esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Recent technology developments on low-power and low-rate wireless communication, micro-sensor, microprocessor hardware etc., have made wireless sensor networks (WSNs) one of the dominant research trends in the last few years. It can be potentially applied in target tracking, habit monitoring, environment observation, structural detection, physiological tele-monitoring and even drug administration, etc. [3][4][5][6][7]. To enable high performance of WSNs, there exists a number of challenges in research as well as in practice due to its wireless nature, node density, limited resources, low reliability of the sensor nodes, distributed system architecture and frequent mobility. These issues are different from those of classical wireless ad hoc networks [6][8]. The above characteristics result WSNs in an unreliable and unpredictable behavior. Therefore, Quality of Service (QoS) supporting such as data reliable transmission is actually as a big challenge as energy efficiency for WSNs.  
However, current research works on routing algorithms mostly focused on protocols that are energy aware to maximize the lifetime of network, scalable for large number of sensor nodes and tolerate to sensor damage and battery exhaustion. But there are many applications including real-time mobile target tracking in the battle environments and emergent event triggering in monitoring applications etc, which require not only energy-efficient but data-reliable routing. So the dynamics and loss behavior of wireless connectivity poses major challenges to the low-power radio transceivers found in WSNs and raises new issues that routing protocols must address.  
In this paper, a dynamic windows concept (\(m,k\)) is introduced to capture the historical link states and estimate link quality before routing decision making. A link quality estimation based routing estimation based routing protocol (LQER) protocol is designed, which creates a connectivity graph based on minimum hop count field and (\(m,k\)). Our proposed protocol considers both energy and link quality to avoid poor link connectivity and reduce the possibility of retransmissions. Therefore, the lifetime of WSNs can be prolonged and an improved data reliability is obtained.  
The remainder of this paper is organized as follows. Section 2 introduces some related work including typical routing protocols. In section 3, LQER protocol is designed in detail, which includes dynamic windows concept (\(m,k\)), link quality estimation based on (\(m,k\)), minimum hop field establishment and description of LQER Protocol. Section 4 does the simulation experiments based on WSNsim environment that is developed by us and evaluates the performance of LQER. Finally, we make some concluding remarks and outline some future work.
# Failure Mechanism of Multilayer Ceramic Capacitors under Transient High Impact
## 2 Experimental Study on MLCC Parameter Fluctuation Failure
### Transient Change of the Leakage Current  
The leakage current of a multilayer ceramic capacitor is another key performance evaluation parameter. During the impact, the leakage current of the ceramic capacitor also changes significantly, causing ignored energy loss. According to [PERSON] et al. (2018), the ceramic dielectric (BaTiO\({}_{3}\)) is not an absolutely ideal insulating material and has a piezoresistive effect. When the capacitor is charged, the electron penetrates through the dielectric layer and forms the leakage current. During the process of impact, the piezoresistive effect is evident, resulting in a sharp increase in the leakage current.  
In this study, both ends of the MLCC are connected to the electrochemical workstation. Real-time monitoring of the leakage current changes by chronopotentiometry mode. Under such a mode, a constant voltage is applied between the two ends. When the impact acceleration is applied to the MLCC via the Machete hammer, the transient leakage current change is recorded by the electrochemical workstation. The change in leakage current of the ceramic capacitor is closely related to its structure. Figure 4 shows the leakage current of multilayer ceramic capacitors with different specifications changed under different impacts. In the process of the experiment, the peak value of the impulse acceleration increases gradually, and the leakage current of all types of capacitors increases suddenly, which is a universal phenomenon. Moreover, the change in leakage current can reach values of up to 1.2 mA (absolute change), so it cannot be ignored. In addition, the relationship between the leakage current change and impact acceleration rate is not linear; the amount of change increases sharply after the threshold (4000 g) is exceeded. This indicates that the higher the acceleration the penetration fuze is subjected to, the more serious the reliability problem of an increased leakage current can happen. Besides, the greater the rated capacity and withstand voltage, the greater the increase in leakage current. Note that the rated capacity has a greater influence than the withstand voltage on the leakage current fluctuation.
# Improving Structural Power Content Analysis Robustness for Satellite Navigation Applications +
## 5 Results  
In the previous paragraphs, different jammer types and their effect on the performance of the SPCA method were evaluated. Additionally, two filter techniques were suggested to improve the method's resilience against jamming. In this section, the suggested filter combinations are examined with respect to (combined) jamming and spoofing scenarios to evaluate the overall performance of the modified method.  
