esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
### Landslide Recognition Results
provided with a substantial amount of unlabeled environmental features, semi-supervised generative adversarial learning helps distinguish landslides from non-landslides in images and reduces the false detection rate of landslides in complex geographical environments. Consequently, the model presented in this paper emerges as a dependable tool for landslide extraction, streamlining the creation of an accurate landslide database crucial for landslide identification. Although the performance improvement of the method in this research is only slight compared to Model a, its significance should not be overlooked. Particularly in addressing the challenging problem of landslide sample imbalance, the method in this research has demonstrated its effectiveness and applicability. This small improvement may seem negligible, but in real-world applications, every bit of performance enhancement can lead to more accurately predicted landslide events, thereby helping to reduce potential disaster risks. More noteworthy is that the method proposed in this research not only provides substantial contributions to current research, but also opens up new ideas and directions for future researchers.
## 3 Dataset Analysis
### Dataset Overview
The number of keywords plus, which are automatically generated from the titles of the articles, is 2275, with an average of 2.01 keywords per document--see Table 3. The authors' keywords are 3379, with an average of 2.99 per document. With regard to authors, our analysis has identified a total of 3394 unique authors, contributing to a cumulative count of 4295 appearances, as presented in Table 4. Notably, the occurrence of single-authored documents within the dataset is relatively limited, encompassing only 54 out of the 1127 analyzed documents. This paucity of single-authored documents can be attributed to the inherent complexity of the examined domain, particularly when endeavors involve the fusion of transportation and ABMs. This supposition finds support in the number of authors affiliated with multi-authored documents, which totals 3340, a figure in close proximity to the total unique author count. It underscores the collaborative nature of research within this domain, where scholars frequently collaborate to navigate its intricate terrain. Table 5 provides insights into author collaboration patterns. Among the documented statistics, there are 56 single-authored documents, a number closely aligned with the count of authors contributing to single-authored documents, which stands at 54. This implies that single authors, on average, have published approximately 1.03 documents each. Examining the metric of documents per author, we observe a value of 0.332. This figure can be attributed to the comparatively larger number of authors in relation to the total published articles, resulting in a modest average authorship contribution per document, with each author, on average, contributing to less than one article. For documents involving two or more authors, the metric co-authors per document registers at 3.81, while the collaboration index is calculated at 3.12. These values align with expectations for domains as intricate as transportation and ABMs, which typically necessitate the collective expertise of multiple specialists, thus reflecting a normative level of collaboration. Figure 3: Annual average article citations per year evolution.
## 3 Results  
### Screening of Lipase and Mesoporous Molecular Sieves  
To identify the optimal free lipase and immobilized carriers, different free lipases including CALB, AYS, PS, CSL, AY400 SD, and mesoporous molecular sieves (e.g., MCM-22, MCM-41, and MCM-49) were screened based on their performance for enzymatic deacidification. As shown in Figure 1a, compared to the free lipases such as AYS, PS, CSL, and AY400 SD, which had little effect on enzymatic deacidification, lipase CALB effectively reduced the acid value of rapeseed oil from 15.2 mg KOH/g to 2.7 mg KOH/g in 3 h. The catalytic capacity of lipase CALB in oil deacidification was also confirmed by [PERSON] et al. [43], who reported that the lipase CALB showed better performance in the enzymatic removal of FFA from high-acid rice bran oils, compared to the results achieved by other lipases such as Candida rugosa lipase, Lipozyme TL IM and Lipozyme RM IM [46]. The higher catalytic capacity of lipase CALB is mainly attributed to the serine residue in CALB, which can interact with the carbonyl group in FFA to form a complex between the acyl group and the enzyme, while the hydroxyl group in the glycerol will further react with the carbonyl group of the formed complex, leading to the re-release of serine residue for next round of reaction while the esterification reaction occurs [47; 48]. Thus, lipase CALB is selected as the optimal biocatalyst for enzymatic deacidification for rapeseed oil.  
Moreover, the catalytic performance of immobilized CALB based on different mesoporous molecular sieves was also compared. It is noted that the acid values of rapeseed oils were gradually decreased from 15.25 mg KOH/g to 5.2 mg KOH/g, 4.52 mg KOH/g, 7.21 mg KOH/g by the immobilized lipase based on MCM-22, MCM-41 and MCM-49,  
Figure 1: Screening of (**a**) different lipases and (**b**) carriers of mesoporous molecular sieves based on the enzymatic deacidification of rapeseed oil. The reactions were conducted in conditions with 10 g of high-acid rapeseed oil, 1 g of glycerol, 1 g of 4 Å molecular sieve, and 0.5 g of free enzyme/immobilized enzyme at 50 \({}^{\circ}\)C reaction temperature.  
