esa-sceva/satcom-chunk-collection huggingface dataset:
# Generalized Electron Emission Theory for One-Dimensional Conducting Materials
## 4 One-Dimensional Field Emission  
In a metal, free electrons adhere to a Fermi-Dirac distribution. Concerning field emission, the current density in a one-dimensional conductor is as follows:  
\[J_{1D}=e{\int_{0}^{E_{F}}dv_{x}v_{x}n_{1D}(E_{x})D(E_{x})}, \tag{20}\]  
where \(v_{x}\) represents the \(x\)-directional velocity of electrons, \(E_{F}\) signifies the Fermi energy, \(n_{1D}\) denotes the one-dimensional density of electrons, and \(D\) represents the tunneling probability. \(D(E_{x})\) signifies the probability of tunneling, indicating the likelihood that an electron with energy \(E_{x}\) traverses into a vacuum through the potential barrier.  
Figure 1 depicts a schematic representation of one-dimensional field emission, show-casing the application of the \(x\)-directional electric field to the conducting material. The  
electron tunneling probability \(D\) for the conductor exposed to a steady electric field is provided by [9]  
\[D=(\frac{4\sqrt{E_{x}}\sqrt{E_{F}+\Phi_{w}-E_{x}}}{E_{F}+\Phi_{w}})e^{-4k(E_{F}+ \Phi_{w}-E_{x})^{3/2}/3F}, \tag{21}\]  
where \(k=\sqrt{\frac{8\pi^{2}m}{H^{2}}}\) signifies the electron wave number, \(E_{x}\) denotes the electron energy along the \(x\)-direction, \(\Phi_{w}\) represents the work function of the metal, and \(F\) signifies the accelerating field to the metal. The electron tunneling probability described by Equation (21) is contingent on the Fermi energy, work function, and accelerating electric field.  
Particles cannot tunnel in classical mechanics when there is a potential barrier. Electrons can participate in quantum tunneling in quantum mechanics when the potential barrier thickness is comparable to the wavelength of the electron. The electron having the highest energy occupied by the Fermi energy can go through the potential barrier under a strong electric field in which the emitted electron energy is the same as the Fermi energy. This is called field emission because electrons under a strong electric field participate in quantum tunneling in metal.  
Figure 1: Diagram illustrating generalized electron emission in one-dimensional materials. An accelerating field is directed along the \(x\)-axis and applied to the metal. Thermally excited electrons with energy levels surpassing the vacuum threshold engage in thermionic emissions. Electrons experiencing a strong electric field, with energy levels below the vacuum threshold, partake in quantum tunneling, constituting the generalized field emission.  
function with density function theory showed that carbon nanotubes allow the flow of currents of a few micro-amperes for a few volts [29].
## 1 Introduction
Recent studies have also demonstrated the low cytotoxicity of the hydroxylatedGd\({}_{3}\)N@C\({}_{80}\)(OH)\({}_{\rm n}\) system in a cell viability study of hen brain and human neuroblastoma SH-SY5Y cells [33]. Overall, these reports demonstrated that fullerenes have low systemic toxicity and ameliorate inflammatory responses due to radical and ROS scavenging properties [22; 23; 24; 29; 31; 32]. Furthermore, the ease of surface functionalization and ability to use the versatile metallofullerene platform as the basis for multiple imaging agents makes it an ideal candidate for multi-modality imaging applications. Altering the endohedral metal is the basic method for endowing additional imaging properties to the fullerene. Examples of this include encapsulation of Gd or Gd\({}_{3}\)N for superior MRI contrast [34; 35], Lu\({}_{3}\)N for x-ray contrast [36], and \({}^{177}\)Lu for SPECT detection [37]. External ligands have also been added to empty C\({}_{60}\) cages to provide x-ray contrast [38; 39] and radiolabeling [40]. Recent work has shown the imaging and therapeutic, or theranostic potential of f-Gd\({}_{3}\)N@C\({}_{80}\) nanoparticles externally labeled with \({}^{177}\)Lu in an orthotopic xenograft murine brain tumor model [41]. Therefore, there is clear potential for combining endohedral and exohedral components to yield a desired multi-modal nanomaterial imaging agent. The current study describes the synthesis and initial _in vivo_ imaging demonstration of a metallofullerene-based nanoplatform for combined PET/MRI. Two other dual probes for PET/MRI have recently been reported, both of which utilize T\({}_{2}\) MRI contrast agents (iron oxide based) [13; 14; 42]. The agent presented in this work offers T\({}_{1}\) MRI contrast and affects T\({}_{2}\) sufficiently to provide T\({}_{2}\)-weighted imaging as well.
