esa-sceva/satcom-chunk-collection huggingface dataset:
# Telescopic Network of Zhulong for Orbit Determination and Prediction of Space Objects
## 2 Data and Methods
### CPF Data
position \(\stackrel{{\rightharpoonup}}{{\mathbf{R}}}_{t}= \begin{bmatrix}X_{t}\\ Y_{t}\\ Z_{t}\end{bmatrix} \), the right ascension (\(\varnothing_{r}\)) of the space object, declination (\(\delta_{r}\)), and calculation formulas are  
\[\varnothing_{r}=\arctan(\Delta Y_{t}/\Delta X_{t}) \tag{1}\]  
\[\delta_{r}=\arcsin(\Delta Z_{t}/\rho_{t}) \tag{2}\]  
where  
\[\Delta X_{t}=x_{t-\Delta t}-X_{t}\]  
\[\Delta Y_{t}=y_{t-\Delta t}-Y_{t}\]  
\[\Delta Z_{t}=z_{t-\Delta t}-Z_{t}\]  
\[\rho_{t}=\sqrt{\Delta{X_{t}}^{2}+\Delta{Y_{t}}^{2}+\Delta{Z_{t}}^{2}}\]  
\[\stackrel{{\rightharpoonup}}{{\rho}}_{t}=\sqrt{(x_{t}-X_{t})^{2 }+(y_{t}-Y_{t})^{2}+(z_{t}-Z_{t})^{2}}\]  
Among them, \(\emptyset_{r}\) represents the reference right ascension, and \(\delta_{r}\) represents the reference declination. c refers to the speed of light. Note that \(x_{t-\Delta t}\), \(y_{t-\Delta t}\), and \(z_{t-\Delta t}\) represent the position of a space object, accounting for the propagation speed of photons, and are calculated using Lagrange interpolation polynomials. In addition, all data's time and coordinate systems need to be consistent. (3) Angular data error calculation. For a certain moment, the error of angular data is defined as  
\[\Delta\emptyset=\mathcal{O}_{o}-\mathcal{O}_{r} \tag{3}\]  
\[\Delta\delta=\delta_{o}-\delta_{r} \tag{4}\]  
\[e=\sqrt{\left(\mathcal{O}_{o}-\mathcal{O}_{r}\right)^{2}+\left(\delta_{o}- \delta_{r}\right)^{2}} \tag{5}\]  
where \(\mathcal{O}_{o}\) refers to the observed right ascension and \(\delta_{o}\) refers to the observed declination. The error \(e\) is calculated using Equation (5). The standard deviation \(S\) of an angular data file with \(n\) sets is given by Equation (6). \[\delta_{r}=\arcsin(\Delta Z_{t}/\rho_{t}) \tag{2}\]0  
where \(e_{i}\) refers to the error of each angular data point and \(\overline{e}\) is its mean value. Figure 2 presents the error of angular data collected at 21:38:00 on 28 September 2023. The angular data in this file start at 21:38:00 on 28 September 2023, with approximately one data point per second for approximately 3 min. The accuracy of angular data is usually associated with the characteristics of the telescope positions and space objects. Table 2 presents error statistics for 2 stations and 3 space objects. The results show that the accuracy of angular data for the three space objects  
\[\delta_{r}=\arcsin(\Delta Z_{t}/\rho_{t}) \tag{2}\]1 The errors of angular data that occurred on 28 September 2023.  
and two telescope stations is relatively similar, with an average value of approximately 10 arcseconds and a standard deviation of around 3 arcseconds. In addition, the average error in the right ascension for all files is approximately 2 arcseconds, with a standard deviation of about 7.3 arcseconds. The average error in declination is approximately \(-3\) arcseconds, with a standard deviation of about 3.8 arcseconds.
