esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background and Related Work
### Emergency Management in Smart Cities  
Emergency management in smart cities provides valuable insights and foundational strategies that can be adapted and applied to the specific context of smart campuses. The integration of advanced technologies into emergency management systems is a critical aspect of modern smart cities. [PERSON] et al. [31] present an integrated resilience system for smart cities that enhances disaster recovery by linking interconnected critical infrastructures. Using a data-driven approach and artificial intelligence, the system aims to reduce cascading failures and rapidly restore infrastructure performance. It provides a decision support system that improves disaster preparedness, response, and recovery by leveraging the interconnections between critical infrastructures. The approach is illustrated through a case study of Lisbon, Portugal.  
Building on this, the concept of smart cities often focuses on enhancing community life through continuous collaboration among citizens, services, and organizations. In this context, emergency management becomes crucial. [PERSON] et al. [32] discuss the redesign of an Emergency Notification (EN) application within smart cities, focusing on enhancing community collaboration and emergency management. The redesign incorporates gamification and Self-Determination Theory (SDT) principles to improve user experience and encourage civic participation. By connecting citizens, services, and organizations, the application aims to reduce emergency risks and response times. The effectiveness of the new design was assessed through an exploratory focus group with citizens and practitioners.  
Moreover, [PERSON] et al. [33] proposed a framework that supports the creative design of emergency management scenarios by automatically generating and organizing conceptual models, called \"mini-stories\". These mini-stories, derived using semantics-based techniques, help in modeling and simulating emergency situations, particularly in smart cities. The framework integrates structural, domain, and contextual knowledge to assist in creating detailed scenarios, addressing the complexity of smart city ecosystems. A software application was developed to facilitate this process, and the approach was validated through experiments with city planners.  
Finally, the development of smart city digital twins is another innovative approach to disaster management. [PERSON] and [PERSON] [34] explored the use of digital twins in smart cities (SCDT) for enhancing community disaster management. They proposed and tested a conceptual model of an SCDT tailored for disaster scenarios and identified key challenges and mitigation strategies related to SCDT development. The study emphasizes the importance of focusing on information loops rather than individual components. Key contributions include a framework for SCDT in disaster management, a detailed conceptual model, and a discussion of development and deployment issues.
## 1 Introduction
The literature presenting the impact of different DO sensor fault types on the WWTP energy, effluent water quality and GHG emissions performance is still lacking, although they have become of very high interest. To the best of the authors' knowledge, no WWTP single study of fault detection has been conducted on six different sensor fault types combined with the assessment of associated environmental and economic impact. The goal of the present paper is to use multivariate statistical methods to construct a fault diagnosis method for the wastewater treatment facility. This research was intended to explore efficient diagnostic ways for specific defects caused by faulty DO sensors and to assess the environmental and cost impact of the faults. Six different fault types were considered: bias, drift, wrong gain, loss of accuracy, fixed value or complete failure. The original contribution of the paper addresses the comprehensive and comparative disclosure of the DO sensor fault types and evaluation of the fault identification benefits for the automatically controlled treatment plant. Furthermore, for the municipal WWTP case study, the energy costs and environmental impact on the treatment plant performance were assessed for the various defects of the DO sensor. The structure of the present work presents (i) the dynamic model of the WWTP used for simulations, (ii) the basic theory underpinning the FDA fault-diagnosis methodology for the identification of the sensors' faults and (iii) the presentation of the equations used to compute the GHGs released by the fault affected WWTP process; then, the (iv) results and discussions of the performance are obtained by the FDA approach and the environmental and economic study, and the paper ends with (v) the conclusions of the research for improving the performance of the case study WWTP.