## 5 Proposed Framework
### ZTA Design
#### 5.1.3 Micro-Segmentation
At the Application Layer, the security policies governing communications between xApps and other O-RAN components are defined by the A1 and E2 interface specifications, which are critical for ensuring the safe and controlled interaction between trusted and untrusted components. Figure 4: Micro-segmentation architecture showing (**A**) the Core Zone with SMO and RICs, (**B**) the Controlled Zone for third-party xApps, and (**C**) the Quarantine Zone for compromised components. Security controls are shown for each zone with interface-specific policies. The implementation of this micro-segmentation framework has resulted in a significant reduction ofinattack surfaces by approximately 72% compared to traditional, flat O-RAN deployments, as demonstrated by our testbed results (see Section 7). Moreover, the framework's policies are not static but are dynamically updated in real time through the SMO's policy management interface, allowing for a rapid adaptation to emerging threats. This dynamic nature of the micro-segmentation approach enables a highly responsive security posture, capable of mitigating risks within a mere 200 milliseconds.
# A Survey of GIS and IoT Integration: Applications and Architecture
## 3 GIS and IoT Integration Use Cases  
Nowadays, GIS and IoT-based systems are not only at developers' center of attention but also at officials' and organizations [26; 27; 28; 29]. With the wide range of applications provided by these integrated systems [19; 25], they are being used in many aspects including urban and rural developments.  
Various related literature studied on the application of integrated GIS and IoT systems is discussed in this section. In addition, these studies were categorized into seven groups indicated in Figure 1.  
As it is shown in Figure 1, Urban Infrastructure mostly including smart city-related studies has been the most frequent domain of applications [8; 26; 29; 30]. Environmental Monitoring and Utilities shared the same frequency of 16% [28; 31; 32]. On the other hand, less attention was paid to the Healthcare industry in GIS and IoT integrated point of views [33]. These industry shares can be compared with the estimated market share of IoT applications by 2025 [1] in which Healthcare is projected to have the most economic influence. Therefore, it would be a great opportunity to focus on the Healthcare industry to use the great functionality of GIS simultaneously with IoT.  
Some of the studies in each category are discussed in the following sub-sections.  
Figure 1: Industry share of GIS and IoT integrated applications.
# An Approach to Trustworthy Article Ranking by NLP and Multi-Layered Analysis and Optimization
## 4 Methodology
### BERT Embedding and Similarity Comparison  
In our approach to semantic text analysis, we employ the BERT model, a popular method in NLP, to generate dense vector representations of both user queries and academic articles. The bidirectional nature of BERT allows it to consider the full context of each word, making it particularly effective for understanding complex academic text and technical terminology.  
We specifically selected the \"BERT-base-uncased\" model over other available variants for several reasons. First, we chose BERT-base over BERT-large because the latter's 340 M parameters (compared to BERT-base's 110 M) would significantly increase computational overhead without proportional performance gains for our similarity task. Second, we opted for the uncased version because academic abstracts often contain inconsistent capitalization patterns, and treating terms like \"Machine Learning\" and \"machine learning\" as equivalent is more appropriate for semantic similarity matching. Finally, while domain-specific variants like SciBERT exist, BERT-base-uncased provides better generalizability across multiple academic disciplines, which aligns with our cross-domain article retrieval system.  