# Additive Manufacturing for Sensors: Piezoresistive Strain Gauge with Temperature Compensation
## 3 Results
### On-Off Preliminary Force Tests PF1 and PF2 (Ranges of 10 g, 0.1 mm, and 50 g, 0.4 mm, Respectively)  
Figure 4 shows the results of resistance compensation on the preliminary on-off tests performed to obtain a first estimate of sensor sensitivity (ohm per gram) and to evaluate the influence of temperature. The high correlation between temperature \(T_{2}\) and resistances \(R_{a}\) and \(R_{d}\) is clear in Figure 4. Moreover, the variation of \(R_{a}\) due to the 10 g steps in test PF1 is not distinguishable from the variation due to temperature (Figure 4c), whereas the 50 g steps are better observable even in the presence of temperature drift due to their higher amplitude (Figure 4h). Hence, temperature compensation is performed with respect to \(R_{d}\) for test PF1 and test PF2. Force reconstruction led to an RMSE of 3.0% in the 50 g range, whereas an RMSE of 17.3% is obtained in the 10 g range. However, the absolute RMSE values are comparable, with values of 1.5 g and 1.7 g for tests PF1 and PF2, respectively. The RMSE results obtained in both cases prove that the compensation procedure with the proposed method allows reconstructing the force applied on \(S_{a}\), which results in being very sensitive to 50 g steps with good accuracy, but it can also discriminate 10 g steps. The experimental results led to the choice of 20 g steps for the following force profile as a trade-off between the total number of steps (and test time) for a given range and the expected capability of clearly observing force changes.
# Comparative Vulnerability Analysis of Thai and Non-Thai Mobile Banking Applications
## 2 Background and Related Work
### Mobile Security Threats  
In today's digital landscape, ensuring the security of mobile applications has gained significant importance, especially in the context of financial transactions. Given that mobile banking applications manage confidential user data and financial details, they are highly susceptible to cyber threats. In response to these security challenges, the Open Worldwide Application Security Project (OWASP) introduced the OWASP Mobile Top 10, which is a valuable reference point for developers and cybersecurity experts.  
This well-regarded framework identifies and classifies the ten most common security risks associated with mobile applications. It plays a vital role in shaping our research endeavours by directing our focus towards the vulnerabilities that are most prone to exploitation within mobile banking applications.  
The list of common cyber threats of mobile applications and their descriptions as compiled by OWASP Mobile Top 10 [6] is provided in Table 1.  
Our research aims to enhance the security of mobile banking applications by identifying and mitigating the cybersecurity risks provided by the OWASP Mobile Top 10 in Table 1. This effort is intended to strengthen user confidence and trust in utilising mobile platforms for financial transactions. By systematically evaluating the security weaknesses of mobile banking applications using the OWASP Mobile Top 10, this research not only highlights common vulnerabilities but also uncovers potential regional differences that may influence security practices. Understanding these trends is crucial for stakeholders, including developers, customers, and financial institutions, as it enables them to tailor their security measures to address specific vulnerabilities prevalent in their respective markets.
# A Software-Defined Networking Framework to Provide Dynamic QoS Management in IEEE 802.11 Networks
## 3 Proposed SDN-Based Framework for Implementing DEDCA  
This section describes a SDN framework for IEEE 802.11 infrastructure-based networks that implements the proposed DEDCA mechanism. Being the central point of the network management and network monitoring, the SDN controller is the ideal network element to manage the processes related to the EDCA mechanism, by programming the adequate software module. This framework makes possible a dynamic management of the backoff values related to contention-based medium access mechanism of the standard IEEE 802.11, offering to the wireless terminals a response to dynamic QoS requirements.  
The amount of real scenarios and applications which could benefit from the implementation of the proposed DEDCA mechanism is wide and varied. By way of example, we are going to consider a particular scenario that allows us to show the validity and usefulness of our proposal. In this case, we are going to consider an outdoor parking lot, where a surveillance system is installed. It is represented in a schematic way in Figure 3.  
Figure 2: Values of gain \(G\) when the default value of \(CW_{min}\) is decremented in \(k\) units (\(G^{+}\)) and incremented in \(k\) units (\(G^{-}\)), for \(W=16\).  
The wireless network consists of an SDN 802.11a Access Point that is equipped with OpenFlow protocol (i.e., OpenWRT AP) and sixteen 802.11a outdoor surveillance cameras that cover a parking lot of dimension 200 m \(\times\) 200 m. The video signals captured by the cameras are transmitted to a surveillance center, where a surveillance software and the SDN controller are executed.  
