esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Mechanical Testing Results
Its preliminary mixing and freeze-drying with aluminum oxide enables achieving a uniform distribution of GO in volume and prevents the agglomeration of ceramic particles, and a relatively small amount of GO prevents it from agglomerating itself. Therefore, at these concentrations of graphene oxide, \"nothing\" prevents polymer molecules from starting to untangle, orient themselves and irreversibly flow one relative to the other in the direction of the shear force, which we observe on the stretching curves for these filaments (0.10 and 0.25 vol.%) (Figure 6A). The concentration of 0.50 vol.% graphene oxide seems to be sufficient for limiting the mobility of polymer chains of polyamide 12. Although the rheological properties of the composition with 0.50 vol.% GO showed better values than those of a mixture without graphene oxide, this is probably because when the compositions are heated at a temperature, it is easier for polymer chains to start the untangling mechanism. The optical images of cross-sections of filament fractures during tension (Figure 7A,B) additionally demonstrate the effect of GO on the behavior of the material during this test. As shown in Figure 7A, the fracture surface of the filament with 0 vol.% GO is smooth and has obvious signs of brittleness, while the surface of 0.10 vol.% GO is uneven, elongated along the direction of the surface force, which is characterized by a plastic fracture (Figure 7B). Also, crack lines perpendicular to the direction of the tensile force are visible on samples with 0.10 vol.% GO (indicated by white arrows in Figure 7B), which appeared during tests in the field of plastic deformation (Figure 6A). Thus, the addition of 0.10 and 0.25 vol.% graphene oxide contributes to a simultaneous increase in the tensile strength and plasticity of the ceramic-filled polymer material. The resulting effect allows winding filaments with 0.10 and 0.25 vol.% GO onto the spool and helps avoid breakage during unwinding and printing.
## 2 Materials and Methods  
### Instrument Specification  
The VSFlab instrument is established based on the principle of the double periscopic optical system and rotating detector, which is similar to that of [PERSON] et al. [23]. In addition, the module of the attenuation coefficient (\(c\)) measurement is set up so that the samples' attenuation coefficients and VSFs can be measured simultaneously. The overall schematic is illustrated in Figure 1a. The laser source's wavelength is 532 nm (as an alternative, the 520 nm CW laser module of MatchBoxTM is available), and the divergence is about 0.06\({}^{\circ}\) at a half angle. The typical power is 60 mW. The laser source, together with a 1 mm pinhole, is fixed in an adjustor that allows one axial translation and two axial rotations. A beam splitter (\(R\):\(T\) = 10:90) divides the laser into two beams. To monitor the fluctuation of the laser, we record the reflected beam with a photodetector, which also serves as the reference for \(c\) measurements. Through prism 1, the transmitted beam enters the sample inside the basin. Some of the transmitted beam is scattered at different angles, some is absorbed by the water, and some is reflected from the water onto the glass surface of the new prism and absorbed by the bottom of the basin whose absorptivity is 99.99% after the process of oxidative blackening. The remaining beam leaves the sample via the new prism and is then detected by another photodetector, whose minimum detectable power is about 2.4 \(\times\) 10\({}^{-14}\) W/\(\sqrt{\text{Hz}}\), to determine the sample's attenuation coefficient. The periscopic optical system, which contains a mirror, prism 1, and the new prism, separates the plane containing the scattered light from the plane containing the light source. The system ensures that the laser source won't mask the photomultiplier tube (PMT) at near backward angles and then broadens the angle range. To broaden the angle range further, we adjust the transmitted beam such that it is as close to the edge of the prism as possible.  
The basin is fixed on the rotating device, and the detector is installed at the wall of the basin. The scattering signal is collected by the detecting module, which includes the lens, pinhole, and PMT. A high-performance PMT (HAMAMATSU H10721-20) whose minimum detectable power is about 1.25 \(\times\) 10\({}^{-9}\) mW is used to meet the required dynamic range of nearly five orders of magnitude. The schematic of the rotatable component is shown in Figure 1b. The basin is used to store the sample where scattering occurs. The detector, together with the basin, spins under the drive of the rotating device. A complete measurement is not time consuming and typically lasts 8 s. The basin is oxidized and turned black to protect it from erosion and reduce the amount of stray light reflected from its wall. The assembled VSFlab is shown in Figure 1c.