_applied sciences_  
_Article_  
**Innovative Protocols for Determining the Non-Reactive Agility of Female Basketball Players Based on Familiarization and Validity Tests**  
**[PERSON]**\({}^{\text{\textregistered}}\), [PERSON]**\({}^{\text{\textregistered}}\), [PERSON]**\({}^{\text{\textregistered}}\)**\({}^{\text{\textregistered}}\), [PERSON]**\({}^{\text{\textregistered}}\), [PERSON]**\({}^{\text{\textregistered},\ast}\)**, [PERSON]**\({}^{\text{\textregistered}}\), [PERSON]**\({}^{\text{\textregistered}}\)**\({}^{\text{\textregistered}}\) and [PERSON]**\({}^{\text{\textregistered}}\)  
a significant component of many activities and numerous sports [6; 7; 8]. Analysis of movements in elite women's basketball shows that activity changes are performed every 2.56 s, and that during the game, basketball players perform an average of 576 \(\pm\) 110 movements, in contrast to college female basketball players, who have a greater number of movements and a longer time to change activities [9; 10]. At the same time, the analysis showed that a very important role in elite women's basketball is represented by short linear sprints of 1-5 m without the ball that are often repeated (57% of the total number of sprints), as well as that 52% of the total performed sprints involve changing the direction of movement, which indicates the importance of agility development in female basketball players [10]. Agility as a multidimensional ability can be manifested through pre-planned and adopted movements as non-reactive agility (offensive or defensive movements trained through training), but also in sports situations as reactive agility when movement structures are not pre-planned but mainly depend on external stimuli and cognitive abilities of the player [1; 11; 12; 13; 14]. Bearing in mind that agility is a decision-making process, that is, including both the ability to plan and perform precise movements suitable for predetermined (previously practiced) or unplanned stimuli [11], there is great interest in sports theory and practice for the development of appropriate tests for the diagnosis of this complex ability [10]. Authors working in this specific field [1; 11] are rejecting the possibility of using usual and standardized tests with the intention of creating new tests of agility while using a new generation of instruments such as the FitLight TrainerTM system, and are working under the assumption that they will provide valid and reliable measures of agility. They have designed tests of reactive and non-reactive agility. To use them more frequently for diagnosis by professional coaches working with female basketball players, as well as by researchers in the field of sports, further work on familiarization protocols and the validity of these tests is becoming imperative.  
Based on the aforementioned, this study aimed to analyze a familiarization protocol and to determine the constructive validity of four structurally different tests of non-reactive agility (a frontal agility test, lateral agility test, semicircular agility test, and universal agility test), on a sample of professional female basketball players.
## 2 Nonlinear Modeling of the Pump Turbine  
The most common method for the pump turbine nonlinear modeling is through the complete characteristic curves [14]. The main idea of the nonlinear modeling based on complete curves is to first extract certain discrete data points from the practical curves, and then the extracted data points are fitted or extended to obtain the modeling curves [14]. The mathematical model of the flow and moment characteristics to express the pump turbine characteristics is as follows [2].  
\[\left\{\begin{array}{l}M_{11}=f_{M}(a,N_{11})\\ Q_{11}=f_{Q}(a,N_{11})\end{array}\right. \tag{1}\]  
where \(M_{11}\) represents the unit moment, \(Q_{11}\) denotes the unit flow, \(N_{11}\) is the unit speed, and \(a\) denotes the guide vane opening. In this study, the pump turbine complete characteristic curves of a hydropower station in China are employed as a case study. The practical complete characteristic curves are shown in Figure 1 as follows [2].  
As can be seen in Figure 1, the original completed curves still have a significant twist curl when the unit speed is bigger than 80, which causes the multi-value phenomenon in the \"S\" characteristic area. For example, three flow (Figure 1a) and moment (Figure 1b) data points appear when the value of unit speed is 90 r/min and the value of the guide vane opening is 10. The interpolation error is large and the derivative is discontinuous when multiple values exist, which may cause an iteration error to occur in the PTGS. To avoid the multi-value phenomenon of the original curves, this study introducesthe improved Suter transformation [20] to pre-process the original complete curves. The original flow and moment characteristic curves are changed to _WH_ and _WM_ curves, respectively, through the improved Suter transformation. The converting equations of the improved Suter transformation are expressed as follows.  
\[\left\{\begin{array}{l}\begin{array}{l}WH(x,y)=\frac{h}{a^{2}+q^{2}+C_{h}h}(y +C_{y})^{2}\\ WM(x,y)=\frac{(m+s_{2}h)}{a^{2}+q^{2}+C_{h}h}(y+C_{y})^{2}\\ x=\arctan\left[(q+s_{1}\sqrt{h})/a\right]\ \ \mathrm{a}\geq 0\\ x=\pi+\arctan\left[(q+s_{1}\sqrt{h})/a\right]\ \ \mathrm{a}<0\end{array}\right. \tag{2}\]  
where \(\mathrm{a}\), \(q\), \(h\), and \(m\) denote the relative speed, relative flow, relative water head, and relative moment, respectively, \(x\) and \(y\) denote the relative flow angle and relative opening, respectively. \(s_{2}>|M_{11\mathrm{max}}|/M_{11\mathrm{r}}\), \(s_{1}=0.5\)-\(1.2\), \(C_{y}=0.1\)-\(0.3\), and \(C_{h}=0.4\)-\(0.6\). The _WH_(_x_,_y_) and _WM_(_x_,_y_) curves based on an improved Suter transformation are given in Figure 2 as follows [2].  
Figure 1: The characteristic curves of a pump turbine under different openings. **(a)** Flow characteristic curve and **(b)** moment characteristic curve.  
Figure 2: WH and WM characteristic curves based on improved Suter transformation under different relative speed.