When all the wireless terminals are configured by default, the available bandwidth is equally shared among all the cameras. The 802.11a data rate is set to 24 Mbps. Thus, due to the fact that there are sixteen contending stations, each station only obtains enough bandwidth to transmit H.264 video streaming at the common frame resolution 4 CIF and 12 fps (the typical frame rate in parking lots). If a higher resolution is required by any of the cameras at a given time, the bandwidth sharing has to be modified.  
We propose to use the DEDCA mechanism to give a solution to this problem. As detailed in Section 2.2, the DEDCA mechanism is based on the definition of three terminal categories (TC): _normal, requesting_ and _giving terminals_. In this case, the default backoff configuration of a terminal, which corresponds to a \(CW_{min}\) of 31, defines a _normal terminal_. On the other hand, the cameras that require a higher bandwidth are the _requesting terminals_ and, finally, the set of cameras that give part of their bandwidth up are the _giving terminals_.  
The SDN controller will be in charge of detecting the _requesting terminals_ and selecting the set of _giving terminals_. In addition, using the _gain_ scalar \(G\) from Section 2.2.1, the controller will obtain the new backoff values of all these terminals.
# Internal Flow Prediction in Arbitrary Shaped Channel Using Stream-Wise Bidirectional LSTM
## 3 Experiments
### Implementation Details  
In the experiments, we used the Adam optimizer [38] (\(\beta_{1}=0.5\), \(\beta_{2}=0.999\)). The learning rate was initialized to \(1\times 10^{-4}\) and the batch size was set to 64. All methods were trained for 200 epochs and evaluated at each epoch. Using the cosine annealing algorithm [39] as the learning rate scheduler, the learning rate gradually decayed to \(1\times 10^{-6}\). The PyTorch framework [40] and two NVIDIA RTX 3090 GPUs with 24 GB of RAM, 48 GB in total, were used for the implementation. The official code can be found in the following link: [[https://github.com/choiwanuk/SB-LSTM](https://github.com/choiwanuk/SB-LSTM)]([https://github.com/choiwanuk/SB-LSTM](https://github.com/choiwanuk/SB-LSTM)), accessed on October 19 2023.
# Study on the Anti-Interference Performance of Substrate-Free PEDOT:PSS ECG Electrodes
## 2 Materials and Methods
### Impedance Measurement and ECG Monitoring  
The skin-electrode impedance was measured using an electrochemical workstation (Parstat 4000A, Ametek Ltd., Berwyn, PA, USA) with a three-electrode measurement system, in which the counter electrode (CE) and the working electrode (WE) carry the current, the working electrode and the reference electrode (RE) measure the voltage, and the sensing electrode (SE) and the working electrode (WE) are clamped together. Skin-electrode impedance was measured on the right arm of a healthy male, and the skin under test needed to be cleaned and wiped with alcohol before the experiment to prevent the possible presence of oils and grease from affecting the results. As shown in Figure 3a, the subject was seated in front of the electrochemical workstation in a relaxed state to prevent skin tightness, the test electrodes were attached to the inner side of the right arm, where two Ag/AgCl wet electrodes were connected to the reference and counter electrodes in the three-electrode system, with the center distance between the two sets at about 8 cm, and the substrate-free PEDOT:PSS dry electrodes were attached in the middle and connected with the working electrodes and the sensing electrodes for the EIS measurements. The signal amplitude (Vrms) was set to 10 mV, and the frequency scanning range was set to 1-1000 Hz in the static influence factor experiment. Since most of the energy of the ECG was concentrated in 0.1-35 Hz in the dynamic influence factor experiment, the EIS frequency points were set to 1, 10, and 30 Hz for the experiments.  
For ECG measurements, as shown in Figure 3b, the substrate-free PEDOT:PSS electrodes were employed as the sensing electrodes, affixed to the inner side of the subject's right wrist and left ankle skin surface and connected to a digital multi-lead ECG machine (BeneHeart R3, Mindray, Shenzhen, China) for ECG signal acquisition. To better investigate the effects of interference factors on ECG, the ECG machine was set to enable only a fixed 50 Hz power line interference filter, while all other filters or processing functions were disabled.
