esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Proposed Antenna Framework  
Applying the equations related to the patch antenna presented in the preceding part, the antenna's rough design is created. A parametric sweep and CST optimizer are used to optimize the parameters and variables. Figure 3 depicts the antenna structure (CST perspective) and the design's schematic view. A driven element, four directors, two reflector elements, and feeding composition make up the antenna's seven patch elements. For ease of analysis, we refer to the reflector element \"R\" as a single element with a 0.24 mm gap through the middle to pass the feedline. A quarter-wave transformer is used to convert the 50 mm transition feedline utilized in the feeding arrangement into a high-impedance line. The high-impedance line is used to prevent radiation from the feedline near the driven element from interfering with the radiation from the antenna, which would lower gain.  
Figure 2: Fundamental structure of the presented BNN model.  
D (Driven element), D1T (Top Director 1), D1B (Bottom Director 1), D2T (Top Director 2), and D2B make up the remaining elements (Bottom Director 2). To simulate the antenna design, a double copper-clad board made of RT/Duroid 5880 material (epsilon = 2.2) was used. The Reflector Element R with Wr and Lr; the Driven Element D with Ld and Wd; the Director 1 element D1T and D1B with Ld1 and Wd1 indicating the value of length as well as width; and the Director 2 element D1T and D2B with Ld2 and Wd2, indicating the length and width, respectively. The length of g separates every element along the x-axis. S1 divides the Top Directors 1 and Bottom Directors 1, while S2 displays the separation between the Top Directors 2 and Bottom Directors 2. SL and SW stand for length and width of the substrate, respectively. The substrate has a thickness of 0.1 mm. The substrate's overall dimensions are 10.01 \(\times\) 10.8 mm\({}^{2}\). The CST MWS design tool simulates the design. The suggested design's parametric values are shown in mm in Table 1.
# Construction of the Stand and Experimental Studies of the Iontophoresis Process
## 3 Research Plan and Program  
The following were adopted as independent variables of the experiment:  
* Electric current voltage \(U\)\([\mathrm{V}]\), which was applied to the sample by the positive electrode using a laboratory power supply and monitored with a voltmeter;
* Solution temperature \(T\)\([^{\circ}\mathrm{C}]\), regulated by a water bath heater; the water temperature was monitored with a built-in thermometer, and the temperature \(T\) of the solution was monitored with a thermal imaging camera.
* The following were assumed as dependent variables:
* Current \(I_{p}[\mathrm{mA}]\), tested on the basis of the readings from an ampere meter connected serially with the negative electrode of the solution to the laboratory power supply;
* Electrical resistance \(R\)\([\mathrm{k}\Omega]\), calculated based on the relationship between the results of the current \(I_{p}\) of the solutions and the selected voltage \(U\) on the power supply.  
For the purpose of carrying out the tasks related to the main objective of the work, an experiment was planned. For this purpose, 50 mL of each solution was taken. A control sample with tap water was also determined. The samples were placed in glass beakers. To avoid contaminating and disturbing the composition of the sample being tested, a separate container of water was used in which the beakers were immersed. The water was heated to the appropriate temperatures. The parameters of the solutions were controlled with a thermal imaging thermometer, and a specially prepared heater maintained the set water temperature. After determining the appropriate liquid temperature, a waiting period of 2 min was observed before the sample was tested. The DC resistance was calculated using the formula:  
\[R=\frac{U}{I_{p}}\]  
where  
\(R\)--electrical resistance \([\Omega]\);  
\(U\)--current voltage \([\mathrm{V}]\);  
\(I_{p}\)--electric current \([\mathrm{A}]\).  
Figure 1 shows experimental test diagram.  
In the Figure 1:  
\(L_{e}\)--distance between the electrodes [m];  
\(U\)--electric current voltage [V];  
\(I_{p}\)--electric current [mA];  
\(R\)--electrical resistance [k\(\Omega\)];  
\(T\)--temperature [\({}^{\circ}\)C];  
\(w\)--humidity [\(\%\)].  
In the course of the conducted tests, the temperature \(T\) in the laboratory was 21 \({}^{\circ}\)C with a relative air humidity of 55%. However, the distance between the electrodes \(L_{e}\) was 0.06 m.  
The values of the independent variables were adopted based on the literature [22; 23] and preliminary studies conducted by the authors of this work. For the purposes of the experiment, the values of the independent variables were determined:  
- For the solution's voltage \(U=1;3;5\); \(i\) 10 V;  
- For the solution temperature \(T=26;30;35;38\) and 40 \({}^{\circ}\)C.
