esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Phase Analysis of CuO-CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\)
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Catalyst** & **Reaction Condition** & **Protection Time** & **Reference** \\ \hline \multirow{3}{*}{0.5\%Pt-Al\({}_{2}\)O\({}_{3}\)} & 299 \({}^{\circ}\)C, & \multirow{3}{*}{8 h} & [PERSON] \\  & DMMP concentration 3.5 g/m\({}^{3}\), & & et al. [18] \\  & flow rate 8.85 L/min & & \\ \hline \multirow{3}{*}{Cu2-HA} & 400 \({}^{\circ}\)C, & \multirow{3}{*}{7.5 h} & \multirow{3}{*}{[PERSON] et al. [19]} \\  & DMMP concentration 3.58 g/m\({}^{3}\), & & et al. [18] \\  & DMMP concentration 3.58 g/m\({}^{3}\), & & et al. [19] \\  & flow rate 100 mL/min & & \\ \hline \multirow{3}{*}{10\% V/Al\({}_{2}\)O\({}_{3}\)} & \multirow{3}{*}{400 \({}^{\circ}\)C, } & \multirow{3}{*}{8 h} & \multirow{3}{*}{[PERSON] et al. [8]} \\  & DMMP concentration 1300 ppm, & & et al. [8] \\ \cline{1-1}  & low rate 50 mL/min & & \\ \hline \multirow{3}{*}{10\% Fe/Al\({}_{2}\)O\({}_{3}\)} & \multirow{3}{*}{12.5 h} & \multirow{3}{*}{\multirow{3}{*}{8.5 h}} & \multirow{3}{*}{[PERSON] et al. [8]} \\  & DMMP concentration 1300 ppm, & & et al. [8] \\ \cline{1-1}  & low rate 50 mL/min & & \\ \hline \multirow{3}{*}{10\% Ni/Al\({}_{2}\)O\({}_{3}\)} & \multirow{3}{*}{1.5 h} & \multirow{3}{*}{[PERSON] et al. [8]} \\  & DMMP concentration 1300 ppm, & & \\ \cline{1-1}  & low rate 50 mL/min & & \\ \cline{1-1}  & low rate 50 mL/min & & \\ \hline \multirow{3}{*}{10\% V/SiO\({}_{2}\)} & \multirow{3}{*}{25 h} & \multirow{3}{*}{[PERSON] et al. [8]} \\  & DMMP concentration 4.0 g/m\({}^{3}\), & & \\ \cline{1-1}  & low rate 100 mL/min & & \\ \hline \end{tabular}
\end{table} 
Table 1: A comparison of protection time on various catalysts. addition, the grain size of CeO\({}_{2}\) in the CuO-10% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) catalyst was larger than that of CeO\({}_{2}\) on CuO-5% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\). However, the thermal catalytic decomposition performance of CuO-10% CeO\({}_{2}\)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) was relatively limited. Therefore, the size of the CeO\({}_{2}\) grains is one of the essential considerations for the successful development of catalysts for thermal catalytic decomposition [24].
# VRChem: A Virtual Reality Molecular Builder
### Virtual Reality as an Educational Tool
While all software systems were seen as having aided the students' understanding of the reaction nearly equally, the VR application was seen as much more enjoyable, was better for improving the students' understanding of molecular structure and increased their interest in computational chemistry. [PERSON] et al. [16] tasked a small group of pupils and their teacher (N = 13, ages 12-36) to build molecules using a virtual reality HMD and haptic gloves in a gamefied VR application. Again, learning outcomes were not measured, but participants reported an increase in learning motivation and engagement towards chemistry and saw value in VR as a tool for teaching [19]. Finally, [PERSON] et al. had their university students (N = 70) compare the sizes of molecules and carbon nanotubes in VR and then assess the bulkiness of similar compounds and sizes in a questionnaire. The results agreed with those from other groups before, with students considering the workshop enjoyable and useful, and several wished for more VR exercises. However, no conclusion could be drawn about the benefits of the workshop, possibly due to the scope and formatting of the questionnaire [20]. Other studies reported positive results or outlooks as well [21; 22; 23; 24]. Overall, the current view of using VR for tuition is generally positive, though not all studies fully support this view. For example, in one of their studies, [PERSON] et al. saw an initial increase in motivation and a high perceived value of VR training after one three hour VR workshop, but the effect decreased rapidly with more exercises, and VR use was ultimately considered a \"fun add-on thing of very little value for the course\" in a follow-up interview [22]. It should be noted that the exercises had limited interactivity and underutilized the capabilities of VR, which could explain the reactions. [PERSON] et al. concluded that VR can be of use in teaching, but that being a new teaching method, it requires more carefully thought out exercises. Additionally, a study by [PERSON] et al. reported that using immersive VR for science laboratory simulations is disadvantageous to learning when compared to a normal computer interface, despite the increased sense of presence [25]. The study, however, was not explicitly chemistry-related and was conducted using a relatively unsophisticated VR device and an awkward-to-use control method, leading to a poor user experience that could have factored into the results. In conclusion, while most of the studies on using VR as an educational tool used small test groups and often did not attempt to quantify any learning gains, they mostly agreed that VR has potential to be an advantageous teaching aid and at the very least is not counterproductive in chemistry education. Whether the benefit arises from the immersive experience, the stereoscopic three-dimensional molecular models or simply from using an entertaining technological device that helps motivate students is uncertain but seen as worthy of exploring.