# Coordination of Macro Base Stations for 5G Network with User Clustering
## 5 Conclusions  
In this study, a two-step optimal energy management for a 5G macro BS network was developed to coordinate the BSs' on/off states, user allocation, and power transmission among BSs in the network. A user clustering method based on geographic location was proposed to reduce the computational burden, and the Benders decomposition method was applied to accelerate problem solving. Case studies were conducted on a 3 \(\times\) 3 5G macro BS network and a 10 \(\times\) 10 5G macro BS network. The key findings of the simulation results are summarized as follows:  
* The two-step energy management model for communication and standard equipment can effectively reduce the energy consumption and electricity costs of the entire 5G macro BS network compared with the conventional dispatching scheme by making full use of the spatial and temporal fluctuations of the traffic load, the thermal inertia of the cabinets, and the storage of the backup batteries;
* The proposed solution-accelerating methods--that is, user clustering and Benders decomposition--were found to be computationally efficient, while they ensured excellent performance with approximate optimality.  
All authors contributed extensively to the work presented in this paper. Conceptualization, K.L., J.F. and X.A.; methodology, K.L.; software, B.Z. and L.L.; validation, K.L., J.F. and X.A.; formal analysis, K.L.; investigation, K.L.; resources, J.F.; data curation, K.L.; writing--original draft preparation, K.L.; writing--review and editing, K.L., J.F. and X.A.; visualization, K.L.; supervision, J.F. and X.A.; project administration, J.F.; funding acquisition, J.W. All authors have read and agreed to the published version of the manuscript.  
Figure 11: Average indoor temperature.  
Figure 12: Energy storage of backup batteries in the 5G macro BS network.  
Figure 16: Electricity price.  
Figure 17: Traffic load of a 10 \(\times\) 10 5G macro BS network.
# Nanomaterials in Craniofacial Tissue Regeneration: A Review
## 4 Current State of Nanomaterials in Crani Tissue Regeneration  
### Challenges in Clinical Translation  
While it is evident that nanomaterials serve a promising purpose in craniofacial tissue regeneration, there are challenges that need to be addressed to further the integration, application, and translation of nanomaterial use in clinical settings. One challenge is optimizing cell viability. Nanomaterial-based hydrogels can support cell growth during implantation for bone regeneration; however, these hydrogels tend to have low mechanical strength. Various nanopolymers can be used to strengthen the hydrogel but can compromise the biofabrication and fabrication time, thus reducing cell viability [72]. To improve cell viability, novel scaffold development techniques have been suggested, such as solution electrospinning and 3D printing techniques, though these techniques greatly limit the manufacturing and production of these scaffolds. Regardless, to date, these techniques have yet to be applied to nanomaterial-based scaffolds for craniofacial tissue engineering [72]. Additionally, immunogenic properties must be considered as well: Although one material may have a superior structural resemblance to native tissue and/or have a superior cell viability, it may be more likely to elicit a severe immune response in certain individuals [72]. Another challenge, as previously mentioned, is the innervation of the tissues engineered via nanomaterials, such as dental pulp, which has not been studied to our knowledge. In general, although the results are promising, further groundwork (such as a better understanding of the biomechanisms and the impact of nanoscale spacing and orientation) is required before the application of nanomaterials in a clinical setting can be considered [73].
# Design and Testing of Torveastro: An Outer Space Service Robot
## 3 Methods  
The methods utilized to fulfill the project's purpose are summarized in Figure 1. A number of specifications [20; 21] must be met by an astronaut robot intended for space tasks. The design specifications will correspond to the problem and desired outcomes, such as going from one site to another using existing infrastructure, such as handrails. The mechanism specifications refer to the construction of an appropriate mechanism that can ensure the performance of the astronaut robot for the required task, such as a compliant gripper that can adapt its grabbing while travelling along handrails. The objective of electronics design is to create devices that are compatible with their intended environment and protected from its characteristics, such as ionizing radiation. The ultimate objective of control design is to integrate everything, such as receiving an input and doing the necessary task utilizing embedded sensors. The hostile space environment, consisting of microgravity, complex illumination, and severe radiation, imposes obstacles for space robotics in the areas of long-distance stable mobility, dexterity and safe manipulation, precision sensing, and high-precision measurement [19].  
In a constrained microgravity environment, it is difficult to conduct a variety of stable movements and safe dexterous manipulation, and it is also difficult to verify the 3D motion of a robot astronaut on the ground. However, the motion mechanism of humanoid robots in situations with microgravity differs significantly from that of those on Earth.  