## 7 Prospective Aspects of WebAssembly
### Prospective Alignments with Technologies
Wasm could potentially enable smart contracts execution or complex computations on decentralized platforms, opening up new possibilities for IoT applications in a decentralized context. * **Heterogeneous Computing** In the future, IoT devices will be increasingly heterogeneous, involving a mix of CPUs, GPUs, and other specialized hardware. The need for a common runtime that can efficiently use these diverse resources will be more critical than ever. Wasm, with its portable and efficient nature, could provide a unified platform for executing code across this heterogeneous hardware, unlocking new possibilities for IoT applications. * **Advanced Robotics** Wasm's high performance and real-time capabilities could make it suitable for advanced robotics applications. Whether controlling robotic movements with precision, processing sensor data in real time, or running complex navigation algorithms, Wasm could be instrumental in pushing the boundaries of what is possible in robotics.
# Dynamic Rating of Three-Core XLPE Submarine Cables for Offshore Wind Farms
## 1 Introduction
Rating cables to conduct the actual current \(I_{a}\) is performed through a thermal cable behaviour analysis, proposed in IEC 60853-2 [8]. This way, the selection of cable parameters can be improved, which can result in an economic advantage in the development phase [5]. Thermal considerations of offshore submarine cables are worthy of investigation, as the thermal soil conditions are better than those onshore. Thus, there is an excellent opportunity to utilise the surrounding conditions in the cable current rating phase. Previous work has shown that on the basis of a more dynamic approach, a significant improvement in the transmission ability of cables can be achieved using real-time monitoring systems on existing cables, such as DTS [6]. This opens opportunities to investigate possibilities to use a dynamic cable rating method in the design phase of new projects.
###### Abstract  
(1) Introduction: deciduous traumatic dental injuries pose a serious global health concern. Root fractures show an incidence rate of approximately 2%; however, the literature is limited regarding the appropriate treatment and prognosis of affected teeth. This retrospective study aims to analyze the long-term outcomes of orthodontic splitting using brackets compared with composite resin-only splitting in two homogeneous samples affected by root fractures. The study also examines the onset and patterns of root resorption. (2) Methods: The first group included 25 patients with 27 deciduous upper incisors affected by root fracture; Group 2 consisted of 35 patients with 38 root fractures of maxillary deciduous teeth. The categorical data for both groups were analyzed using the chi-squared homogeneity test. Age groups were compared using the Mann-Whitney U test; \(p<0.005\) was considered statistically significant. (3) Results: In both groups, the male gender predominated similarly. In Group 1, early decidual loss occurred in 16% of cases, whereas in Group 2 it occurred in 51% of cases. Pulp canal obliteration was observed in 68% of deciduous teeth in Group 1, compared with 30% in Group 2. No complications affecting permanent teeth were noted in Group 1; in Group 2, 29% developed enamel dysplasia and 26% experienced delayed eruption, with statistically significant differences in these proportions. Apical fragment resorption was observed in 92% of cases in Group 1 and 30% in Group 2. (4) Conclusions: The treatment of deciduous tooth root fractures using orthodontic splits can yield significant benefits, such as reduction of early tooth loss. Furthermore, the study confirms that early resorption of the distal fragment of fractured roots is a common physiological phenomenon in primary teeth and typically occurs within a year following trauma.  
Keywords: dental traumatology; orthodontic split; primary teeth; primary root fracture; dental trauma; apical fragment resorption; pulp canal obliteration
## 3 Materials and Methods
### Methodology for Performance Evaluation  
In this paper, we considered the following performance indicators: accuracy (ACC), F1 Score, Sensitivity/Recall, and Specificity, described in Table 1 with their formulas.  
* **Accuracy**--a commonly used metric to assess the overall performance of a melanoma detection system. It measures the proportion of correctly classified melanoma and non-melanoma cases. However, it is important to consider other metrics as well, as accuracy alone may not provide a comprehensive evaluation;
* **F1 Score**--a metric that combines precision and recall. It considers both false positive (FP) and false negative (FN) and provides a balanced measure of a model's performance. Higher F1 scores indicate better performance in terms of both precision and recall;
* **Sensitivity/Recall**--Sensitivity, also known as recall or true positive rate, measures the proportion of actual melanoma cases correctly identified by the system. It focuses on minimizing false negatives (FN) and is particularly important in medical applications to avoid missing melanoma cases;
* **Specificity**--Specificity measures the proportion of non-melanoma cases correctly identified as such by the system. It focuses on minimizing false positives (FP) and is essential to reducing unnecessary biopsies or false alarms [76; 77; 78; 79; 80; 81; 82; 83].  
