esa-sceva/satcom-chunk-collection huggingface dataset:
# Development of Ultrasonic Pulsed Plasma Jet Source for Remote Surface Treatment
## 1 Introduction  
Atmospheric-pressure plasma has been applied to the decomposition and treatment of industrial waste, trace element analysis, and cutting and processing of high-melting-point materials because it does not require a vacuum vessel or exhaust system and can generate higher-density plasma than low-pressure plasma [1; 2; 3; 4; 5; 6; 7; 8]. Recently, however, the development of atmospheric-pressure low-temperature plasma, a type of atmospheric-pressure nonequilibrium plasma, has attracted attention for its application in various industrial and medical fields. This plasma is low-temperature and does not cause thermal damage to the irradiated object; therefore, a wide range of application research is underway, including hydrophilization of surfaces and improvement of adhesive strength in the material field and hemostasis, sterilization, and wound healing in the medical field [9; 10; 11; 12; 13]. In a typical atmospheric-pressure low-temperature plasma generator, plasma is generated by supplying plasma-generating gas from a cylinder to a discharge unit and applying a high voltage to the electrodes to cause a discharge. The generated plasma is ejected outward by the gas flow. The active species generated in the plasma are then sprayed onto the material to be treated, causing a variety of useful reactions. However, because the active species in the plasma are deactivated in a short time in the air [14], only objects within a short distance of a few millimeters can be effectively treated, and the treatment efficiency decreases as the distance between the plasma generator and the object to be  
distance from an atmospheric-pressure low-temperature plasma generator. In this system, atmospheric-pressure plasma generated between electrodes is pulsed outward with pulsed high-pressure gas, and the active species generated in the plasma are transported to distant objects to be treated. This paper describes the basic characteristics of a supersonic pulsed plasma jet and the results of its surface hydrophilization.
## 4 Overview of the Proactive Transmission of Replicated Frames (PTRF) Mechanism
### PTRF Operation  
As we have anticipated in Section 1, we have designed three different approaches to the PTRF mechanism. The approaches differ from each other in two aspects, (i) what are the devices that carry out the replication of frames and the elimination of surplus replicas, and (ii) what is the technique used to calculate the number of replicas. Figure 3 shows the basic operation of the three approaches in the presence of temporary faults in the links. Note that, even though in this work we assume that our network implements CQF to schedule frames, PTRF is designed to operate with any schedule, not only CQF. For this reason, in our description, we talk about time instants and not windows. All the subfigures depict the same network, which consists of two end-systems and two bridges connected in a line topology. The talker \(T_{1}\) transmits a replicated frame in instant \(t_{i}\), which is forwarded by the bridge \(B_{1}\) in instant \(t_{i+1}\) and by bridge \(B_{2}\) in instant \(t_{i+2}\). Furthermore, during \(t_{i+1}\) a temporary fault affects link \(l_{2}\) and during \(t_{i+2}\) a temporary fault affects link \(l_{3}\).  
We next explain the main characteristics of the approaches and we describe how each one behaves in the scenario depicted in Figure 3.