To start with the performance of spoofing detection, which is the core functionality of the algorithm, the achieved probability of (spoofing) detection \(P_{D}\) was computed as a function of the false alarm rate \(P_{FA}\). Note that this was the achieved false alarm rate of the method, which in the case of a clean scenario was approximately equal to the desired false alarm rate. These results are shown in Figure 2(a). Then, for all filter combinations, a jamming signal was added, after which the test was repeated. The results for a scenario with an AM jammer with a JSR of 13 dB are shown in Figure 2(b).  
From these results, it can be stated that for spoofing detection the original filter combination yields the highest probability of spoofing detection for a given probability of false alarms. The jamming resistance, however, can be seen in Figure 2(b); for the filter combinations without the DC notch filter, data appear to be missing in the low-false-alarm regions. This is due to the fact that these false alarm rates cannot be satisfied under the  
Figure 3: A spoofing detection performance analysis for all the suggested filter combinations in (**a**) a clean scenario and in (**b**) a scenario where an AM jammer with a JSR of 13 dB is present.  
Figure 2: A comparison between the SPCA results for different filter combinations in a scenario with an AM jammer with a JSR of 13 dB.  
given jamming conditions. These results show that the comb noise filter yields a better spoofing detection performance than the notch noise filter. Additionally, adding the DC notch filter slightly reduces this performance, but greatly increases the jamming resistance of the algorithm. When used in combination with the DC notch filter, the notch noise filter only adds slightly to the jamming resistance with respect to the comb noise filter.
# Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications
## 5 Discussion
The effect of SE as an external variable is the most studied in the TAM works we analyzed. Only one category out of seven didn't report the relationship between SE and PU or PEOU, namely, studies comparing a set of technologies. In all the other research topics, SE showed a significantly strong influence on the perception of how ease could be to use technology as [PERSON] and [PERSON] [138] suggested. For PU, the predictive power of SE was strong when moderating variables such as gender and age were being contemplated. All the other categories mentioned a medium effect of SE in PU. As can be expected, the SQ is particularly relevant for studies analyzing the acceptance of a system or service. If a platform does not run smoothly, users may lose interest in using it, and their perception of ease of use will decrease, as well as their satisfaction [139; 140]. Our study confirmed the results obtained by [PERSON] et al. [131], pointing out that SQ has a substantial impact on PU and PEOU of platforms and systems. In contrast, the theoretical studies category reported a minimum effect of SQ on both TAM's determinants. The logic behind SN is that human behavior is somehow affected by the opinions of the individuals' closer social spheres. In some cases, people may use a technology based on others' perceptions about the convenience of the use over his or her own emotions and beliefs [19]. Our results suggest that social pressure can have a more significant influence on users' perceptions of usefulness than in PEOU. Academic works comparing the acceptance of a set of technologies reported that users tend to perceive innovations as more useful, based on the recommendations of individuals closest to them. In those cases, SN seems to have a strong predictive power on PU. Theoretical studies and researches investigating the acceptance of methodologies, devices, or systems, showed a medium explanatory impact of SN in PU. When innovations are considered a bunch of technologies, SN had a low effect on PU. Concerning PEOU, theoretical studies registered a moderate effect of SN on this TAM determinant, as well as studies assessing the acceptance of systems. When the acceptance of a methodology is under analysis, SN seems to have little effect on PEOU. The main findings and correlations are summarized in Figure 8. Only variables reporting a more significant influence in the two TAM's beliefs are included for each of the seven study categories. Common factors used in TAM extensions in the fields of interest are also listed. Figure 8: Summary of findings. Based on the previous analysis, the TAM extension that better fits the context of the e-learning tool FARMER 4.0. is depicted in Figure 9. The validation of the proposed model corresponds to the subsequent phase of the present study and will be developed in the near future.