In our work, the selected \"BERT-base-uncased\" model creates 768-dimensional embeddings that effectively capture the semantic relationships within the text. The initial  
Figure 1: Detailed steps in the three-layer architecture of our proposed system for the trustworthiness ranking and recommendation of academic articles.  
step involves concatenating each article's title and abstract into a unified text string before generating the embedding. This approach ensures that the full topic and context of the article are captured in the vector representation.  
After generating BERT embeddings for both the user queries and the articles, we implement a similarity comparison using cosine similarity measurements. Cosine similarity serves as an effective metric for comparing high-dimensional vectors as it measures the cosine of the angle between two vectors, producing a normalized similarity score ranging from \(-1\) to \(1\). A score of \(1\) indicates perfect similarity, while lower scores suggest decreasing degrees of semantic relevance. This normalization makes the metric particularly suitable for comparing texts of different lengths. In our implementation, we select the top 10% of articles with the highest cosine similarity scores for further analysis and refinement. This filtering step ensures that we maintain a manageable set of highly relevant articles while retaining enough diversity for subsequent analysis stages.
## 4 Discussion
Future studies should aim to confirm these findings. It is crucial for athletes to possess both psychological readiness and functional ability when returning to sport competition to minimize the risk of re-injury. Assessing certain factors, such as re-injury worry, confidence, and attention, in previously injured athletes and identifying significant correlations with functional tests can aid the rehabilitation team in enhancing performance and reducing re-injury risks upon return to sport. The clinical significance of these findings lies in improving athletes' preparation and performance after an injury. Rehabilitation teams can utilize reliable psychometric instruments, like the questionnaires employed in this study, to evaluate these psychological characteristics before athletes resume competition. Early identification of re-injury worries, as well as levels of confidence and attention at the start of the season, allows for targeted interventions. Athletes exhibiting high levels of re-injury worry or reduced confidence and attention may benefit from tailored psychological support programs and might be advised to gradually reintegrate into competition while avoiding particularly challenging games initially. Proactively addressing these factors can help prevent further injuries throughout the season, leading to decreased absence from training and competitions and ultimately maximizing athletic performance. This study has several limitations that warrant consideration. As a cross-sectional study, it provides a snapshot of the relationships between variables at a single point in time. Consequently, the generalizability and causality of the results should be further explored through additional multicenter and longitudinal studies. Other limitations include the heterogeneity in injury duration and the variability in both the duration of rehabilitation programs and the length of absence from sport. Additionally, the study did not investigate whether athletes who received medical treatment exhibited better psychological readiness. Future research should focus on examining differences in re-injury worry, confidence, and attention across various demographic characteristics, such as gender, athlete categories, and among those who have returned to their preinjury level. Further studies could also explore the relationship between re-injury worry, confidence, and attention in athletes recovering from acute versus chronic injuries. Additionally, comparing these psychological factors in athletes who have received medication or undergone surgical treatment for musculoskeletal injuries would provide valuable insights.
###### Abstract  
Prefabricated concrete hollow slab bridges are widely used in short- and medium-span highway bridges in China due to the advantages of high production quality, installation convenience, and low construction cost. Field investigation shows that severe hinge joint damage occurred during the service life, and mechanical performance of the bridges also deteriorated with the weakened joints. It is important to accurately evaluate the performance of hollow slab bridges to ensure the safety of the highway system. In this paper, transverse connectivity and durability of the concrete hollow slab bridges are investigated in a field test using the surface damage and neural networks. Hollow slab bridges in the Wu-He highway system were taken as the background bridge. Surface damage was visually checked and statistically analyzed. Static load test was conducted to evaluate the transverse connectivity of the hinge joints based on the girder responses. The hollow slab bridges were then demolished, and a total of 75 concrete girder segments were cut off. Durability of the girders was evaluated based on the conditions of concrete and rebars, and the analytic hierarchy process along with the fuzzy comprehensive evaluation method was employed. Results showed that there were two main types of the defects in the hollow slab bridges, i.e., the transverse cracks on the bottom plates of the girders and the longitudinal cracks in the hinge joints. The distribution of the deflection of each girder was non-uniform due to the weakening of the transverse connectivity, and the girders in the background bridges were within the moderate deterioration condition after 25 years' service life. An evaluation method of the hollow slab girders using the neural networks and surface damage was verified by the field test data. The maximum crack width at different locations of the bridges was used in the input layer of the neural network, and the hinge joint damage or the durability was considered as the output results. The prediction error of the method in the test set was within 15.0% for the hinge joint damage and within 40% for the durability result of the girder, indicating the feasibility of the evaluation method.  