## 3 Results
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Models** & **Groups** & **Accuracy** & **Precision** & **Recall** & **F1-Score** \\ \hline ResNet18 & White & 37.50 \(\pm\) 2.24 & 0.36 \(\pm\) 0.03 & 0.38 \(\pm\) 0.02 & 0.34 \(\pm\) 0.03 \\  & non-White & 21.90 \(\pm\) 1.78 & 0.73 \(\pm\) 0.03 & 0.22 \(\pm\) 0.02 & 0.24 \(\pm\) 0.02 \\ ResNet50 & White & 34.35 \(\pm\) 1.83 & 0.40 \(\pm\) 0.02 & 0.34 \(\pm\) 0.02 & 0.36 \(\pm\) 0.02 \\  & non-White & 36.64 \(\pm\) 1.14 & 0.71 \(\pm\) 0.02 & 0.37 \(\pm\) 0.01 & 0.45 \(\pm\) 0.01 \\ Wide ResNet101 & White & 32.87 \(\pm\) 1.26 & 0.39 \(\pm\) 0.01 & 0.33 \(\pm\) 0.01 & 0.35 \(\pm\) 0.01 \\  & non-White & 42.13 \(\pm\) 1.28 & 0.71 \(\pm\) 0.01 & 0.42 \(\pm\) 0.01 & 0.51 \(\pm\) 0.01 \\ ResNet152 & White & 37.70 \(\pm\) 1.09 & 0.43 \(\pm\) 0.01 & 0.38 \(\pm\) 0.01 & 0.40 \(\pm\) 0.01 \\  & non-White & 43.52 \(\pm\) 0.94 & 0.71 \(\pm\) 0.01 & 0.44 \(\pm\) 0.01 & 0.52 \(\pm\) 0.01 \\ VGG & White & 39.95 \(\pm\) 0.89 & 0.43 \(\pm\) 0.01 & 0.40 \(\pm\) 0.01 & 0.41 \(\pm\) 0.01 \\  & non-White & 37.51 \(\pm\) 0.80 & 0.71 \(\pm\) 0.01 & 0.38 \(\pm\) 0.01 & 0.45 \(\pm\) 0.01 \\ EfficientNet & White & 39.09 \(\pm\) 1.13 & 0.42 \(\pm\) 0.01 & 0.39 \(\pm\) 0.01 & 0.40 \(\pm\) 0.01 \\  & non-White & 38.04 \(\pm\) 0.74 & 0.70 \(\pm\) 0.01 & 0.38 \(\pm\) 0.01 & 0.46 \(\pm\) 0.01 \\ ConvNeXt & White & 39.08 \(\pm\) 0.85 & 0.43 \(\pm\) 0.01 & 0.39 \(\pm\) 0.01 & 0.41 \(\pm\) 0.01 \\  & non-White & 38.73 \(\pm\) 0.70 & 0.70 \(\pm\) 0.01 & 0.39 \(\pm\) 0.01 & 0.47 \(\pm\) 0.01 \\ RegNet & White & 38.66 \(\pm\) 0.71 & 0.43 \(\pm\) 0.01 & 0.39 \(\pm\) 0.01 & 0.40 \(\pm\) 0.01 \\  & non-White & 35.72 \(\pm\) 0.65 & 0.70 \(\pm\) 0.01 & 0.36 \(\pm\) 0.01 & 0.43 \(\pm\) 0.01 \\ Ensemble & White & 56.72 \(\pm\) 6.26 & 0.44 \(\pm\) 0.08 & 0.57 \(\pm\) 0.06 & 0.49 \(\pm\) 0.07 \\  & non-White & 69.23 \(\pm\) 6.41 & 0.53 \(\pm\) 0.08 & 0.69 \(\pm\) 0.06 & 0.60 \(\pm\) 0.08 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of performance metrics before post-processing adjustment for the multiple class formulation, stratified by race.
# Research and Evaluation Method for Echelon Usage of Double-Life Equipment Considering Calendar Life
## 3 Analysis and Solution  
The echelon usage of equipment is a multi-objective decision-making problem. [PERSON], [PERSON] et al. [22] elaborated the evaluation indicators of multiple objectives, especially the quantitative indicators of life echelon uniformity for working life. However, they did not propose the optimal echelon interval determination of echelon uniformity. According to the use control ability and the comprehensive utilization rate, [PERSON], [PERSON] [23] and [PERSON], [PERSON] [24] respectively put forward the calculation method of the optimal step interval to evaluate the life distribution more accurately. Dual-life equipment needs to consider two life indicators. [PERSON], [PERSON] et al.'s [25] treatment method is to use the analytic hierarchy process to weight the two life indicators. [PERSON], [PERSON] et al. [26] deal with the relationship between the two life indicators by calculating the proportion of the optimal double life based on historical data. [PERSON], [PERSON] et al. [27; 28] used a BP neural network to process the weights of various indicators and ranked the equipment use. [PERSON], [PERSON]-[PERSON] et al. [29] proposed to arrange the equipment according to the size of the calendar life, and then use the echelon uniformity to evaluate the working life, but this method is only suitable for the specific life distribution. This paper considers two life indicators at the same time, analyzes the law of life change under different circumstances, proposes the calculation method of the controllable range of equipment under different working life and numbers used, and finally calculates the optimal working life distribution and the sum of the optimal working life when the external environment changes.
