esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Proposed Scheme for Prosumer-Based Energy Sharing
### Problem Formulation
These criteria urge users to generate more energy, be active participants in energy sharing and keep the selling price at its lowest possible value. Note that these incentives are based on the assumption that more renewable energy is needed. When the production reaches to a certain limit, the incentives will have to be changed accordingly. We define a variable \(\rho^{t}\) to represent \(t\)th priority criterion. Based on the proposed priority criteria, the problem is reformulated as:  
\[\min\sum_{n=1}^{N}w\zeta_{nj}x_{nj}-\Phi_{nj}xr_{nj}\text{ }\forall\text{ }xr_{nj}\
eq xs_{nj} \tag{8}\]  
Subject to  
\[\sum_{n=1}^{N}\Phi_{nj}xr_{nj}\leq\psi r_{mj}\left(\rho^{t}\right)\text{ } \forall\text{ }\psi r_{mj}\
eq\psi s_{mj} \tag{9}\]  
\[\psi r_{mj}\left(\rho^{t}\right)=\left\{ \begin{array}{ll}\psi r_{mj}\left( \max\left(\kappa_{mj}\right)\right),&if\text{ }t=1\\ \psi r_{mj}\left(\max\left(\Delta_{mj}\right)\right),&if\text{ }t=2\end{array} \right. \tag{10}\]  
\[0\leq w\leq 1\]  
where \(xr_{nj}\) and \(xs_{nj}\) are binary values and represent the inclusion or exclusion of the remaining and served users respectively. \(\psi r_{mj}\) and \(\psi s_{mj}\) are the shortage of remaining and served users respectively. \(\kappa_{mj}\) and \(\Delta_{mj}\) denote capacity and overall contribution respectively. The overall contribution has been defined as:\[\Delta_{mj}=P_{1}\alpha_{mj}-P_{2}\beta_{mj}+P_{3}\gamma_{mj} \tag{11}\]  
where \(\alpha\), \(\beta\) and \(\gamma\) are capacity, selling price and contribution of surplus energy respectively. A more comprehensive contribution factor, involving other possible parameters, may be used in future enhancements of this work. The weights \(P_{1}\), \(P_{2}\) and \(P_{3}\) represent the relative importance of above three criteria and take values from 0 to 1 such that:  
\[P_{1}+P_{2}+P_{3}=1 \tag{12}\]  
The effectiveness of the algorithm, with both single criterion and multiple criteria approaches, has been evaluated through extensive simulations. The test system and results have been presented in the next section. BIP has been used for optimization. BIP is the type of integer programming in which decision variables can take value of 0 or 1 only; in the proposed scheme, if there is a user's surplus energy available for sharing then the respective decision variable takes a value of 1, otherwise it is 0. The algorithm deals with shortages on hourly bases. However the execution time is very small (less than 10 s on a 1.80 GHz processor machine) and it can be run as frequently as required based on the availability of the updated surplus/shortage scenario. The frequency of running the algorithm also depends on communication speed between the controller and prosumers.
# Electro-Optic Sensor for Measuring Electrostatic Fields in the Frequency Domain
## 2 Method and Experimental Results
### Electric Field Measurements with an Electro-Optic Sensor  
The system is composed of two electro-optic (EO) crystals, made of Lithium Niobate (LiNbO\({}_{3}\)), and two polarizers arranged in a crossed-polarizers configuration. Large EO coefficients [2], as well as lower values of conductivity compared to the other EO materials [18], make LiNbO\({}_{3}\) the preferred candidate to be used for electrostatic measurements.  
To describe the sensor, we use the coordinate system shown in Figure 1.  
The \(z\)-axis is parallel to the optical axis of a uniaxial LiNbO\({}_{3}\) crystal. The refractive index along that direction is known as the _extraordinary index_ (\(n_{e}\)) and differs from the _ordinary index_ (\(n_{o}\)), which is exhibited by the material along any other direction perpendicular to the optical axis. This material property is commonly referred to as _birefringency_[2].  