## 1 Reduced-Complexity Approaches for Performance Improvement in MIMO Systems  
A first group of three papers concerns MIMO systems, in particular addressing the problem of improving the performance through the additional degrees of freedom while reducing the complexity of massive systems, by acting on different aspects.  
The paper, \"Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems\", by [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] [7] addresses the problem of the increasing demand for data rate (high throughput) in modern wireless communication systems, considering MIMO systems. In particular, to overcome the difficulty of implementing massive number of antennas at base stations, an adaptive precoder is proposed which provides high throughput and bit error rate (BER) performances in multi-user MIMO downlink systems with a practical antenna array (up to 16 elements).  
A second contribution towards the simplification of massive MIMO systems is provided in the paper, \"Energy-Efficient Hybrid Beamforming with Variable and Constant Phase Shifters\", by [PERSON] and [PERSON] [8]. The authors propose a novel partially connected hybrid beamforming (PC-HBF) architecture, which employs variable phase shifters (VPSs) and constant phase shifters (CPSs) for analog beamforming to harness the potential of these two types of phase shifters. Since exact sum rate optimization is intractable, especially in massive MIMO systems, a reduced-complexity, near-optimal greedy algorithm is proposed. Results show that by optimally combining VPSs and CPSs, the proposed architecture achieves performance close to that of the VPS-based PC-HBF architecture, with higher energy efficiency than the CPS-based fully connected HBF scheme.  
A third paper, \"Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems\", by [PERSON] and [PERSON] [9], proposes an adaptive threshold-aided K-best sphere decoding (AKSD) algorithm for large MIMO systems. A suitable strategy is proposed to reduce the complexity in visiting the nodes of the decoding tree, compared to the conventional K-best sphere decoding (KSD). Results show that the proposed AKSD provides nearly the same BER performance as the conventional KSD scheme while achieving a significant reduction in the average number of visited nodes, especially at high signal-to-noise ratios (SNRs).
## 7 Conclusions  
This article reviews various identity management systems based on both centralised and decentralised models. A thorough comparison of the most prominent models of both systems on the basis of scalability, reliability, security, adaptability, and cost is conducted. The analysis revealed that both the systems have some advantages and disadvantages. The organizations need to make informed trade-offs between scalability, cost-effectiveness, security, and complexity, based on their requirements.  
Currently, centralised systems, which have been used for decades for authentication and identity management, are the preferred choice as they provide both organizations and users ease of setup, management, and cost effectiveness. These systems handle large-scale deployments swiftly without the need for much changes in the existing infrastructure. Additionally, centralised systems have adapted to modern-day threats by implementing MFA and encrypted sessions which add complexity for attackers.  
On the other hand, decentralised systems address the shortcomings of the centralised systems. Its innovative approach to distribute the control of identity management in the hands of user and other participants, making the system secure and transparent. However, it faces a huge setback because of its complex architecture, which also needs a huge investment for setup and maintenance. There is a need for specialists in this field to handle these operational challenges. Industries like healthcare, finance, and government, which operate and store identity data and require high levels of security and privacy, can benefit from a decentralised approach. Blockchain scalability solutions like sharding and making use of the layer-two approach could further reduce the operations cost and increase performance and overall efficiency of the decentralised systems.
###### Abstract  
Miniaturized flexible microelectrode arrays are desirable for small-area surface electromyography (sEMG) to detect the electrical activity generated by muscles in a specific area of the body. Here, we present a flexible 8-channel microelectrode array with electrodes of diameter 150-300 \(\upmu\)m for small-area sEMG recordings. The microelectrode arrays based on a flexible Parylene C substrate recorded the sEMG signals from a curved skin surface with a maximum signal-to-noise ratio (SNR) of 21.4 dB. The sEMG signals recorded from a small area of 17671-59325 \(\upmu\)m\({}^{2}\) showed a clear distinction between the signal and noise. Further, the sEMG data were analyzed in the frequency domain by converting the signals via fast Fourier transform (FFT), and it was verified that the proposed microelectrode could reliably record multichannel sEMGs over a small area. Moreover, a maximum voluntary contraction (MVC) experiment was performed to confirm the recording capability of the microelectrode array, which showed consistency with the previous reports. Finally, we demonstrated the effects of the electrode size by comparing the results for two different electrode sizes. When the electrode size was increased 3.37 times, the root-mean-square value of the amplitude (V\({}_{\text{rms}}\)) increased 2.64 times, consequently increasing the SNR from 16.9 to 21.4 dB. This study demonstrates the expanded utility of Parylene-based flexible microelectrode arrays.  