# Precision-Boosted Forest Fire Target Detection via Enhanced YOLOv8 Model
## 2 Materials and Methods
### Improved YOLO8 Model
#### 2.3.4 WIoU Loss  
In the context of woodland-hearth goal detection using unmanned-car aerial imagery, challenges arise, specifically in detecting small-sized fire site sources or smoke. YOLOv8 employs DFL and CIoU [31] for bounding box regression, yet CIoU has several drawbacks: it lacks balance between difficult and easy samples, inaccurately penalizes aspect ratios, and involves inverse trigonometric functions in computations. EIoU [32] improves upon CIoU by way of introducing separate penalties for width and height, more precisely reflecting variations between the floor reality and the anticipated boxes. SIoU [33] introduces an angle as a penalty factor, restricting regression freedom and enhancing model convergence speed.  
WIoU represents a loss function for bounding box regression, incorporating a dynamic focus mechanism that is non-monotonic in nature. There are three versions of Wiou, among which v1 uses distance as an attention indicator, v2 reduces the weight of easy examples by constructing monotonic focus coefficients, and v3 considers the outlier values of anchor box quality, dynamically adjusting weights.  
WIoU v1 improves mannequin generalization by decreasing the penalty on geometric measurements; v2 introduces a monotonic center of attention coefficients but reveals slower convergence. WIoU v3 defines an outlier price \(\beta\), dynamically optimizing the weights for excessive and low-quality anchor bins through a non-monotonic focal point thing r, bettering common performance. In this calculation, the measurement of \(\beta\) is considered, meaning great anchor packing containers have a smaller weight in the loss, decreasing hazardous gradients for low-quality anchor boxes. The components for WIoU v1 are proven in Equations (1)-(3):  
\[L_{WIoUv1}=R_{WIoU}\times L_{IoU}, \tag{1}\]  
\[R_{WIoU}=\exp\left(\frac{\left(b_{cx}-b_{cx}^{gt}\right)^{2}+\left(b_{cy}-b_{ cy}^{gt}\right)^{2}}{c_{w}^{2}+c_{h}^{2}}\right), \tag{2}\]  
\[L_{IoU}=1-IoU. \tag{3}\]  
The formula for WIoU v2 is given in Equation (4):  
\[L_{WIoUv2}=\left(\frac{L^{*}_{\text{IoU}}}{L_{\text{IoU}}}\right)^{\gamma} \times L_{WIoUv1},\gamma>0. \tag{4}\]  
The method for WIoU v3 is introduced in Equations (5)-(7). In Equation (6), the parameters \(\delta\) and \(\alpha\) are adjustable hyperparameters that can be tailored to exceptional models.  
\[L_{WIoUv3}=r\times L_{WIoUv1}, \tag{5}\]  
\[r=\frac{\beta}{\delta\alpha^{\beta-\delta}}, \tag{6}\]  
\[\beta=\frac{L^{*}_{\text{IoU}}}{L_{\text{IoU}}}\in[0,+\infty). \tag{7}\]  
Through comparison with various mainstream loss functions, WIoU v3 amalgamates the advantages of EIoU and SIoU. It incorporates a non-monotonic mechanism dynamically to account for anchor box quality, enabling the model to concentrate more on anchor boxes of standard quality, thereby improving target localization ability. In the context of forest fire target detection, WIoU v3 dynamically adjusts the loss weights for small targets, enhancing the model's performance.