Figure 2 presents a conceptual overview of an EO sensor for DC electric field measurements. A linearly polarized laser beam propagates in free space and traverses the entire optical chain. Using the aforementioned coordinate system, the laser beam propagates along the \(y\)-axis and oscillates in the perpendicular \(x\)-\(z\) plane.  
Figure 1: Coordinate system used throughout the paper.  
The first polarizer fixes the light's polarization at 45\({}^{\circ}\) with respect to the \(x\)-axis. As the laser beam enters the first crystal, two polarization components of the beam (orthogonal to the propagation direction) are unevenly phase-retarded due to the crystal's natural birefringence, resulting in a different polarization state at the output face of the crystal. The laser beam undergoes the same phenomenon in the other crystal.  
The second polarizer, set at \(-45^{\circ}\) with respect to the \(x\)-axis, filters out the component of the laser beam not aligned with its transparency window, translating the polarization state change into a laser power variation. At the end of the optical chain, a photodetector measures the output optical power.  
Because of the Pockels effect, EO crystal's refractive indices change linearly with the incident electric field. The relationship between the electric field and crystal's birefringence can be exploited to encode the incident electric field onto the polarization state of the laser beam traversing the crystals, resulting in an intensity modulation of the optical power.
## 4 Discussion
It is reiterated that DD can be considered a false negative diagnosis, and the clinical signs must be confirmed with imaging tests [43]. The condylar position is difficult to determine through clinical history alone; the only reliable method to assess it is through complementary radiographic examinations, such as computed tomography (CT) and MRI [44]. Patients with hypermobility and/or subluxation should confirm their diagnosis by avoiding pathologies such as alterations in the opening and closing of the mouth that, in the long term, can generate problems of joint adhesions or ankylosis [45]. According to preliminary studies, the prevalence of DDwR increases with age: the prevalence of symptomatic DD is approximately 6%, increasing in the population between 16 and 19 years of age [46]. Prevalence estimates in most of the included studies were obtained from children and adolescents registered with the Ministry of Education and the national health system, ensuring a diverse sample from public and private schools, as well as multicenter, randomly selected populations. It should be noted that the sample did not originate from orofacial pain treatment clinics to avoid potential data bias [47]. [PERSON]'s study included only children and adolescents and raised awareness of high rates of some specific types of TMD [18; 48]. Appropriate strategies for early and correct diagnosis are crucial for effective treatment management. Most cases are asymptomatic, with patients often reporting only mild discomfort due to joint noise. According to the literature, only a small proportion of affected adolescents seek treatment for the condition. When pain is present, it is typically exacerbated by activities such as chewing or other jaw movements [49]. Some dentists and specialists advise their patients that the symptoms generally resolve over time due to the natural and harmless progression of disc disorders, but cases of persistent symptomatology are a concern, where conservative non-surgical treatment is the main option [50]. In this review, the limitations identified include the scarcity of studies that report the psychological aspects of temporomandibular disorders. Although it has been established that errors in the diagnosis and progression of the disorder can be influenced by conditions such as headaches and depression, it is recommended that more studies be conducted that consider these factors. This systematic review examined the prevalence of temporomandibular disorders (TMDs) in children and adolescents aged 7 to 17. It focused on the presence of at least one sign or symptom, such as muscle pain, arthralgia or disc displacement, while comparing differences in symptom presentation across age groups. The findings showed a wide range of symptom prevalences, with muscle pain being the most common symptom (up to 31%) and disc displacement with reduction frequently observed in older adolescents (up to 14.4%) [51]. These results highlight the need to standardize diagnostic methods and consider factors like age in clinical assessments.