# SDR-Based 28 GHz mmWave Channel Modeling of Railway Marshaling Yard
## 3 Software-Defined Radio-Based Channel Modeling
### SDR mmWave Measurement System
#### 3.1.1 Key Hardware Components  
The two most important components of the hardware of the measurement system are the receiver/transmitter USRP-2974 and the mmWave phased-array antenna mmPSA-TR64 MX, as shown in Figure 7.  
USRP-2974 is a high-performance software-defined radio (SDR) device produced by NI company, and is widely used for channel measurements in wireless communication systems. There are many advantages to using the USRP-2974 for channel measurements. Firstly, it provides high-performance analog-to-digital converters and processors that can achieve high-precision signal acquisition and analysis. Secondly, it supports a wide range of programming tool and development libraries, including GNU Radio, LabVIEW, and MATLAB, so that users can quickly customize their own channel measurement applications. The main parameters of the USRP-2974 are listed in Table 3.  
The mmWave phased-array antenna mmPSA-TR64 MX is a 64-unit two-dimensional mmWave phased-array antenna, the duplex mode of which is TDD, and the operating frequency band is 27-29 GHz. It supports the 3 GPP 5G FR2 n257 frequency band and can be used for 5G mmWave wireless communication. The mmPSA-TR64 MX is equipped with 64 phase-shifting transceiver channels, which can achieve high-performance dynamic beamforming of 4096 states in a two-dimensional \(\pm\)60\({}^{\circ}\) degrees range, and the EIRP value is 51 dBm. The array can be individually turned on or off per 2 \(\times\) 2 antenna unit to achieve flexible array reconstruction. The phased array is internally integrated with a bidirectional frequency conversion circuit and a high-performance mmWave local oscillator, realizing a 2-4 GHz 5 band IF transceiver interface, which is convenient for connection with the low-frequency band digital sampling system. The beam characteristics of the mmWave phased-array antenna are shown in Figure 8:  
Figure 8: Beam Characteristics of the mmWave phased-array antenna. (**a**) Horizontal beam. (**b**) Vertical beam. (**c**) Beam Width.  
Figure 7: Receiver/transmitter and mmWave phased-array antenna. (**a**) USRP 2974. (**b**) mmWave phased-array antenna mmPSA-TR64 MX.
## 2 Literature Review
### The Role of DIDs and Digital Twins  
While traditional traceability often relies on centralised databases prone to silos and tampering, DIDs and digital twins offer a more robust approach to managing product identity.  
DIDs provide a globally unique, verifiable, and self-sovereign identifier for each product or batch, independent of centralised authorities [4]. They enable secure, cryptographically verifiable relationships between physical products and their digital representations.  
Digital twins act as real-time, virtual counterparts of physical products, maintaining up-to-date states of the product's attributes, conditions, and certifications across its lifecycle [36].  
\begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**Title** & **Major Contribution** & **Research Question** \\ \hline Blockchain and Digital Twin Applications in Smart Agriculture [29] & Explores the integration of blockchain and digital twins in smart agriculture. & How do blockchain and digital twins benefit smart agriculture? \\ \hline Enhancing Traceability in Agricultural Supply Chain Using Blockchain Technology [30] & Proposes a blockchain-based model for improving agricultural supply chain traceability. & How can blockchain enhance traceability in agricultural supply chains? \\ \hline Digital Traceability in Agri-Food Supply Chains: A Comparative Analysis of OECD Member Countries [31] & Presents blockchain implementation for soybean supply chain traceability. & How can blockchain be used for traceability in soybean supply chains? \\ \hline Blockchain and Digital Twin Applications in Precision Agriculture: A Comprehensive Approach [32] & Details a comprehensive approach combining blockchain and digital twins for precision agriculture. & How can blockchain and digital twins be applied in precision agriculture? \\ \hline AgriBlockchain: Agriculture Supply Chain Using Blockchain [33] & Proposes a blockchain-based architecture for agricultural supply chain management. & How can blockchain improve agricultural supply chain operations? \\ \hline \hline \end{tabular}
\end{table}
Table 2: Cont.  
Unlike generic tracking IDs (e.g., barcodes, QR codes), DIDs and digital twins support:
* Immutable provenance data linked to the product identity;
* Dynamic updates reflecting transformations (e.g., processing, packaging);
* Secure, interoperable data exchange between stakeholders.  
Thus, while traceability answers \"where has the product been?\", product identity answers \"what exactly is this product, and can its claimed attributes be verified?\". Both are essential for transparent, trustworthy supply chains, but product identity adds an additional layer of authenticity assurance.
# Teamwork Conflict Management Training and Conflict Resolution Practice via Large Language Models
## 2 Background
### LLMs In Education  
The adoption of large language models (LLMs), such as GPT-3 and newer iterations, in educational settings has been increasing, transforming ways of teaching and learning [39; 40]. The integration of LLMs into educational practices leverages the capability of these models to simulate complex human interactions, providing students with a unique platform for practicing communication strategies in a controlled environment [41; 42].  
The use of LLMs in educational contexts offers numerous advantages. Primarily, these models provide a scalable method for delivering personalized education and feedback [41]. They can generate a wide range of responses to student input, which allows for dynamic interaction that can mimic real-life conversations [42]. This capability is particularly useful in conflict management training, where students can practice negotiation and resolution strategies in a variety of simulated scenarios without the logistical challenges of organizing role-plays with human actors [43; 44]. Moreover, LLMs facilitate a safe learning environment where students can make mistakes and learn from them without the fear of real-world consequences [45]. This aspect is critical in educational psychology, as it supports the development of interpersonal skills in a low-stress setting, encouraging deeper learning and reflection [43].  
LLMs are being used in various educational applications to enhance learning experiences and outcomes. For example, [PERSON] et al. [46] used ChatGPT, a type of LLM, to generate lesson plans and multiple-choice quizzes based on the learning outcomes provided by the professor for a particular class. These lesson plans were customized to different styles (traditional, with Batman references, or with [PERSON] influence) to increase engagement. [PERSON] et al. [42] discussed their use in language learning, where LLMs helped learners by providing feedback on vocabulary and general proficiency and serving as a conversation partner for practice. Research by [PERSON] et al. [47] demonstrated the successful integration of ChatGPT in game development education to enhance students' creativity, problem-solving skills, and critical skills. Finally, [PERSON] and [PERSON] [48] utilized ChatGPT in programming learning and teaching and illustrated how it helped students improve their programming skills.  
The present study aims to contribute to this growing body of research by exploring the nuanced experiences of computing and engineering students as they engaged in conflict management training via LLMs and employed conflict resolution strategies in teamwork. Understanding these experiences is not only essential for evaluating the viability of LLMs in conflict management training but also for developing pedagogical approaches that prepare students for the technical aspects of their future professions and equip them with the skills necessary for effective teamwork and conflict resolution.
## 3 Results and Discussion
### Electricity Consumption  
Figure 7 shows the annual quantity of electricity consumed for cooling, lighting, etc., in this office building when it is built in the four cities. The main results showed an estimated annual electricity consumption of between 88.2 and 121.3 kWh/m\({}^{2}\) in the four cities, and this amount is estimated to between 81.7 and 110.7 kWh/m\({}^{2}\) after setting 5 cm of insulation on the walls and roof, between 79.0 and 107.8 kWh/m\({}^{2}\) after setting 7.4 cm of PCM material, and between 74.1 and 101.6 kWh/m\({}^{2}\) after combining insulation and building shading. At the same time, an electricity consumption between 30% and 40% bigger in the hot tropical coastal (e.g., Mahajunga city) than in the humid tropical coastal region was observed (Toalagnaro city). The distribution of electricity consumption per strategy is shown in Table 5. The PCM has a very significant effect on the indoor climate. Indeed, [PERSON] et al. [9] showed that optimal PCMs are capable of reducing temperature fluctuations and the maximum temperature up to 2.04 \({}^{\circ}\)C.  