###### Abstract  
Multipath transmission in ICN provides high transmission efficiency and stability. In an IP-ICN compatible network environment, unmodified IP terminal devices can access ICN through gateways, benefiting from these performance enhancements. This paper proposes a gateway framework for hybrid IP-ICN multipath transmission systems, enabling protocol conversion and quality of service management. A packet reordering module is integrated at the egress gateway to address complex packet disorder issues caused by ICN multipath transmission, thereby enhancing the service quality provided to IP terminals. A Reordering Buffer Management Method (RBMM) is introduced, consisting of two key components. First, RBMM employs an improved dynamic threshold scheme for reserved buffer partitioning, efficiently identifying congestion and optimizing buffer resource utilization. Second, a flow-priority-based replacement strategy is designed to enhance fairness in resource allocation by evicting packets with lower delivery probability during congestion. Experimental results demonstrate that RBMM dynamically adapts to varying traffic conditions, maintaining high transmission performance while reducing buffer resource consumption. In comparison to existing methods, RBMM significantly reduces queuing delay and flow completion time, providing more balanced resource allocation when multiple flows compete for limited buffer capacity.  
ICN multipath transmission; IP-ICN gateway; packet reordering; buffer management Article
## 4 Numerical Examples
### Numerical Example 2  
In Figure 7, a gate-shaped frame problem [31] is modified and used as example 2. Here, the yield moments \(R_{i}(i=1,2,\cdots 5)\) and the load \(F\) are uncertain parameters with marginal intervals \(R_{1}^{1}=[58\text{k}\text{N}\text{m},78\text{k}\text{N}\text{m}]\), \(R_{2}^{1}=[62\text{k}\text{N}\text{m},84\text{k}\text{N}\text{m}]\), \(R_{3}^{1}=[62\text{k}\text{N}\text{m},88\text{k}\text{N}\text{m}]\), \(R_{4}^{1}=[62\text{k}\text{N}\text{m},84\text{k}\text{N}\text{m}]\), \(R_{5}^{1}=[55\text{k}\text{N}\text{m},75\text{k}\text{N}\text{m}]\), and \(F^{1}=[32\text{k}\text{N},48\text{k}\text{N}]\), respectively. The structure is treated as a series system consisting of four performance functions determined by four failure paths [31], i.e.,  
\[\begin{array}{l}g_{1}=R_{1}+2R_{3}+R_{4}-1F\\ g_{2}=R_{1}+2R_{3}+R_{5}-1F\\ g_{3}=R_{2}+2R_{3}+R_{4}-1F\\ g_{4}=R_{2}+2R_{3}+R_{5}-1F\\ \end{array} \tag{24}\]  
where the height \(l\) is 6 m. The uncertainty domain can be expressed as follows:  
\[\begin{bmatrix}R_{1}-R_{1}^{\text{c}}\\ R_{2}-R_{2}^{\text{c}}\\ R_{3}-R_{5}^{\text{c}}\\ R_{4}-R_{4}^{\text{c}}\\ R_{5}-R_{5}^{\text{c}}\\ F-F^{\text{c}}\end{bmatrix}^{\top}\begin{bmatrix}0.0116&-0.0001&-0.0017&-0.0019&- 0.0021&0\\ -0.0001&0.0088&-0.0008&-0.0009&-0.0016&0\\ -0.0017&-0.0008&0.0065&-0.0005&-0.0005&0\\ -0.0019&-0.0009&-0.0005&0.0092&-0.0012&0\\ R_{5}-R_{5}^{\text{c}}\\ F-F^{\text{c}}\end{bmatrix}\leq 1 \tag{25}\]  
The redundant failure mode and the identification criterion are listed in Table 3. Reliability analysis results for the proposed method, NRBM, and MCS are given in Table 4.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Subsystem** & **Identification Criterion** & **Redundant Failure Mode** \\ \hline \((G_{3},G_{4})\) & \(0\leq\gamma_{34}=0.2280\leq|\arccos(0.956)-\arccos(0.822)|=0.3081\) & \(G_{3}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Redundant failure mode and identification criterion for numerical example 2.  
Figure 7: A gate-shaped frame structure.  
In Table 3, \(G_{3}(g_{3})\) is a redundant failure mode and, hence, can be removed. In Table 4, the proposed method yields the same reliability bounds containing the reference solution from the MCS as the NRBM. Therefore, the former has equivalent accuracy to the latter. For the number of possible ordering alternatives, as listed in Table 4, the proposed method and the NRBM have 6 and 24, respectively. Thus, the former has a higher efficiency than the latter. In summary, for this problem, the proposed method is superior to the NRBM.