# A Robust Tracking Algorithm Based on a Probability Data Association for a Wireless Sensor Network
## 4 Experiment and Result Analysis
### Experimental Results  
In order to further verify the positioning accuracy of the proposed algorithm, we carried out experiments in a real environment. Ultra-wideband (UWB) technology was used to transmit signals between beacon nodes and a mobile node to obtain the range measurements. The time-based UWB positioning system makes use of the accurate TOA of the information exchange between devices [36] and has a high positioning accuracy. Therefore, in recent years, UWB has been widely used in indoor positioning. As shown in Figure 7a, there were six beacon nodes and a mobile node moved uniformly along the trajectory shown. In order to avoid the reflection of UWB signal from the ground, the mobile node was moved to 1.2 m above the ground. The room was 10 meters long and 7 meters wide. Because there were many obstacles in the room, the measurements were prone to be disturbed by NLOS factors, resulting in larger errors. Six beacon nodes sampled mobile nodes every 0.6 m for a total of 16 times. Each beacon node took 20 measurements at each sampling position, and the average value was taken as the final measurement.  
The initial state of the mobile node was set \(X(0)=\left[\begin{array}{cccc}1.2\,\mathrm{m}&1.8\,\mathrm{m}&0.6\,\mathrm{m/ s}&0\,\mathrm{m/s}\end{array}\right]^{T}\), the sampling period \(\Delta t\) was 1s, and other parameters were consistent with the simulation. The error distribution of each sample point is shown in Figure 7b, and the CDF of the localization error is shown in Figure 7c. Because there were some obstacles in the experimental environment, and the interference of NLOS factors was serious, the localization errors of the EKF and IMM-EKF were relatively large in most cases. Compared with the EKF and IMM-EKF, the localization errors of the MPDA and the proposed algorithm were smaller at most sample points, but the positioning accuracy of the proposed algorithm was slightly higher than that of the MPDA.  
Figure 7: (a) The deployment of beacon nodes and the true trajectory of the mobile node. (b) The localization error at each sample point. (c) The CDF of the localization error.
# Multilayer Bolometric Structures for Efficient Wideband Communication Signal Reception
## 3 Experimental Setup and Measurements; Results and Discussion  
### Experimental Setup and Measurements  
We have developed an experimental setup for the comparative analysis of experimental and numerical results, as shown in Figure 1. The central element of the experimental setup was a closed-type waveguide system with two ports for the supply and detection of electromagnetic radiation. To build a closed-type waveguide system, we used two coaxial waveguide junctions (CWJ) and a waveguide, the length of which is 50 cm; the internal size of the CWJ and the waveguide is 5.8 \(\times\) 2.5 cm, and the operating frequency range in the single-mode radio wave propagation regime is from 2.5 to 6 GHz. A vector network analyzer (VNA), S5085 [48], was used as a source and detector of electromagnetic radiation, with two CWJs connected to its ports. The VNA was calibrated with the coaxial cables (CCs) before the output of the coaxial cable connector using the 6550F18-F calibration standard kit (full two-port calibration) to eliminate the influence of the CCs on the input and detected electromagnetic radiation.  
Figure 1: An experimental setup with a closed waveguide system, a signal source and detector, and test samples.  
We measured the power of the electromagnetic radiation passing through the heterostructure (dielectric-semiconductor-dielectric-semiconductor) at the output of the CWJ port (left in Figure 1). The CWJ electromagnetic radiation was fed to another port (right in Figure 1). Fluctuations displayed on the VNA screen are associated with re-reflections of electromagnetic radiation within the waveguide and the occurrence of standing waves within the waveguide system.  
The heterostructure consisted of:  
(3) Two dielectric plates (polymer dielectric ST-16 with geometric dimensions of \(5.8\times 2.5\times 1.3\) cm, a dielectric constant \(\varepsilon_{d0}=16.1\), and a loss tangent \(tan\)\(\delta_{\varepsilon}=2\times 10^{-3}\)) as described in (3);  
(4) Semiconductor wafer (silicon doped with phosphorus having geometric dimensions of \(5.8\times 2.5\times 0.4\) cm and an average resistivity of \(49.5\)\(\Omega\)\(\times\) cm) as described in (4);  
(5) Semiconductor wafer (silicon doped with phosphorus having geometric dimensions of \(5.8\times 2.5\times 0.35\) cm and an average resistivity of \(17\)\(\Omega\)\(\times\) cm) as described in (5).  