From this table, it can be concluded that the consumption of electrical energy varies according to the seasons. This rate remains very low compared to that of developed countries. Globally, it can be observed that the energy demand is expected to increase between 10% and 25% in 2050, and up to 85% in 2100, when the air temperature increase is between 1.5 \({}^{\circ}\)C and 3.5 \({}^{\circ}\)C. [PERSON] et al. [38] showed that  
Figure 6: Cooling energy saving in the four cities during the two seasons.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Cities**} & **No** & **With Shading** & **With** & \multirow{2}{*}{**With PCM**} & **With Insulation** & \multirow{2}{*}{**2050**} \\  & **Strategy** & **Effect** & **Insulation** & & **+ Shading** & \\ \hline Antsiranana & 115.6 & 111.8 & 104.2 & 101.6 & 95.7 & - \\ Mahajunga & 121.4 & 119.2 & 110.7 & 107.9 & 101.6 & 129.3 \\ Taolagnaro & 88.2 & 87.3 & 81.6 & 79.1 & 74.1 & 90.3 \\ Toamasina & 90.1 & 85.5 & 83.0 & 80.7 & 75.6 & - \\ \hline \hline \end{tabular}
\end{table}
Table 5: Electricity consumption (kWh/m\({}^{2}\)).  
the energy demand is expected to increase between 120% and 530% with an increase in air temperature between 2 \({}^{\circ}\)C and 5 \({}^{\circ}\)C in the next decade in Australia. Some results found in these results confirm these findings.
## 3 Results  
Results are presented for a drone flight conducted during the day on 18 March 2022, at 2:30 p.m. The wind speed recorded at the local weather station, Perth Airport, was \(\approx\)16.7 km/h [24].  
The link budget for the testbed is presented in Table 1. The optical sensitivity floor for the photodetector was determined to be \(-33\) dBm, corresponding to a mean output voltage of 1.4 mV. During measurements, the variable optical attenuator was adjusted such that the received power, after pointing losses, was near the threshold for error-free reception. Error-free reception occurred when the output voltage exceeded 2.9 mV, corresponding to an optical pulse power of \(-30.3\) dBm. Typically, less than one-third of the codewords were received without error, as the optical power received remained consistently above the \(-30\) dBm error-free threshold due to angle-of-arrival correction by the TT mirror. At this link distance, the beam size is smaller than the Fried parameter and, therefore, scintillation due to turbulence was not expected to cause any fading in excess of the angle-of-arrival errors caused by drone movement and beam wander.  
To confirm receiver functionality, BER was compared to Equation (1) using observations for SNR per Equation (3). The portion of transmissions received with bit errors, caused by partial or complete signal fading arising due to pointing errors, allow the receiver performance to be characterised. Figure 3 shows the SNR as derived from Equation (3) and BER for 720 codeword transmissions, with each data point representing a single 15,120-bit codeword. This record has a BER measurement sensitivity floor of 1/15,120 errors per bit, and a ceiling at 1/2 errors per bit, caused by failure to demodulate, though pulses were present. For comparison, the theoretical BER, from Equation (1), is plotted alongside the data as a black line in Figure 3.  
\begin{table}
\begin{tabular}{l r l} \hline \hline \multicolumn{1}{c}{**Parameter**} & \multicolumn{2}{c}{**Value**} \\ \hline Transmit power & \(13.0\) & dBm \\ Modulator insertion loss & \(-3.50\) & dB \\ Circulator losses & \(-2.40\) & dB \\ Splitter loss (2 way) & \(-6.00\) & dB \\ Singlemode fibre coupling penalty & \(-10.0\) & dB \\ \hline Receive power (error free) & \(-30.3\) & dBm \\ Combined pointing and variable attenuator loss & \(22.6\) & dB \\ \hline Mean photodetector sensitivity & \(-33.0\) & dBm \\ Error-free link margin & \(2.70\) & dB \\ \hline \hline \end{tabular}
\end{table}
Table 1: Link budget for retroreflected laser link to drone.