# Optimization Design for Sparse Planar Array in Satellite Communications
###### Abstract  
The antenna is one of the key components of satellite communication load. To address the evolving requirements of future satellite communication systems, the sparse planar array has become an important device for transmitting and receiving electromagnetic waves in emerging antenna systems. The advantages of this technology include low cost, low system complexity, and robust anti-interference ability, which have attracted widespread attention within the industry. In this paper, we investigate an optimization design of sparse planar arrays in satellite communication scenarios. Firstly, we introduce the mathematical foundation of the array antennas and establish the optimization design model of the sparse planar array. Secondly, we analyze and compare the impact of different array layout methods on the sparse planar array antenna pattern, and then introduce the latest design trend of array material design. Thirdly, we review some classical optimization methods for optimizing sparse planar arrays and the recent research advancements in promising and novel methods. Lastly, on the basis of the present research status, we propose three future research directions and two critical challenges for optimal design of sparse planar arrays in satellite communication scenarios, which can facilitate the development and realization of array technology under future B5G and 6G wireless networks.  
satellite communications; sparse planar array; array optimization design; metamaterial technology; reconfigurable smart antenna
# Game Approach to HDR-TS-PV Hybrid Power System Dispatching
## 1 Introduction
The existing coordinated dispatching models and payoff allocation mechanisms for multi-energy sources are not entirely suitable for \(HDR\) power stations. Accordingly, the coordinated operation model and payoff allocation strategy for \(HDR\) power stations require further research. Therefore, the major contributions of this paper are: (1) a new method for designing \(HDR\) power stations is presented to reduce the power fluctuations of \(PV\) plants and improve the reliability of the power grid; (2) a hybrid power system composed of \(HDR\), \(TS\), and \(PV\) plants is constructed, and the coordinated operational characteristics of \(HDR\) power stations in the hybrid power system are analyzed; (3) a game pattern with \(HDR\) power stations, \(TS\) power stations, and \(PV\) plants as players is proposed. The non-cooperative game's payoff function and the characteristic function of the cooperative game are then defined; and (4) the game dispatching models are simulated with the case of the Gonghe Basin of Qinghai. Finally, a sensitivity analysis of the two critical parameters of the allowed fluctuation rate, and the penalty coefficient is carried out. The remainder of this paper is organized as follows. The architecture of the \(HDR\)-\(TS\)-\(PV\) hybrid power system and characteristics of the \(HDR\) power station are given in Section 2. The \(HDR\)-\(TS\)-\(PV\) game model is proposed in Section 3. Section 4 simulates a case based on actual data of the Gonghe Basin. An in-depth discussion of the simulation results is carried out in Section 5. Conclusions and further developments are discussed in Section 6.
## WT1 Immunohistochemical Expression in Human Embryonal/Fetal and Neoplastic Tissues
### Wilms' Tumor  
[PERSON] tumor is a malignant embryonal neoplasm, also known as a nephroblastoma of pediatric age, resulting from a disturbance of the differentiation of nephrogenic blastematous cells, which replicates various stages of the developing kidneys [53; 54; 63; 64]. Microscopically, [PERSON] tumor is typically composed of three components: blastematous, mesenchymal (stromal) and epithelial [65; 66; 67]. Most [PERSON] tumors show all three components, but their proportions vary widely. Some tumors are biphasic, while others are monophasic. The blastematous component is extremely cellular and composed of small round-to-oval cells with scanty cytoplasm, dark nuclei and frequent mitotic figures, arranged in diffuse, nodular, cord-like (serpentine), or basaloid (with peripheral palisading) patterns. The stromal component is composed of spindle-shaped cells set in a myxoid stroma.  
Figure 1: Nuclear expression of the [PERSON] tumor gene (WT1) (_N-terminus_) in human metanephros (**A**), in gonadal stromal cells (**B**) and in the mesothelial cells covering the surface of the ovary (**B**) of the fetus of 11 weeks of gestational age. Cytoplasmic expression of WT1 (_N-terminus_) in myocardium (**C**) and in the skeletal cells (**D**) in a fetus of 22 weeks of gestational age.  