respectively (Figure 1b). MCM-41 facilitated the immobilized CALB with higher deacidification, this is mainly related to its internal topology [49]. As shown in Table S1, the surface area of MCM-41 is 1439.3 m\({}^{2}\)/g, which is apparently higher than 440.5 m\({}^{2}\)/g and 1102.2 m\({}^{2}\)/g for MCM-22 and MCM-49, relatively. The higher surface area can promote lipase immobilization and subsequent contact between lipase and substrates [50]. Moreover, the proper pore size of 3.5 nm makes MCM-41 an ideal carrier to accommodate the lipase CALB and prevent it from leakage or damage during the stirring reaction. Hence, MSM-41 is screened and used for lipase CALB immobilization in the following experiments.
# A Service-Constrained Positioning Strategy for an Autonomous Fleet of Airborne Base Stations
## 6 Evaluation and Results
### Energy Consumption Evaluation
In the second and the third non-static scenarios, where the users move, the UAVs that have moved fastest in forward flight are the ones close to the peak density of users, which are E (black), F (blue), H (gray) and I  
Figure 9: Power consumption models as a function of velocity. (green), as near the peak of users the amount of moving users is higher. Therefore, it implies a higher impact on their associated UAVs and, as a consequence, higher displacements. Figure 10: Evolution of the individual energy consumptions vs the numbers of iterations for: one UAV decays (**top**); displacement of users (**center**); and scattering of users (**bottom**). Each color in the figures represents one UAV using the same colors as the ones assigned to letters in the previous figures in this section. Moreover, by comparing the consumptions, two conclusions can be extracted. On the one hand, it can be concluded that the autonomy of the selected UAVs in the evaluated scenarios is very low. Thus, either rotary-blade UAVs with a higher autonomy should be selected, which are difficult to find, or a strategy to replace the UAVs without the loss of rate observed in the first non-static scenario should be developed. On the other hand, taking into account that the iteration time is 0.3 s, it can be seen that the duration of the battery of each UAV is approximately between 5 and 20 min depending on the maneuvers, which agrees with the specifications of the selected UAV [38] taking into account the high altitudes and the payload (2 kg).
## 3 System Model
### Latency Analysis  
In the downlink power-domain communication scenario in TI, latency can be defined as the delay incurred when the signal (ts) is transmitted from the BS until it is received by users (\(U_{1}\), \(U_{2}\),..., \(U_{N}\)). This latency includes delays such as transmission delay, propagation delay, queuing delay and processing delay.  
The transmission delay (\(D_{T}\)) is the time required to transmit data packets over the communication channel. This delay considers the sum rate (Equations (15) and (16)) or set target rate (Equation (17)) of users and the amount of data to be sent (packet size). Thus, \(D_{T}\) is given by  
\[D_{T}=\frac{Packet\;size\;in\;bits}{Transmission\;rate\;in\;ps} \tag{21}\]where transmission rate = sum rate in (\(\rm{bps}/\rm{Hz}\)) \(\times\) system bandwidth (\(\rm{Hz}\)).  
Moreover, the propagation delay (\(D_{P}\)) is the time required for the data packets to travel the physical distance between the BS and the user. This delay also relies on the transmission rate of the signal and thus is given by  
\[D_{P}=\frac{Distance\ between\ the\ BS\ and\ the\ user\ in\ metres}{Speed\ of\ light\ in\ m/s} \tag{22}\]  
where speed of light = \(3\times 10^{8}\) m/s.  
The queuing delay (\(D_{Q}\)) is the time required to wait in queues at the BS before data packet transmission. This delay may arise due to network congestion or scheduled multiple users based on channel conditions. On the other hand, the processing delay (\(D_{P}\)) is the time required to process superposition coding (multiplexing) at the BS and SIC decoding at the receiver's side.  
Hence, the overall latency (\(L\_overall\)) for a particular user will be given by  
\[L\_overall=D_{T}+D_{P}+D_{Q}+D_{P} \tag{23}\]
# Accelerate Incremental TSP Algorithms on Time Evolving Graphs with Partitioning Methods
## 2 Background and Related Work
### Traveling Salesman Problem  
TSP is a well-studied problem in the field of graph computing. It has various applications in computer science and operation research. Hence, finding an optimal solution for TSP is challenging. In order to find a global optimal solution, various metaheuristic algorithms have been proposed. These algorithms are: \((1)\) Genetic algorithm [13; 25], which finds fittest individuals that can generate new offspring in every generation, \((2)\) Simulated annealing [26], which finds approximate solution using the probabilistic technique, and several others such as \((3)\) Ant Colony Optimization [27], \((4)\) Particle Swarm Optimization [28], and \((5)\) tabu search [29]. Hybrid algorithms [30] are even well studied in the literature, and they can further improve the accuracy and efficiency. There are many versions of the TSP algorithm. Three of them are Generalized TSP (G-TSP), Multiple TSP ( M-TSP), and Clustered TSP (C-TSP). In GTSP [9; 10; 11], the nodes of a complete undirected graph are partitioned into clusters, and the objective is to find a minimum cost tour passing through exactly one node from each cluster. Multiple TSP (MTSP) [12] consists of more than one salesman, and each salesman visits an exclusive set of vertices. In C-TSP [8], the group of cities must be visited contiguously in optimal and unspecified order. The real-world warehousing problem is an example that fits this problem definition. Many researchers [31] have also used the divide and conquer strategy to solve various applications of TSP. The main idea is to divide the solution space into sub-problems and then solve each sub-problem independently in parallel. In the current work, we have used the divide and conquer strategy to partition the graph and compute a TSP tour on only the affected partition.