## 2 Materials and Methods
### Data
This situation is also evident in the total equity since some Portuguese firms present negative equity, it means, liabilities are not only to finance the firm's assets (investment), but also the negative equity \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Region** & **\#** & **Total Assets** & **Total Equity** & **Net Income** & **Sales** & **N. Employees** & **Age** \\ \hline
**Panel A: Portugal** & & & & & & & \\ North & 17 & 111,518,741 & 17,984,099 & 767,795 & 10,891,640 & 48.02 & 9.03 \\ Center & 8 & 82,207,292 & 15,196,040 & 565,915 & 8,002,019 & 36.68 & 10.83 \\ Lisbon & 16 & 57,432,432 & 15,867,416 & 1,009,200 & 7,600,640 & 69.82 & 10.76 \\ Alentejo & 3 & 178,214 & \(-\)91,414 & \(-\)11,042 & 12,611 & 0.33 & 15.50 \\ Algarve & 1 & 100,821 & 72,060 & 22,192 & 118,970 & 3.00 & 6.50 \\ Azores & 1 & 1,968,167 & 816,207 & \(-\)36,914 & 551,971 & 17.00 & 22.50 \\ Madeira & 1 & 4599 & \(-\)11,243 & \(-\)3451 & 8905 & 1.00 & 1.00 \\ \hline
**Total sample** & **47** & **74,188,436** & **14,458,501** & **711,416** & **7,908,158** & **47.49** & **10.45** \\ \hline
**Panel B: Spain** & & & & & & & \\ Andalusia & 24 & 580,223 & 281,359 & 44,833 & 507,186 & 7.18 & 10.32 \\ Aragon & 12 & 9,485,054 & 3,349,859 & 147,887 & 1,673,319 & 8.43 & 10.08 \\ Asaturias & 2 & 2,107,223 & 1,069,929 & 8709 & 895,479 & 9.50 & 18.00 \\ Balearic Islands & 4 & 946,759 & 580,358 & 47,143 & 496,308 & 7.47 & 16.75 \\ Canary Islands & 8 & 715,141 & 176,182 & 73,036 & 1,473,822 & 29.12 & 8.57 \\ Cantabria & 1 & 45,427 & 3315 & 115 & 138,661 & 3.00 & 0.50 \\ Castilla y Leon & 10 & 757,523 & 391,654 & 63,637 & 534,787 & 2.89 & 11.00 \\ Castilla-la-Mancha & 7 & 1,228,147 & 1,061,821 & 55,245 & 782,639 & 9.46 & 11.30 \\ Catalonia & 31 & 1,212,260 & 625,025 & 75,557 & 1,443,074 & 15.05 & 18.50 \\ Valencian community & 20 & 4,447,564 & 2,000,531 & 82,985 & 3,569,681 & 50.19 & 16.22 \\ Extremadura & 2 & 2,627,736 & 622,003 & 53,765 & 3,141,402 & 47.13 & 16.50 \\ Galicia & 13 & 7,039,792 & 3,317,971 & 8704 & 1,526,122 & 8.08 & 11.14 \\ La Rioja & 3 & 1,826,621 & 1,124,287 & 169,839 & 2,368,906 & 20.33 & 6.17 \\ Madrid & 18 & 28,726,264 & 16,388,426 & 1,966,768 & 8,513,969 & 67.76 & 19.78 \\ Murcia & 8 & 357,438 & 200,769 & 28,929 & 323,713 & 4.24 & 10.07 \\ Navarra & 4 & 1,329,890 & 190,334 & 35,489 & 956,221 & 11.75 & 14.50 \\ Basque country & 6 & 631,995 & 254,300 & 36,806 & 889,929 & 10.13 & 17.83 \\ \hline
**Total sample** & **173** & **5,353,193** & **2,740,192** & **262,525** & **2,147,424** & **22.50** & **14.10** \\ \hline \hline \end{tabular} Total assets, total equity, net income, and sales are in euros. Number of employees and age are in number. Source: IBM SPSS version 27.  
\end{table} 
Table 2: Mean values of main accounting information (annual data) per region. that results from losses of previous years, and in Spain, there is no evidence of that problem. Finally, Portuguese firms employ in mean more people than Spanish ones.
# Use of Indoor Location Technologies in Healthcare Contexts: A Scoping Review
## 3 Results
### Limitations and Risks  
A significant portion of the studies did not explicitly address the main limitations and risks related to technology use, instead highlighting recurring challenges identified in the literature, which limits the analysis of this topic. However, the most cited difficulty was the lack of precision and sensitivity of the technologies or their intrinsic limitations [9, 27, 31, 55, 58, 62, 66, 68]. Also, the lack of infrastructure (physical or technological) in locations where the technologies were applied and signal interference from medical equipment, materials such as metal or liquids, and even between tags was reported in some articles [9, 13, 27, 62, 65, 67, 69, 70, 71].  