Due to advancements in astronaut robot technology, the astronaut robot aboard the space station has improved in terms of stable motion, dexterous manipulation, and precise sensing and measuring.  
The aim of the Torveastro project is to create a robot that can work along the current handrails installed outside the space station to aid astronaut movement. Using a combination of bionics and robotics, methods of human-like stable motion were analyzed. The Torveastro robot was therefore built to follow the railings intended for human space travel. Along the surface of the space station, rails are installed to allow astronauts to perform maintenance and service operations in space. To address the issue of hostile space environments, in the Torveastro astronaut robot, all the electronics and actuation are installed in the central body and the forces are transmitted with cables along the limbs, thereby avoiding  
Figure 1: A framework for designing outer space astronaut robot design.  
exposure damage and ensuring long-life performance during inspection, maintenance, and service in-orbit operations.
## 2 Materials and Methods  
### Materials  
Nicotinamide Mononucleotide (95%), sodium fluorescein, DSPE-PEG2000(1,2-disteaoryl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]), and DSPE-PEG2000-Mal (1,2-disteaoryl-sn-glycero-3-phosphoethanolamine-N-[maleimide(polyethylene glycol)-2000]) were obtained from Shanghai vianye Bio-Technology Co., Ltd. (Shanghai, China). Soy lecithin was obtained from Avanti (Alabaster, AL, USA). The peptide RVG with cysteine at the C-terminus (H2N-YTIWMPENPRPGTPCDIFTNSRGKASNG-OH, HS-RVG) and the peptide ANG with cysteine at the C-terminus (TFFYGGSRGKNNFKTEYC, HS-ANG) were synthesized by MeloPEG (Shenzhen, China). \(\beta\)-Mercaptoethanol (\(\beta\)-ME), cholesterol was obtained from Sigma-Aldrich (St. Louis, MO, USA), and 3-(4,5-Dimethyl-2-Thiazolyl)-2,5-Diphenyl Tetrazolium Bromide (MTT) was obtained from Thermo Fisher Scientific (Waltham, MA, USA). Other chemicals were of analytical grade, and solvents used in HPLC were of HPLC grade.  
Transwell(tm) plates of 12 wells (12 mm, pore size 3.0 um) were purchased from Corning Costar (Cambridge, MA, USA). Endothelial Cell Medium was obtained from ScienCell Research Laboratories (Carslbad, CA, USA). [PERSON] balanced salts solution (HBSS) was obtained from Gibco Laboratories (Life Technologies Inc., Grand Island, NY, USA).  
hCMEC/D3 cell line was obtained from Hunan Fenghui Biotechnology Company (Changsha, China).
## 3 Results
### Development of Research Interest over Time  
The development of the research field can be assessed by the number of publications over time. Composite Figure 3 presents both a bar chart and a donut chart, providing a comprehensive visualization of the annual publication count for each journal category and overall distribution. Four journal categories are selected to classify each publication to a specific group: \"Remote Sensing\", \"Agronomy\", \"Environmental Science\", and \"Other\". The category \"Other\" includes all journals that do not fit into one of the three categories, such as the journals \"Global Healthaction\", \"Engineering of Applications of Artificial Intelligence\", or \"American Journal of Tropical Medicine and Hygiene\".  
The bar chart on the left side of Figure 3 shows that, as of the end of April 2024, only six publications had been released during the year. This is likely due to the limited time frame. The overall trend depicted in the figure shows a clear increase in the number of publications over time, with 2023 reaching a peak of 24 publications. Notably, 53% of all publications have been released since 2019, highlighting the recent increase in output. \"Remote Sensing\" stands out as the most frequent category in nearly every year, especially in recent times, reflecting a growing emphasis on this field. Nearly half of the 163 publications (47.9%) fall under this category. \"Environmental Science\" is also consistently represented, though less frequently than \"Remote Sensing\", comprising 27.6% of the total publications. \"Agronomy\" shows a steady presence, accounting for 17.2% of the publications, with noticeable activity in 2020, 2022, and 2023, suggesting a slight increase in focus on this area recently. In the earlier years (2000 to 2014), there were fewer publications and categories, with \"Remote Sensing\" still dominant but less frequent overall, followed by an expansion in the later years. Twelve publications (7.4%) could not be classified into any of these categories.