In the context of this study, our primary emphasis will be on the assessment of the F1 score as opposed to accuracy. This preference stems from the heightened utility of the F1 score, particularly in scenarios where the costs associated with FN and FP significantly differ. As previously mentioned, the F1 score serves as an amalgamation of both recall and precision, whereby achieving a higher F1 score inherently implies improved precision and recall. Notably, the F1 score does not take into account the count of true negatives that were accurately identified. It is particularly recommended to employ the F1 score in situations where the concern about predicting false negatives is of substantial significance. This approach aligns with our focus on optimizing the performance of our melanoma detection system while considering the potential consequences of missing cases of melanoma.
# DC Converter with Wide Soft Switching Operation, Wide Input Voltage and Low Current Ripple
###### Abstract  
A soft switching current-source resonant converter is presented and implemented for wide voltage applications such as fuel cells and solar power. An _LLC_ (inductor-inductor-capacitor) converter is adopted to accomplish zero voltage (current) operation on active switches (diodes). Thus, the circuit efficiency is increased. The interleaved pulse-width modulation (PWM) converter is employed on the input side to accomplish low input ripple current. A hybrid _LLC_ converter is adopted to achieve wide voltage operation from \(V_{in,\ min}\) to \(4V_{in,\ min}\) and to improve the weakness of a conventional _LLC_ converter. Half-bridge diode rectification is employed on the output side to decrease power loss on the rectifier diode. To confirm the theoretical analysis and feasibility, experimental verifications with a 500-W prototype are demonstrated in this paper.  
DC converters; ZVS operation; variable frequency control; _LLC_ converter +
Footnote †: journal: Applied Sciences  
_Article_  
DC Converter with Wide Soft Switching Operation, Wide Input Voltage and Low Current Ripple
## 2 Overall Analysis Approach and Implemented Methods
### Parametric Definition of Tanks Geometry  
The geometry of a generic longitudinal section of any of the tanks is defined as in Figure 7, for which it assumed that the thickness of insulation foam (\(t_{ins}\)), central walls (\(tc\)), and endcap walls (\(te\)) are uniform.  
The other relevant parameters indicated in Figure 7 are:  
* \(R\): external radius of the tank;
* \(R_{str}\): external radius of the structural part, same for both central tube and endcaps;
* \(R_{int}\): internal radius of the cylindrical tube;
* \(Re_{int}\): internal radius of endcaps measured at the junction with the cylindrical tube;
* \(L\): length of the cylindrical tube;
* \(L_{end}\): longitudinal dimension of the semi-ellipsoidal endcap, whose ratio versus \(R_{str}\), also called endcaps aspect ratio and indicated as \(f_{end}\), is given in Equation (1); \[f_{end}=\frac{L_{end}}{R_{str}}\] (1)
* \(L_{tot}\): total length of the tank, for which the relation in Equation (2) stands: \[L_{tot}=L+2\cdot R_{str}\cdot f_{end}+2\cdot t_{ins}\] (2)
* \(d_{supp}\): distance between supports providing the structural connection between the tank and the fuselage.  
The parametric description of tanks' geometry was focused on the description of the space occupied by the tanks within the fuselage cross-section, and it was conceived to handle a high number of tank layouts using a small number of parameters. The input needed by the parametric model is the dimensions of the available fuselage section and the position of the main tank in the fuselage cross-section. These inputs can be provided in a different manner, depending on the desired layout:  
* Full-section layout: a set of tanks properly sized to occupy the elliptic cross-section of the fuselage, hence reducing the space available for passengers and containers;
* Part-section layout: a set of tanks properly sized to occupy only the parts of the fuselage cross-section below and/or above an assigned height, hence not reducing the space available for passengers;  
In addition, the presence of \"catwalks\", i.e., corridors which allow crews and passengers to walk through the portion of fuselage occupied by the LH\({}_{2}\) tanks, and multiple groups of tanks (both with full-section and part-section layout) can be specified.  
Figure 7: Longitudinal section of a generic hydrogen tank composed of a cylindrical central part and two semi-ellipsoidal endcaps, both covered by an external layer of insulation material (in blue).  