Implementation and hardware costs were obstacles reported [9, 44, 49, 55, 60, 61, 65, 72, 73]. However, these focus primarily on implementation and do not discuss maintenance costs. User acceptance [41, 49, 59], both by patients and healthcare staff, and the need for adequate training were described as limitations in some references [62, 63, 74], in addition to other user-related issues, including the Hawthorne effect [43, 56, 75], limited sample space and time [48, 56, 58, 60, 76], and experimental or controlled environments impacting the technology's actual effectiveness.  
Lastly, articles mentioned difficulties in processing and analysing the data collected and privacy and data security risks [44, 60, 62, 65, 67, 73, 77]. A lack of comparison with other geolocation methods was also cited as a limitation in two articles [50, 78] and two papers noted that the lack of patient satisfaction evaluation was a limitation [45, 46].
## 6 Existing Routing Protocols
### SPIN (Sensor Protocols for Information via Negotiation)  
SPIN [16,17] is a family of adaptive protocols that use data negotiation and resource-adaptive algorithms. SPIN is a data centric routing protocol. It assumes:  
1. all nodes in the network are base stations.
2. nodes in close proximity have similar data.  
The key idea behind SPIN is to name the data using high-level descriptors or meta-data. Since all nodes can be assumed as base stations all information is broadcasted to each node in the network. So user can query to any node and can get the information immediately. Nodes in this network use a high level name to describe their collected data called meta-data. Figure 5 shows how SPIN works.  
Before transmission, meta-data are exchanged among sensors nodes (meta-data negotiation) via a data advertisement procedure, thus avoiding transmission of redundant data in the network. After receiving the data each node advertises it to its neighbors and interested neighbors get this data by  
Figure 4: Chaining in PEGASIS.  
Figure 5: Data Transmission in SPIN.  
sending a request message. The format of this meta-data is not specified in SPIN and it depends on the used applications. This meta-data negotiation solves the classic problem of flooding and thus it achieves energy efficiency. SPIN uses three types of messages: ADV, REQ, and DATA for communication with each other. ADV is used for adverting new data, REQ is used for requesting for data and DATA is the actual message. According to this protocol first a node gets some new data and the node wants to distribute that data throughout the network, so it broadcasts an ADV message containing meta-data. The interested nodes request that data by sending a REQ message and the data is sent to the requesting nodes.  
The neighboring node repeats this process until the entire network gets the new data. The SPIN protocols include many other protocols. The main two protocols are SPIN-1 and SPIN-2. These two protocols incorporate negotiation before transmitting data so that only useful information will be transferred. Each node has its own resource manager that keeps track of resource consumption. The SPIN-1 protocol is a 3-stage protocol, as described above. SPIN-2 is an extension of SPIN-1, which incorporates threshold-based resource awareness mechanism in addition to negotiation. When energy in the nodes is abundant, SPIN-2 communicates using the 3-stage protocol of SPIN-1.  
One of the advantages of SPIN is that topological changes are localized since each node only needs to know its single-hop neighbors. SPIN provides much more energy savings than flooding and meta-data negotiation almost halves the redundant data. However, SPINs data advertisement mechanism cannot guarantee the delivery of data. To see this, consider the application of intrusion detection where data should be reliably reported over periodic intervals and assume that nodes interested in the data are located far away from the source node and the nodes between source and destination nodes are not interested in that data, such data will not be delivered to the destination at all.
## 3 Results  
### Plasma Diagnostics and Plasma-Activated Water (PAW) Characteristics  
The emission spectrum of the plasma from SDBD was measured using optical emission spectroscopy (OES). The result shows the intensive molecular spectra of a nitrogen second positive system (N\({}_{2}\) SPS) and nitrogen first negative (N\({}_{2}\) FNS) in the 300-400 nm region during the air discharge. An OH radical peak (309 nm) was not observed; thus, the air discharge may not produce OH radicals (Figure 1). Because N\({}_{2}\) SPS and N\({}_{2}\) FNS were detected by OES, it is estimated that a large amount of nitrogen ions will be generated by this plasma system. When these NO\({}_{x}\) react with H\({}_{2}\)O, they become ionized into NO2 and NO3, which were detected in the PAW. The physical and chemical properties of DW and the PAW were analyzed (see the Materials and Methods section), and the results are presented in Table 1. To produce the proper PAW for _Arabidopsis_, plasma-activated water samples were generated using five different PAW treatment times and used in the experiment. The plasma-activated water samples in this paper are denoted as PAW5 time in minutes (min), PAW7, PAW12, PAW19 and PAW40 with the number indicating the plasma treatment time.  