# ECC: Passenger Counting in the Elevator Using Commodity WiFi
## 3 Materials and Methods
### Multi-Dimensional Feature Extraction
#### 3.5.1 Amplitude Feature  
Though the number of signal propagation paths in the elevator gradually reduces as the passenger number increases and the received vector becomes weaker, the variation range of CSI becomes narrow. Hence, the CSI amplitude can not directly be used to characterize the relationship between the people number and the variation of CSI. The AOA is defined to denote the received amplitude of CSI, which is the average value of all PCs after noise filtering. By averaging the PCs, the amount of frequency information of CSI can be obtained as the PCs are orthogonal to each other, and each of them consists of unique frequency components [30]. Moreover, this method can reduce human interference, and the relationship between the variation of CSI and the crowd number can effectively be reflected. The AOA is expressed as:  
\[AOA=\frac{1}{MN}\sum_{j=1}^{M}\sum_{i=1}^{N}A_{ij} \tag{12}\]  
where \(A_{ij}\) is the CSI amplitude, \(N\) is the length of CSI, and \(M\) is the number of PCs. The average AOA values of two Rxs with 10 experiments under each passenger number are shown in Figure 6. The AOA value gradually decreases as the passenger number increases. However, the variation of AOA becomes weak as the passenger number grows. Hence, more proper quantifiable indexes are required to verify the relationship between the people and the variation of CSI in a short time.  
Figure 5: De-noising the PCs of 4 persons (a 4-level db3 wavelet).  
Figure 6: AOA and TVS value under different passenger numbers.
## 2 Literature Review
### Smart Cities  
Smart cities harness digital technologies to enhance urban living and streamline municipal services [49; 50]. Central to this evolution is the IoT, which facilitates real-time data collection and analysis, enabling cities to monitor infrastructure, manage assets, and respond proactively to community needs [51]. However, challenges such as data security, transparency, and privacy persist. While blockchain has been explored to address these issues [52], its limitations in scalability and energy efficiency prompt the exploration of alternative solutions [49; 52; 53].  
Holochain emerges as a compelling alternative, where its architecture supports various applications, including secure data sharing among city departments, transparent citizen engagement platforms, and efficient management of urban resources. Its resilience to inconsistent connectivity ensures reliable operation even in environments with variable network conditions. By enabling secure, transparent, and efficient data exchange, Holochain contributes to the development of sustainable and responsive smart city infrastructure, fostering greater trust and collaboration among stakeholders.
# Surface-Modified Ceramic Boron Carbide as a Platform for Specific Targeting in Tumour Environments
## 3 Results
### Zeta Potential  
The adsorption of seven different modifiers (dextrin, dextran T50, T70, arginine, lysine, sorbitol) was studied by monitoring changes in the electrophoretic mobility (zeta potential) of boron carbide particles induced by this process. The experimental procedure consisted of following steps:  
* The zeta potential of bare boron carbide particles in suspension with a concentration equal to 100 mg L\({}^{-1}\) was measured,
* Modifier covered boron carbide particles were formed in situ by filling the cell with the modifier suspension of an appropriate concentration for 10 min. After that, the electrophoretic mobility of the new complex was measured using electrophoretic methods.  
As can be seen in Figure 1a-c, in all cases, the zeta potential of boron carbide increases monotonically with the modifier concentration. The zeta potential value varied considerably up to a certain point, at which point the value stabilised.  
Figure 2a-c shows the zeta potential changes for modifiers, such as sorbitol, arginine, and lysine. For sorbitol and amino acids, slight changes in the zeta potential of the formed complex were observed. However, low zeta potential values suggest the formation of a more stable suspension.