microelectrode; electromyography; electrode size; Parylene; surface EMG Article
# Strategies for Deploying a Sensor Network to Explore Planetary Lava Tubes
## 1 Introduction
### Robotics for Exploring Rugged Environments
For mobility, SphereX can perform unconventional mobility in the form of ballistic hopping and rolling with the help of a hybrid mobility system comprising of a single-thruster miniaturized propulsion system  
Figure 3: (**a**) Artistic view of SphereX robots cooperatively exploring underground pit on the Moon; (**b**) Preliminary 3D CAD model of SphereX. and an Attitude Determination and Control (ADCS) System. Due to reduced traction on low-gravity environments, hopping mobility has an advantage over wheeled and rolling mobility as the surface interaction time is minimized. Moreover, a robot performing hopping mobility can overcome large obstacles much higher than the robot itself compared to wheeled and rolling mobility. Comparatively speaking, hopping mobility has advantages over wheeled/rolling mobility but at the expense of higher energy consumption. However, it has a definite advantage while exploring rugged environments as robots with wheeled/rolling mobility may very easily get stuck. Navigation is performed using the onboard 3D LiDAR, which maps the environment and autonomously generates trajectories. Once a SphereX robot is on the ground, the onboard cameras would take precise, high-resolution panoramic and stereo panoramic images. Furthermore, these images may be used for mission science and public outreach. Stereo video generated during flight can be post-processed to be viewable using VR (Virtual Reality) headsets, giving the public and mission planners the impression of being on site. The feasibility of successfully exploring a cave or a lava tube depends on an architecture where multiple SphereX robots work collaboratively for navigation and mapping, performing science experiments, and communicating data to and back from a base station. Due to the physical structure of caves and lava tubes, maintaining a direct line-of-sight link from a base station outside to robots inside the caves is nearly impossible. As a result, the robots need to strategically place themselves much like a bucket-brigade and pass information from one to their neighbor and eventually to the base station. A robot team forming a communications bucket-brigade can also be used to transmit power wirelessly using lasers from the base station to the robots inside the cave.
## 4 Results and Discussion
### Comparison of Natural Gas and Hydrogen
#### 4.2.3 Surrounding Rock Temperatures at Varying Distances from the Cavity  
As illustrated in Figure 8a, three monitoring points are established at varying horizontal distances from the cavity, designated as A, B, and C, in an order from the nearest to farthest. The temperature variations at these horizontal monitoring points during the injection and withdrawal operations are depicted in Figure 8b. The temperature of the surrounding rock changes in accordance with the temperature of the gas within the cavity during the injection and withdrawal cycle. As the distance from the cavity increases, the amplitude of temperature change in the surrounding rock diminishes. For the same monitoring point, the temperature of the surrounding rock when storing hydrogen is higher than that when storing natural gas. Additionally, the rates of temperature increase and decrease are more pronounced for hydrogen storage compared to natural gas, indicating a more significant thermal exchange effect between hydrogen and the surrounding rock.  
Figure 8: Horizontal monitoring point setting and temperature variations.  
Figure 6: Variation in wellbore pressure over a three-year injection–withdrawal cycle.  
Figure 7: Variation in wellbore temperature over a three-year injection–withdrawal cycle.
# Network Diffusion Algorithms and Simulators in IoT and Space IoT: A Systematic Review
## 4 Analysis
### Analysis of Research Question 4: Network Architecture
#### 4.3.4 Dynamicity of Networks  
Dynamicity refers to the changes in node connectivity over time, which is common in mobile IoT devices or networks where nodes frequently join, leave, or change status.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Topology** & **Impact on Diffusion** & **Challenges** \\ \hline Random Graph & Promotes unpredictable diffusion paths; useful in decentralized IoT. & Higher propagation delays; inefficient for structured IoT. \\ \hline Scale-Free Networks & Fast diffusion via hubs; applicable to social-driven IoT networks. & Vulnerable to targeted failures at hubs. \\ \hline Small-World Networks & Efficient diffusion due to short paths; suited for time-sensitive IoT applications. & Scalability issues in Space IoT. \\ \hline Mesh Networks & Reliable and redundant diffusion paths; ideal for critical IoT infrastructure. & Increased overhead and complexity in large-scale IoT. \\ \hline Tree Networks & Hierarchical diffusion; common in sensor networks. & Single points of failure hinder resilience. \\ \hline Hybrid Networks & Optimized for performance, combining benefits of multiple topologies. & High complexity in deployment and maintenance. \\ \hline \hline \end{tabular}
\end{table}
Table 10: Impact of network topologies on diffusion in IoT.  
Static Networks: Topologies remain unchanged, making it simpler to implement diffusion algorithms, though they do not accurately represent most real-world IoT networks.  
Dynamic Networks: Devices frequently change positions or status. Diffusion algorithms must be flexible and adaptive to handle these changes, which increases complexity but improves realism.  
Example: In dynamic sensor networks, where nodes are mobile, algorithms need to adapt to topology updates, improving efficiency but complicating the diffusion process if changes occur too frequently.