# Underwater SLAM Meets Deep Learning: Challenges, Multi-Sensor Integration, and Future Directions
## 2 Core Principles of SLAM: Front-End and Back-End  
SLAM is a fundamental problem in robotics, concerned with building a map of an unknown environment while simultaneously determining the robot's location within that map [6]. The core challenge lies in overcoming sensor limitations and noise while incrementally building a consistent map of the environment. SLAM systems aim to improve both localization and mapping by incorporating them together. In contrast, visual odometry (VO) focuses mainly on estimating the robot's motion by analyzing camera images without creating a map. The critical difference is SLAM's ability to build and optimize a map, providing a broader spatial understanding. VO is limited to tracking movement relative to the environment without mapping it. Figure 3 illustrates the difference between the SLAM and VO algorithms.  
SLAM systems are typically divided into two main modules: front-end and back-end. The front-end processes raw sensor data to extract meaningful features or observations, which involves filtering sensor noise, detecting landmarks, extracting features, or interpreting depth information. The front-end's primary goal is to convert raw data into a format that localization and mapping modules can use. On the other hand, the back-end takes the processed data from the front-end. It focuses on estimating the robot's trajectory and building a map of the environment using optimization or filtering techniques that minimize errors over observations, such as loop closures, when the robot revisits previously mapped areas. The back-end ensures that the SLAM solution is coherent and accurate over time. The following provides a detailed explanation of these two modules.
## 4 Geographical Dispersion of Wind Velocities in Wind Farm (WF)  
As a small deviation in the wind velocity estimation can cause large consequences on the frequency of the system, the effect of geographical dispersion of wind velocity in a WF must be taken into account. In an actual wind site, wind velocity observed at a meteorological station with specific geographic coordinates must be adjusted for WTGs presented in that site. Wind velocity changes with the height above the ground and with the type of terrain surfaces. The logarithmic wind profile, mentioned in Equation (29), is a good approximation for these variations [28].  
\[\mathrm{V_{2}}=\ \mathrm{V_{1}}\frac{\ln\frac{\mathrm{h_{2}}}{\mathrm{z_{2}}}}{ \ln\frac{\mathrm{h_{1}}}{\mathrm{z_{1}}}}, \tag{29}\]  
\(\mathrm{V_{1}}\) is the reference wind velocity at the reference height \(\mathrm{h_{1}}\), \(\mathrm{V_{2}}\) is the wind velocity at height \(\mathrm{h_{2}}\). \(\mathrm{Z_{1}}\) and \(\mathrm{Z_{2}}\) are roughness lengths at the reference point and the considered point, respectively. \(\mathrm{Z}\) varies between 0.0002 to 1.6 m. Detailed specification of parameter \(\mathrm{Z}\), mentioned in Equation (29), has been mentioned in Table 2. It must be noted that the considered range of parameter \(\mathrm{Z}\) covers all land types on which WFs can be constructed [29].
## Data
### AVHRR and SEVIRI  
The Advanced Very High Resolution Radiometer (AVHRR), flying aboard the National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational Satellite (METOP) polar satellites, was designed mainly for meteorological studies.  
This instrument, which offers a good trade-off between temporal (up to 6 h) and spatial (1.1 km at nadir view) resolution, provides data in five spectral channels ranging from visible (VIS) to thermal infrared (TIR). Channel 3 (3.55-3.93 um), which is centered in the medium infrared region (MIR), has been largely used to identify volcanic thermal anomalies, such as lava flows and fumarolic emissions (e.g., [40; 41; 42; 43; 44]). Channel 4 (10.3-11.3 um), which is located in the TIR region, has been used in combination with channel 5 (11.5-12.5 um) to detect ash/dust clouds by exploiting the reverse absorption effects of silicate particles at 11- and 12-um wavelengths in comparison with water/ice droplets [45; 46].  
Spinning Enhanced Visible and Infrared Imager (SEVIRI), aboard Meteosat Second Generation (MSG) satellites, operates in 12 spectral channels, providing data with a temporal sampling of 15 min. Despite the coarse spatial resolution (\(\sim\)3 km at the nadir), this sensor represents, thanks to its geostationary attitude, an important instrument for studying, monitoring, and characterizing both volcanic phenomena (e.g., [47; 48; 49]) and Saharan dust events (e.g., [50; 51; 52]).  
In this work, we present the results achieved from analyzing a set of satellite-based products generated using the robust satellite technique (RST) multitemporal approach [53; 54]. In addition, we investigated the AVHRR observations of Outgoing Longwave-Earth radiation (OLR) associated with the Mt. Etna eruptive activity of September-December 2006, available from the NOAA Climate Prediction Center.