The result showed that the pH decreased (increased acidity) as the PAW processing time was extended due to the change in the ion content of the water. Furthermore, we confirmed that a small amount of nitrite was detected in the PAW, whereas the concentration of nitrate ions and their conductivity dramatically increased in proportion to the plasma treatment time in the PAW. In the case of hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)), it was not detected in the DW, but it increased slightly depending on the plasma treatment time (Table 1).
## 3 Methodology  
### Description of the GIS-Based DRASTIC Model Framework  
In this study, a GIS-based DRASTIC model was employed to assess the vulnerability of groundwater in Tangshan City, a coastal area in China. The DRASTIC model, initially developed by the US Environmental Protection Agency (EPA) to evaluate groundwater pollution potential across the United States [35], considers intrinsic vulnerability based on hydrogeological characteristics while disregarding the specific contaminants. The use of a GIS-model interface facilitates data input, and the GIS can also serve as a common platform for transferring information between different examples of software. By combining various data sets within the GIS framework, thematic maps can be generated for utilization by the DRASTIC model. Furthermore, the GIS enables the conversion of these maps into raster mode, dividing them into pixels with dimensions of 300 m \(\times\) 300 m. Each pixel is assigned a numerical value corresponding to the resulting grid, which serves as a basis for the seven parameters of the DRASTIC model, as detailed in the following equation:  
\[DRASTIC_{\text{index}}=W_{D}R_{D}+W_{R}R_{R}+W_{A}R_{A}+W_{S}R_{S}+W_{T}R_{T}+W _{I}R_{I}+W_{C}R_{C} \tag{1}\]  
where, the parameters in Equation (1) include the following: depth of groundwater (D), vertical net recharge of groundwater (R), aquifer thickness of media (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C).  
Consequently, vulnerability is calculated at a high resolution for each individual pixel. The GIS is further utilized to overlay the seven thematic maps, thereby generating a groundwater vulnerability map. The DRASTIC index computation involves assigning weights (W) to each parameter and using the assigned values (R).
# Compliant Detachment of Wall-Climbing Robot Unaffected by Adhesion State
## 2 Strategy of Compliant Detachment
### Online Impedance Adaptation Controller
To realize impedance adaptation during peeling, an online impedance adaptive controller (OIAC) [24] is used to produce online variable compliant joint motions for adhesive attachment and detachment. This controller has been applied to finger and elbow exoskeletons, leading to stable variable compliant joint motions [26; 27]. Taking a 3-DOF limb, for example, the torque of all joints is controlled using the equation:  
\[\tau(t)=F(t)+K(t)e(t)+D(t)\dot{e}(t), \tag{6}\]  
where \(\tau(t)\in\mathbb{R}^{3\times 1}\) is the output torque of joint 1-3, \(F(t)\in\mathbb{R}^{3\times 1}\) is the online adjustment bias term, and \(K(t)\in\mathbb{R}^{3\times 3}\) and \(D(t)\in\mathbb{R}^{3\times 3}\) are time-varying impedance parameters adjusted online. The position, velocity, tracking error \((e(t),e(t),\varepsilon(t)\in\mathbb{R}^{3\times 1})\) are given by:  
\[e(t)=q_{d}(t)-q(t),\dot{e}(t)=\dot{q}_{d}(t)-\dot{q}(t),\varepsilon(t)=e(t)+ \dot{\beta}e(t), \tag{7}\]  
where \(q(t)\in\mathbb{R}^{3\times 1}\) is the current position of the joint, \(q_{d}(t)\in\mathbb{R}^{3\times 1}\) is the target position, and \(\beta\) is the tracking factor in tracking error to adjust the proportion of the damping term. The bias term and impedance parameters are given as follows:  
\[F(t)=a^{-1}(1+b\|\varepsilon(t)\|^{2})\varepsilon(t),K(t)=F(t)e^{T}(t),D(t)=F(t )\dot{e}^{T}(t), \tag{8}\]  
where the parameters \(a,b\in\mathbb{R}^{3\times 3}\) were chosen to perform proper online impedance adaptation, thereby avoiding motor torque saturation. It has been shown that online impedance adaptation control can prevent motor dysfunction, which may result from conventional impedance control [26]. The adaptive law of OIAC over state-of-arts are provided in Appendix B. With OIAC, the robot can converge the direction of the detachment force to the tangential forward. Besides, because all joints have impedance characteristics, the limb joints in the stance phase can absorb an instantaneous impact, thus reducing the influence of various forces, including the detachment instantaneous force, on adhesion in the stance phase.