Since space constraints are given through section borders, all the considered layouts are conceived for fuselage parts that can be approximated as cylindrical, as the central ones, whereas fore and aft fuselage volumes are not considered as available for tank integration in this study.
# Educational 5G Edge Computing: Framework and Experimental Study
## 3 5G Smart Campus System Architecture  
### Top-Level System Design of Smart Campus  
As illustrated in Figure 1, a new 5G-based \"1 + 1 + 1 + N\" overall smart education system design is proposed, which means \"one educational terminal + one dedicated network + one educational dedicated cloud + N educational applications\". The system can be a new DICT (data information and communications technology) infrastructure. It consists of four layers, involving a 5G educational terminal, 5G education private network, 5G education dedicated cloud, and 5G educational applications, which will be described in detail in the following Sections 3.1.1-3.1.4. The boxes on the right side are detailed expansions of the four boxes on the left side, denoting the sample entities, applications and services. There are no communication needs between the same level boxes of the terminal, network, cloud and application layers. The communications between terminals and dedicated cloud are based on the network layer. For each instance in the educational applications, its information is handled by the following process. The terminal collects the specific application data, and the network layer transmits data. Some data are transfered to a traditional IDC server, and the rest are executed with a dedicated cloud. The cloud layer stores and calculates data, and the application layer displays data. The dedicated network has multi-access communications and thus can establish one-hop data connection with the terminals. The dedicated cloud runs various services specifically for the smart educational applications.  
The other three layers are orchestrated and managed by the education-specific cloud layer to enable the heterogeneous smart campus system to be manageable, flexible and applicable to different teaching scenarios and various applications inside and outside the campus. The functionality of these three layers should be exposed to educational applications through unified APIs. In this way, advanced technologies such as 5G, cloud, AI, and video in the system can be easily used by different educational applications, creating a campus-specific ecosystem of smart education capabilities for all educational service scenarios.  
In addition, it contains innovative educational private network architecture and educational private cloud architecture, which will be discussed in detail in the next two chapters. The private network and private cloud can be independently or jointly used. When they are used jointly, the transmission delay can be controlled within a deterministic range to guarantee the service-level agreement (SLA) as the education data deployed on them can be directly offloaded from the education dedicated network and education dedicated cloud.
## 4 Empirical Results  
### Confirmatory Factor Analysis  
Table 3 presents the results of the confirmatory factor analysis (CFA). The goodness-of-fit indices indicate that the model fits the data adequately (\(\chi^{2}\) = 347.847, df = 160, \(\chi^{2}\)/df = 2.174, GFI = 0.895, NFI = 0.937, RFI = 0.925, CFI = 0.965, RMSEA = 0.062). All factor loadings, AVE, and CR values exceeded the established thresholds, confirming that the convergent validity of the measurement items is satisfactory. Thus, the convergent validity could appear as acceptable manners. The mean value of the anti-oxidant effect and brand trust are 3.77, and 3.80, respectively. Also, Table 3 illustrates the mean value of healthiness (mean = 3.84), nutrition disclosure (mean = 3.77), and intention to purchase (mean = 3.84).  
Table 4 is the results of correlation matrix. Because the diagonal values are greater than off-diagonal values, the discriminant validity of measurement items appeared as acceptable level. Intention to purchase positively correlates with the anti-oxidant effect (r = 0.601, \(p\) < 0.05), brand trust (r = 0.660, \(p\) < 0.05), healthiness (r = 0.684, \(p\) < 0.05), and nutrition disclosure (r = 0.533, \(p\) < 0.05). Healthiness positively correlates with the anti-oxidant effect (r = 0.667, \(p\) < 0.05), brand trust (r = 0.618, \(p\) < 0.05), and nutrition disclosure (r = 0.596, \(p\) < 0.05).  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Construct** & **Code** & **Loading** & **Mean (SD)** & **AVE** & **CR** \\ \hline \multirow{4}{*}{Anti-oxidant effect} & A1 & 0.806 & & & \\  & A2 & 0.880 & 3.77 & & \\  & A3 & 0.893 & (0.80) & 0.730 & 0.915 \\  & A4 & 0.838 & & & \\ \hline \multirow{4}{*}{Brand trust} & B1 & 0.707 & & & \\  & B2 & 0.862 & 3.80 & & \\  & B3 & 0.824 & (0.78) & 0.674 & 0.891 \\  & B4 & 0.881 & & & \\ \hline \multirow{4}{*}{Healthiness} & H1 & 0.823 & & & \\  & H2 & 0.858 & 3.84 & & \\  & H3 & 0.872 & (0.86) & 0.742 & 0.920 \\  & H4 & 0.892 & & & \\ \hline \multirow{4}{*}{Nutrition disclosure} & N1 & 0.790 & & & \\  & N2 & 0.797 & 3.77 & & \\  & N3 & 0.839 & (0.80) & 0.647 & 0.880 \\  & N4 & 0.791 & & & \\ \hline \multirow{4}{*}{Intention to purchase} & I1 & 0.921 & & & \\  & I2 & 0.937 & 3.84 & & \\ \cline{1-1}  & I3 & 0.897 & (1.01) & 0.836 & 0.953 \\ \cline{1-1}  & I4 & 0.902 & & & \\ \hline \end{tabular} Note: SD, standard deviation, goodness-of-fit indices: \(\chi^{2}\) = 347.847, df = 160, \(\chi^{2}\)/df = 2.174, RMR = 0.031, GFI = 0.895; NFI = 0.937; RFI = 0.925; CFI = 0.965; RMSEA = 0.062; CR, construct reliability; AVE, average variance extracted.  