It should be noted that our waveguide can only operate in the single-mode regime in the band \(f=2.6-6\) GHz, as \(3\) GHz is close to the limit and the multimode regime is found above \(6\) GHz.
# Investigating the Key Aspects of a Smart City through Topic Modeling and Thematic Analysis
## 5 Conclusions  
The concept of a smart city is about improving citizens' quality of life through advancements in information and communication technologies. A smart city is an interconnected system characterized by a high level of complexity. In this work, we investigated various aspects of the smart city paradigm to uncover its latent structure, yielding new prospects for the efficient administration of such a complex system. To accomplish this aim, we collected textual data from three distinct sources: scientific publication abstracts, news blog posts, and social media entries. For the analysis of this textual data, we devised a novel semi-automated methodology that incorporates topic modeling and thematic analysis. Our findings illustrate that the smart city domain is a complex system that must be examined and organized from three perspectives: applications, technology, and socio-economics. The analysis revealed ten themes/aspects of the smart city paradigm, including mobility, energy, infrastructure, environment, IoT, data, business, planning and administration, security, andpeople. When comparing the results from the three different datasets, we observed a lack of interest within the scientific community in certain aspects, such as business, as well as themes that are relevant to the everyday lives of citizens, including food, shopping, and green spaces.  
This work contributes to the literature in three ways: (a) It enhances our comprehension of the structure of the smart city paradigm by examining its various aspects; (b) it reveals latent smart city topics that need more attention from the scientific community, opening new avenues for research; and (c) it proposes a semi-automated methodology for the thematic analysis of very large corpora by using the BERTopic topic modeling library. The insights presented in this work hold significant implications for scholars, practitioners, and public administrators engaged in smart city transformation efforts. Furthermore, this article sheds light on the latent aspects within the domain that require attention from stakeholders. Essentially, our work addresses the phenomenon known as the \"two communities\" or the \"research-practice gap\" [65], which pertains to how research can actively engage with and contribute to practical implementation. Additionally, this paper introduces a data-driven approach for conducting thematic analyses on extensive textual datasets, creating new opportunities for qualitative analysis within the vast sea of available data in our contemporary era.
# Design and Analysis of Pattern Reconfigurable Antenna Based on RF MEMS Switches
## 2 Antenna Structure Design  
### Current Distribution Analysis  
The current direction of the antenna has a direct impact on the spatial distribution of the antenna radiation field. By using the relationship between the source current and the radiation field, we can change the radiation direction of the antenna without changing its frequency, thus achieving a reconfigurable pattern design. To meet the reconfigurable requirements, we need to first determine the current distribution on the antenna, including the current amplitude and phase information, and then select a suitable antenna structure for design according to the current requirements. In the design of reconfigurable antennas, more attention is paid to flexibility and adjustability, and the changes of current distribution under different working conditions need to be fully considered and optimized accordingly. We intended to achieve reconfigurable antenna radiation patterns by changing the antenna structure and thus affecting the current distribution on the antenna's surface by loading micro-mechanical structures on the antenna.  
In order to achieve reconfigurable antenna patterns, this design utilizes two sub-patches placed on either side of the rectangular patch. By controlling the connection between the center patch and the sub-patches using switches, the current distribution of the antenna can be altered. When the switches are in the open state, current flows from the switches to the sub-patches, resulting in a change in the current distribution. Please refer to Figure 1 for a visual representation of the current distribution.  
According to the current distribution of the antenna, it can be found that the energy is mainly concentrated at the interface between the feed line and the main patch. When the main patch is connected to the sub-patch, the radiated energy is biased towards the sub-patch side. Therefore, it was preliminarily judged that the design using the main and sub-patches could achieve the reconfiguration of two directions of the antenna.