hollow slab; RC bridge; durability evaluation; joint damage; visual inspection; neural network +
Footnote †: journal: Applied Sciences
# A Deep Learning Approach for Automatic Hate Speech Detection in the Saudi Twittersphere
## 4 Experiment Setup
### Data Preprocessing  
Before feeding the tweets as an input to the classification models, we firstly applied several pre-processing steps on both testing and training datasets. Pre-processing is a vital step when dealing with data that has a noisy and colloquial nature such as Twitter. This becomes even more important for the Arabic language, given its inherited ambiguity and the high variety of the used dialectal Arabic in Twittersphere. We applied several preprocessing steps to our data before feeding them as input to our experimented models. Steps include:  
**Hashtag removal:** This step was taken to avoid any bias toward certain classes; we dropped any hashtag used as a keyword search while collecting the data from the tweets.  
**Spam filtering:** In this step, we implemented the rule-based algorithm proposed in [30] to filter spam. We used the same spam lexicon created by the authors and extended it with new terms and hashtags that we found to be highly associated with spam tweets.  
**Stop words removal**: In this step, we used a list of 356 stop words that were made publicly available by [12] on GitHub [31].  
**Emoji description**: A recent work on irony detection and sentiment analysis of tweets published by [PERSON] et al. [32] showed that replacing emojis with their textual description is more effective for tweet classification than using other strategies such as using pretrained emoji embeddings or treating emojis as regular tokens. Motivated by this work, we used demoji [33], a python library that provides utilities to replace emojis with their description. This library utilized readily available lists of emojis and their textual descriptions in English [34]. For our task, we translated the list into Arabic by Google translator API [35]. Then, the produced translations were manually revised and updated. The translated list was used with demoji to replace emojis in tweets with their Arabic textual description.  
**Cleaning**: In this step, punctuation, additional whitespaces, diacritics, and non-Arabic characters are removed.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Hate Speech Type** & **Example of Terms/Hashtags** \\ \hline
**Racist** &
\begin{tabular}{c} _“jam j  
**Normalization**: The goal of this step is to reduce orthographical variations observed in tweets as well as normalizing Twitter-specific tokens. The normalization steps are as follows:  
* Different forms of \"\(|\)\" (\"\(|\)\", \"\(|\)\", and \"\(|\)\") were replaced by \"\(|\)\".
* \"\(\zeta\)\" is replaced by \"\(\zeta\)\".
* Links and mentions are replaced by \"mention\" and \"URL\", respectively.  
**Lemmatization:** We applied this step using the Farasa stemmer [36]. We selected Farasa on the basis of a study by [PERSON] et al. [37] that showed that Farasa outperformed other tools such as MADAMIRA.
# Implementation of an IoT Based Radar Sensor Network for Wastewater Management
## 6 Background
### Radar Operating Principles
#### 6.1.2 FMCW Radar  
An FMWC radar however, emits a continuous waveform whose frequency increases linearly during the measurement phase, known as a frequency sweep. Its frequency is modulated, generally in a saw tooth pattern to distinguish between signal peaks. Figure 25 below shows the general principle of a FMCW radar measurement technique.  