\end{table}
Table 3: Confirmatory factor analysis results.
# Front-End Amplifiers for Tuning Forks in Quartz Enhanced PhotoAcoustic Spectroscopy
###### Abstract  
A study of the front-end electronics for quartz tuning forks (QTFs) employed as optoacoustic transducers in quartz-enhanced photoacoustic spectroscopy (QEPAS) sensing is reported. Voltage amplifier-based electronics is proposed as an alternative to the transimpedance amplifier commonly employed in QEPAS experiments. The possibility to use differential input/output configurations with respect to a single-ended configuration has also been investigated. Four different architectures have been realized and tested: a single-ended transimpedance amplifier, a differential output transimpedance amplifier, a differential input voltage amplifier and a fully differential voltage amplifier. All of these amplifiers were implemented in a QEPAS sensor operating in the mid-IR spectral range. Water vapor in ambient air has been selected as the target gas species for the amplifiers testing and validation. The signal-to-noise ratio (SNR) measured for the different configurations has been used to compare the performances of the proposed architectures. We demonstrated that the fully differential voltage amplifier allows for a nearly doubled SNR with respect to the typically used single-ended transimpedance amplifier.  
Keywords:quartz tuning fork; quartz enhanced photoacoustic; QEPAS sensor preamplifier; QTF front-end electronics +
Footnote †: journal: Applied Physics Letters
## 2 Materials and Methods
### Analyzed Methods
#### 2.1.3 Merlin  
MERLIN [11] is a method for offline anomaly detection based on discord discovery: given a subsequence \(S\) with length \(L\) starting at timestamp \(p\), a matching subsequence \(M\) starting at timestamp \(q\) is called a non-self match to \(S\) if \(|p-q|\geq L\)[11]. The discord \(\tilde{S}\) of a time series \(\mathcal{T}\) is defined as the subsequence with the largest distance \(d(\tilde{S},M_{S})\) from its nearest non-self match \(M_{S}\), where \(d(\cdot,\cdot)\) is the z-normalized (zero mean and unit variance) Euclidean distance. MERLIN is based on the discord discovery algorithm from [32]. A key factor in the success and efficiency of the algorithm is the selection of the hyperparameter \(r\). This parameter should be chosen to be slightly less than the discord distance, \(d(\tilde{S},M_{S})\). If \(r\) is too large, the algorithm will fail, while if it is too small, the runtime will be excessively long. To address this challenge, MERLIN provides a structured search procedure for determining an appropriate value for \(r\) by leveraging the observation that good values of \(r\) for subsequences of length \(L\) are likely to be similar to good values of \(r\) for subsequences of length \(L-1\)[11]. The maximum value of \(r\) for subsequences of length \(L\) is given by \(r_{max}(L)=2\sqrt{L}\)[33]. To find an appropriate value for \(r\), the algorithm begins by setting \(r=r_{max}(L_{min})\), where \(L_{min}\) is the smallest subsequence length being considered, and then halving \(r\) until the first discord is returned. For subsequences of other lengths \(L_{min},\ldots,L_{max}\), the previously determined values of \(r\) can be used. We selected MERLIN as it is the method provided with the UCR anomaly archive dataset, which is the benchmark dataset for our study and will be introduced in Section 2.2.