## 3 Results and Discussion
### The Leaf Greenness Index (SPAD) and the Photosynthetic Rate
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Treatments**} & \multicolumn{2}{c}{**BBCH\({}_{\text{31}}\)**} & \multicolumn{2}{c}{**BBCH\({}_{\text{51}}\)**} \\ \cline{2-5}  & **Regression Equation** & **Coefficient of** & **Regression Equation** & **Coefficient of** \\  & **Determination R\({}^{2}\)** & **Determination R\({}^{2}\)** & **Regression Equation** & **Determination R\({}^{2}\)** \\ \hline NPK & A = 0.0921\(\cdot\) R + 2.5164\(\cdot\) T \(-\) 24.5848 & 0.883 & A = \(-\)0.1753\(\cdot\) R + 3.7715\(\cdot\) T \(-\) 35.9334 & 0.585 \\ NPK + PA \({}^{*}\) & A = 0.0996\(\cdot\) R + 2.1819\(\cdot\) T \(-\) 15.7609 & 0.996 & A = \(-\)0.0160\(\cdot\) R \(-\) 1.0631\(\cdot\) T + 44.9450 & 0.354 \\ NPK + BM \({}^{**}\) & A = 0.0801\(\cdot\) R + 0.3463\(\cdot\) T + 3.1292 & 0.599 & A = \(-\)0.0479\(\cdot\) R \(-\) 1.9456\(\cdot\) T + 50.9656 & 0.629 \\ NPK + BS \({}^{***}\) & A = 0.0374\(\cdot\) R + 0.4448\(\cdot\) T + 9.2531 & 0.889 & A = \(-\)0.0972\(\cdot\) R + 2.2360\(\cdot\) T \(-\) 14.1208 & 0.867 \\ NPK + PA + BM + BS & A = 0.0321\(\cdot\) R + 0.0641\(\cdot\) T + 18.4380 & 0.464 & A = \(-\)0.1206\(\cdot\) R + 0.5517\(\cdot\) T + 24.0601 & 0.653 \\ \hline \hline \end{tabular}  
* PA—Paenibacillus azotofixans; \({}^{**}\) BM—Bacillus megaterium; \({}^{***}\) BS—Bacillus subtilis.  
\begin{tabular}{c c} \hline \hline NPK + _Paenibacillus megaterium_ \\ BBCH\({}_{\text{31}}\) & BBCH\({}_{\text{31}}\) \\ \hline \hline \end{tabular}  
* PA—Paenibacillus azotofixans; \({}^{**}\) BM—Bacillus megaterium; \({}^{***}\) BS—Bacillus subtilis.  
\end{table} 
Table 6: Regression equations describing the photosynthetic rate (A) depending on the rainfall (R) and the temperature (T) at the winter wheat development stages (BBCH\({}_{\text{31}}\) and BBCH\({}_{\text{51}}\)) after application of microbial preparations. Figure 5: _Cont._Figure 5: Cont.
###### Abstract  
Earthquakes are sudden-onset disasters requiring rapid, accurate information for effective crisis response. Social media (SM) platforms provide abundant geospatial data but are often unstructured and produced by diverse users, posing challenges in filtering relevant content. Traditional content filtering methods rely on natural language processing (NLP), which underperforms with mixed-language posts or less widely spoken languages. Moreover, these approaches often neglect the spatial proximity of users to the event, a crucial factor in determining relevance during disasters. This study proposes an NLP-free model that assesses the spatial credibility of SM content by analysing users' spatial trajectories. Using earthquake-related tweets, we developed a machine learning-based classification model that categorises posts as directly relevant, indirectly relevant, or irrelevant. The Random Forest model achieved the highest overall classification accuracy of 89%, while the k-NN model performed best for detecting directly relevant content, with an accuracy of 63%. Although promising overall, the classification accuracy for the directly relevant category indicates room for improvement. Our findings highlight the value of spatial analysis in enhancing the reliability of SM data (SMD) during crisis events. By bypassing textual analysis, this framework supports relevance classification based solely on geospatial behaviour, offering a novel method for evaluating content trustworthiness. This spatial approach can complement existing crisis informatics tools and be extended to other disaster types and event-based applications.  
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