# Sentiment Analysis of Arabic Course Reviews of a Saudi University Using Support Vector Machine
## 3 Contributions  
To the best of our knowledge, there is currently no attempt to develop a sentimental analysis system for high education students using Arabic text. This is an important gap in the literature as there is a need to understand the perceptions and opinions of students in Saudi Arabia Universities regarding their education beyond COVID-19. Developing such a system would provide valuable insights into the challenges and obstacles faced by Arab students during online learning and help to improve their educational experience. The main contributions of this study include:  
1. The proposed SVM Sentimental Analysis for Arabic Students' Review called SVM-SAA-SC algorithm for students' Arabic course reviews is a general framework that involves collecting student reviews, preprocessing them, and using a machine learning model to classify them as positive, negative, or neutral.
2. The suggested technique for preprocessing and classifying reviews includes steps such as collecting data, removing irrelevant information, tokenizing, removing stop words, stemming or lemmatization, and using pre-trained sentiment analysis models.
3. To train the classifier, SVM algorithm is used, and performance is evaluated using metrics such as accuracy, precision, and recall.
4. Fine-tuning is done by adjusting parameters such as kernel type and regularization strength to optimize performance.
5. The use of a real dataset provided by the deanship of quality at PSAU, which is ranked 801-900 globally and 6 th in Saudi Arabia according to the 2022 Shanghai Rankings.
6. The dataset contains students' opinions on various aspects of their education, including courses, faculties, assignments, projects, and exams.
7. To validate the suggested SVM-SAA-SC algorithm, a comparison with a sentiment analysis tool called CAMeLBERT Dialectal Arabic model (CAMeLBERT-DA SA Model) [30] is adopted. CAMeLBERT represents an interplay of variant, size, and task type in Arabic pre-trained language models.
8. The use of textual comments instead of grading-based feedback to reveal the exact sentiment of students.  
The proposed model provides insights about education at PSAU and contributes to improving the quality of teaching at PSAU.
## 2 Literature Review
### Evacuation in Emergency Management  
The evacuation processes are divided into pre-travel and actual travel phases [11]. In emergency conditions, both the preliminary stage and immediate action once the emergency event has started are key to minimizing irreversible consequences. In [14], a new assessment method for evacuations in limited spaces such as cruise ships was proposed by presenting a risk assessment model. In this case, most passengers do not have previous preparation for emergency actions; therefore, verifying mass behavior in evacuation instances is relevant. Other situations in confined spaces are also essential for assessing evacuees' decisions as a survival reaction [2; 17]. Although evacuation scenarios have been studied to optimize plan implementation and execution, they still lack representation of human behavior in detail, limiting their scope to engineering solutions. For example, a staggered evacuation is proposed in [18] to improve speed, safety, and functionality. This model uses the total evacuation time, degree of exposure to a catastrophic event, and congestion generated as the primary factors. However, it does not include the behavioral patterns of particular groups of people or individuals, which may affect the actual results of the plan.
# Noble Metal-Based Heterogeneous Catalysts for Electrochemical Hydrogen Evolution Reaction
## 4 Noble Metal-Based Heterogeneous Catalysts
### Alloying Strategy
#### 4.1.1 Pt-Base Alloy  
At present, commercial Pt/C catalysts are still the most widely used catalysts for the HER. In order to improve the catalytic performance of Pt, a series of Pt-based alloy catalysts have been developed. Pt can be alloyed with different precious metals such as Pd [59], Ru [60], Au [61] and Ag [62], but the high cost is not favorable for large-scale commercialization. To address the cost problem, alloying Pt with non-precious metals such as Fe [63], Co [64], Ni [65], Cu [66] and Ti [67] has also been extensively investigated. The d-band center theory mentioned above shows that the distance of the d-band center relative to the Fermi level is closely related to the adsorption energy. Alloying Pt with transition metals (Co, Fe, Ni and Cu) will cause the d-band center of Pt to downshift and weaken the adsorption energy of oxygen-containing (OH*) on the surface Pt atom. [PERSON] and co-authors have calculated a \"volcanic\" relationship between the d-band center of a bimetallic alloy and the chemisorption of catalyst surface molecules [29]. [PERSON] et al. [68] prepared bimetallic nanoparticles with different compositions and structures, obtained dealloyed samples using pickling, and then prepared bimetallic samples with platinum \"skin\" using annealing (PtCo sample in Figure 5a). Taking the alkaline HER (in 0.1 M and 1 M KOH, respectively) as an example, the linear relationship between the d-band vacancy and the \(j_{0}\) was established (Figure 5b,c). The results showed that most of the alloy materials with a thin Pt skin showed strong catalytic activity, while the dealloyed PtCo and PtFe did not follow the linear relationship and showed higher activity. Selective optimization of the adsorption properties of H* and OH* intermediates is the key to improving the HER activity, and dealloying to enhance the surface atomic activity is undoubtedly a successful strategy.