In most tumors, stromal differentiation, including smooth and skeletal muscle, bone and chondroid tissues, adipocyte tissue, or more rarely, neuroglia and mature ganglion cells, may be observed. Skeletal muscle in various stages of differentiation, including rhabdomyoblasts, represents the most common heterologous component [68; 69]. The epithelial component is composed of tubules, papillary and glomerular-like structures, which are closely reminiscent of normal nephrogenesis.  
There is not a single marker or panel of immunostaining that is diagnostic of [PERSON] tumor, but the immunohistochemical profile depends on the different tumor components examined. WT1 is certainly the most sensitive and specific marker for the diagnosis of [PERSON] tumor, with positivity in more than 90% of cases (Figure 2). It is expressed in the nuclei of primitive blastemal cells using antibodies directed both to the _C-terminal_ or _N-terminal_ portions of the protein, while it is absent in the differentiated epithelial and stromal elements. When a [PERSON] tumor is composed predominantly/exclusively of the blastematous component, it may be diagnostically challenging, especially when pathologists are dealing with small biopsies, and the differential diagnosis includes other small, round cell tumors (differential diagnosis with other small, round blue cell tumors-PNETs/Ewing sarcoma, neuroblastoma, rhabdomysocramas, clear cell sarcomas, synovial sarcomas and lymphomas). In this context, the demonstration of WT1 nuclear expression with antibodies directed against the _C-terminal_ portion of the protein (clone WT1C19) is helpful in confirming the diagnosis.
# Development of a Play-Tag Robot with Human-Robot Contact
## 1 Introduction  
In traditional robot development, robots are controlled to avoid contact with humans as much as possible for safety reasons [1]. Therefore, when humans and robots work in the same space, the problem is preventing contact and collisions while still facilitating the work [2]. This criterion also applies to humans in a typical environment; however, in some cases, humans may actively contact each other [3]. In recent years, robots that play with children have been developed [4; 5; 6; 7; 8; 9; 10]. When children play, they often contact each other. The play with contact (rough-and-tumble play) is known to be beneficial for children's development [11; 12; 13] Therefore, when a robot participates in the play, the robot should contact and be contacted by other players while ensuring safety.  
Studies of human-robot contact include research on detecting contact with controlled manipulators such as robotic arms [14] and controlling them in contact with humans [15; 16]. In both cases, the assumption is that the human comes into contact with a solid mechanism, such as a robotic arm, and is stationary. [PERSON] et al. developed a humanoid robot KASPER, which has tactile sensors for interacting with humans through tactile [17]. This robot is used to play with children with autism [7; 18]. In the scenario for using KASPER, the robot does not move. However, in games such as tag, each player moves and makes contact while moving. The RoboCup soccer involves such a task as an ultimate goal, but there is no human-robot contact in the current RoboCup soccer [19; 20].  
On the other hand, when robots participate in games that inherently involve contact, such as touch, the game is often played without actual contact for safety reasons. For example, in the tag game robot by [PERSON] et al. [21], the robot was regarded as touching a player when the robot and the player were close enough for safety reasons. The tag game system by [PERSON] et al. [22] extends human-to-human play, where the players areregarded to be touched when they are close enough. [PERSON] et al. designed a game played by robots for children with or without physical special needs [PERSON] et al. (2018). This game is to use robots to pick up balls and shoot them into a goal; however, the game is designed to avoid actual human-robot contact.  
Some robots that play games with humans make actual contact with humans; in [PERSON] et al.'s robot playing _\"Daruma-san ga koronda\"_([PERSON] et al., 2018), the robot extends its arm to touch the human while both human and robot are stationary. In this case, since both the human and the robot are stationary, the robot only needs to measure the distance from the human and extend its arm.  
This study aims to realize a function that touches the human while avoiding collision in a robot that plays tag with the human. For the robot to actually touch the human, it is necessary to consider the relationship between the arm for touch and the human and the strategy of disengaging from the human after touch.