At any given time, the known slope of the saw tooth pattern, m, is given by:  
\[\mathrm{m}=\Delta\mathrm{f}/\Delta\mathrm{t}, \tag{3}\]  
Hence, from (3), the time delay can be calculated as:  
\[\Delta\mathrm{t}=\Delta\mathrm{f}/\mathrm{m}, \tag{4}\]  
Furthermore, this frequency difference \(\Delta\mathrm{f}\) is calculated using a Fast Fourier transform (FFT). The difference is directly proportional to the distance of the medium away from the radar device, and is calculated from the FFT frequency spectrum.  
The frequency of this wave is precisely modulated in the form of a sawtooth signal between two limit frequencies \(f_{1}\) and \(f_{2}\):  
Figure 24: Pulse radar measurement principle.  
Figure 25: FMCW radar measurement principle.  
For these specific applications, a radar device with high performance accuracy, minimal beam angle and low power supply requirements is essential. Figure 26 below shows the effect of radar beam angle on the beam width diameter at varied medium distances.  
The deepest sewer manholes within Shoalhaven Water's network are 5 m in depth which, with a beam angle of 3\({}^{\circ}\), translates to a beam width diameter of approximately 260 mm. Compared to beam angles of 10+\({}^{\circ}\), significant sections of both the gravity main pipe edges as well as manhole walls will be reflected.  
Whilst most gravity sewer mains are approximately 150 mm in diameter, at maximum medium distance more than half of the radar beam is still reflected off the actual medium rather than sewer main and manhole walls. Once sewer levels are above the 150 mm main, water begins to vertically fill the 1500 mm diameter manhole. The VEGA VEGAPULS 64 [16] radar has been chosen, as it has the lowest power requirements but also the highest signal frequency, hence resulting in the smallest beamwidth and most accurate measurement. The PULS 64 also offers built in false signal suppression where others do not.
# Temporal Changes in Land Use, Vegetation, and Productivity in Southwest China
## 1 Introduction
In addition, according to long-term remote sensing vegetation data, it is found that short-term extreme climate events respond differently to different land-use types, resulting in differences in regional ecological effects [38; 39]. Therefore, it is of great significance to understand the temporal and spatial pattern characteristics and change processes of different LULC types, vegetation dynamics, and gross primary productivity in the region for correctly understanding the temporal dynamic changes and spatial changes in regional vegetation dynamics and gross primary productivity. The changes in vegetation and productivity center can reflect the evolution of ecosystems influenced by human activities and climate change. Human activities affect vegetation and productivity changes, such as ecological engineering, which increases vegetation growth and carbon storage in southwest China [40; 41], and positively contributes to vegetation productivity [42]. However, the expansion of arable land and the surge in population has also led to the degradation of vegetation [15]. Deforestation reduced the GPP and leaf area index in China between 1982 and 2011, and their centers of gravity shifted [43]. The spatial and temporal changes in vegetation cover and productivity in different regions have obvious uncertainties [6; 44; 45]. Natural evolution is also an important factor leading to the migration of its center of gravity; for example, the northward shift of the climatic zone makes the ecological center of gravity move northward [46; 47]. In summary, combined with different LULC types, studying the temporal and spatial variation patterns of different levels of vegetation cover (NDVI) and its gross primary productivity (GPP) in southwest China can deepen the understanding of vegetation and productivity changes in southwest China. It has very important ecological value and practical significance for the balance and sustainable development of the ecosystem. The purpose of this study is to clarify the temporal and spatial dynamic of LULC, vegetation cover, and GPP in southwest China and the migration pattern of the center of gravity. Combined with MODIS remote sensing, we analyzed the temporal and spatial changes of vegetation cover (NDVI) and gross primary productivity (GPP) under different LULC types in southwest China. Therefore, our aims in the study are: (1) to clarify the migratory direction of LULC in southwest China and the spatial and temporal change patterns of NDVI and GPP in the growing season; (2) to explore the change characteristics of GPP under different land use types and different vegetation coverage levels; (3) to analyze the migration law of vegetation cover and GPP center of gravity.