Query tracing \\ Osoprofiler & [44] & No & Query tracing \\ Microscope & [52] & No & Graph generation \\ JCallGraph & [53] & Yes & Tracing and analytics \\ \(\mu\)TOSCA & [22] & Yes & Architectural smells detection \\ [PERSON] & [68] & No & Performance analysis \\ \hline \hline \end{tabular}
\end{table}
Table 4: Identified tools.  
on service granularity and the fact that they have two types, functional or infrastructure, while SOA can have several types. Serverless architecture has also been studied in the context of microservices.
# A Novel Perceptual Hash Algorithm for Multispectral Image Authentication
## 3 Our Perceptual Hash Algorithm Design
### Band Fusion-Based Edge Feature Extraction
#### 3.2.1 Grid Division  
To make the hash value more sensitive to local modification in the MS images, each band is partitioned into \(M\times N\) grids, and the grid is denoted as \(G_{wh}^{k}\) in which \(w=1\), \(2\),..., \(M\), \(h=1\), \(2\),..., \(N\), and \(k\) denote the band number. Thus, the grids in different bands of the same position composed a grid set which is denoted \(G_{wh}\), as follows.  
\[G_{wh}\ =\ \left\{G_{wh}^{1},\ G_{wh}^{2},\ldots,\ G_{wh}^{n}\right\} \tag{5}\]  
As the tamper location ability is based on the resolution of the grid division, the higher the resolution of the grid division, the more fine-grained the authentication granularity can be. While the computational cost would be raised at higher resolutions, we need to segment the remote sensing  
Figure 4: Framework of the proposed perceptual hash algorithm.  
image into more grids in order to increase both the time for computing perceptual hash values, as well as comparing the values. The choice of the grid division resolution thus presents a trade-off between the cost and tamper location ability. Our work aims at designing such an authentication model with good balance between cost and performance.
## 4 Results
### Hydrological Elements
This characteristic may be attributed to the  
Figure 7: Changes in surface runoff, baseflow (the contribution of lateral flow and groundwater to streamflow), evapotranspiration, and precipitation in different months. prevalence of Dystrict Regosol, a loose soil type distributed across numerous flat terrain areas within the basin. During the wet months (June-October), these three components account for 2.5%, 41.6%, and 14.9% of the precipitation, respectively. Conversely, in the dry months (January-May, November-December), these three components represent 2.1%, 47.7%, and 34.6% of the precipitation, respectively. This pattern reveals that as precipitation decreases, the proportion of surface runoff decreases, while the proportions of lateral flow to recharge and groundwater to recharge increase. Additionally, the annual basin-wide evapotranspiration in the region is 524.5 mm, accounting for 72.9% of the annual precipitation. Evapotranspiration, being the primary output of water quantity, is closely correlated with the vegetation cover and temperature of the basin. The significant contribution of evapotranspiration in this study area can be attributed to several factors. Firstly, the predominant land use in the area is forest, and forests have the capacity to retain water, making them a substantial source of water for transpiration by trees. Secondly, the high mean annual temperature, which averages at 16.0 \({}^{\circ}\)C, also plays a crucial role. In the intra-annual variation of evapotranspiration, although the precipitation in July is not the highest throughout the year, the evapotranspiration in this month is the highest (see Figure 7). This anomaly is primarily driven by the elevated temperatures in July, which lead to intensified water surface evaporation and plant transpiration. Figure 8 illustrates the correlation between the principal hydrological components and precipitation for each of the 12 months. Each hydrological element has been tested for significance (Table 4). Correlation coefficients are established, revealing the associations between precipitation and various hydrological factors. Specifically, the correlation coefficients between precipitation and surface runoff, recharge of runoff through lateral flow, recharge of runoff through groundwater, and baseflow (lateral flow + groundwater) stand at 0.96, 0.92, 0.69, and 0.86, respectively. Notably, the correlation coefficient linking evapotranspiration and temperature (0.77) surpasses that of evapotranspiration and precipitation (0.57). Figure 8: The relationship between surface runoff, baseflow (lateral flow and groundwater contribution to streamflow), evapotranspiration, and precipitation (**a–e**); relationship between evapotranspiration and air temperature (**f**).
# Reducing Detrimental Communication Failure Impacts in Microgrids by Using Deep Learning Techniques
## 5 Communication Protocol and Latency
### Latency Experiment with Various Payload Sizes
Figure 10: MQTT end-to-end latency results. The effect of TCP segmentation is clearly visible on the different measured latency values. * For the previously explained application of this research, which the communication system is designed to be used, the redundant information is planned to be in type of power references for several future time steps. That means a number of added numerical values in the scale of 50 or less, therefore the payload sizes will not exceed the upper limit of this experiment.
# Anchorage Loss Evaluation during Maximillary Molars
###### Abstract
Several articles [17; 18; 19] in the literature analyzed the molar distalization performed by CAT, reporting predictable distalization movement up to 3 mm. Among them, [PERSON] et al. [17] showed that CAT is appropriate for maxillary dentition distalization up to 2-3 mm with no significant mesiodistal tipping movement when it is followed the protocol of 50% sequential distalization, combined with Class II elastics and rectangular vertical attachments on upper molars and premolars. However, as CAT uses dental anchorage, undesirable effects can happen in the same way as with conventional intraoral appliances. In the literature, the premolar and incisor anchorage loss obtained during molar distalization performed with traditional intraoral devices is widely described [3; 20; 21]. More than 20% of the space gained between the first upper molars and premolars during the activation of these devices derives from the mesialization of the anterior anchorage unit [22]. On the contrary, to our latest knowledge, very few studies [1; 17; 18; 23; 24] analyzed the anchorage loss obtained during the upper-molar distalization movement with CAT, mainly evaluating this side effect at the end of treatment. Among them, [PERSON] et al. [23] described mesial and labial proclination in maxillary anterior teeth, identifying the center of rotation at the intersection of the apical and middle third of the roots, with fewer unwanted movements determined by the application of Class II elastics. [PERSON] et al. [24] evaluated a group of 38 patients with a mean age of 25.4 years, and they observed a statistically significant relationship between the amount of central- and lateral-incisor anchorage loss and the total maxillary molar distal movement. Non-significant correlation between the amount of molar distal movement and mesial shift of the canine was found. None of these studies analyzed the anchorage loss at the level of upper premolars and canines at the end of the upper first molar distalization before the retraction of the anterior segment. Therefore, the present retrospective study aims to analyze, using three-dimensional (3D) digital casts, the premolar and canine anchorage loss occurring during maxillary molar distalization in young adults presenting with Class II occlusal relationship treated by CAT.