# Study on Deformation Characteristics of Low-Highway Subgrade under Traffic Load
## 4 Numerical Calculation and Analysis of Subgrade Deformation
### Subgrade Horizontal Displacement  
The rule of horizontal displacement along the subgrade surface is shown in Figure 21. As the distance from the center of the roadbed increases, the horizontal deformation of the roadbed surface first increases and then decreases. The maximum value appears at the edge of the roadbed, about 0.2 cm. The increasing phase is approximately a linear increase.
# Noble Metal-Based Heterogeneous Catalysts for Electrochemical Hydrogen Evolution Reaction
## 3 Catalytic Mechanism of the HER  
### Volcano Plot  
The \"volcano plot\", first established by [PERSON], connects the value of \(j_{0}\) with \(\Delta\)G\({}_{\text{H}^{*}}\) calculated using the Density Functional Theory (DFT) to describe the adsorption strength of H\({}^{*}\) on the catalyst surface [53]. Later, based on experiments, researchers established the \"volcano plot\" (Figure 4a) using the correlation between \(j_{0}\) values of some elements and \(\Delta\)G\({}_{\text{H}^{*}}\) calculated using the DFT [8]. \(\Delta\)G\({}_{\text{H}^{*}}\) < 0 indicates that the adsorption of H\({}^{*}\) is too strong and the desorption of H\({}_{2}\) is not sufficient, which causes the active centers on the catalyst to be blocked, thus resulting in catalyst poisoning and hindering the reaction from proceeding [54; 55]. \(\Delta\)G\({}_{\text{H}^{*}}\) > 0 means the adsorption of H\({}^{*}\) is too weak. The hydrogen atoms are not easily absorbed on the metal surface, and the coverage of hydrogen on the material surface is reduced, which causes the active center to not be effectively utilized, further slowing down the reaction speed [56]. Therefore, the energy of the intermediate is neither too strong nor too weak on the surface for an ideal catalyst. It can be seen from the figure that the platinum group precious metals located at the vertex of the volcanic curve have the best HER activity.  
It is important to note that OH* may also be an important factor affecting the HER activity, especially in alkaline electrolytes. [PERSON] et al. [43] studied the HER activity of Pt(111), Ni@Pt(111), NiFe@Pt(111) and NiCo@Pt(111) under the same experimental conditions. The relation of the binding energy with OH* was NiCo@Pt(111) > NiFe@Pt(111) > Ni@Pt(111), and the corresponding HER activity was NiFe@Pt(111) > Ni@Pt(111) > Ni-Co@Pt(111) > Pt(111). The Ni clusters on Pt(111) play the role of water decomposition. The introduction of Co increased the adsorption of OH, and the strong adsorption hindered the subsequent reaction steps of Ni-Co clusters. NiFe@Pt is in a better balance between water decomposition and preventing OH* \"poisoning\". Therefore, the OH* binding energy may be one of the important descriptors of the basic HER (Figure 4b). Too weak OH* binding energy leads to slower water decomposition, while too strong OH* binding energy leads to catalyst \"poisoning\".  
This section may be divided into subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn.
## 2 PFC Converters Power Components Design Analysis and Selection
### Switching Elements Selection
#### 2.3.2 Fast Switching Boost Diode Selection  
The boost diode maximum current is calculated as the maximum load current at the minimum output voltage.  
In the conventional PFC converter, the boost diode Db maximum current is calculated at the full load condition and minimum output voltage as follow  
\[\text{I}_{\text{Db\_max}}=\frac{\text{P}_{\text{out}}}{\text{V}_{\text{o\_min}}} \tag{26}\]  
For the interleaved PFC converter  
\[\text{I}_{\text{DI\_max}}=\text{I}_{\text{DI\_max}}=\frac{\text{I}_{\text{Db\_ max}}}{2} \tag{27}\]  
The diode losses are estimated based upon the forward voltage (Vf) at 125 \({}^{\circ}\)C and the reverse recovery charge (Qrr) of the diode.  
\[\text{P}_{\text{DbLoss}}=\text{V}_{\text{f}}\times\text{I}_{\text{Db\_max}}+0. 5\times\text{F}_{\text{sw}}\times\text{V}_{\text{out}}\times\text{Q}_{\text{ rr}} \tag{28}\]  
As given in (26) the boost diode has big influence on the system's performance due to the reverse recovery behavior. So, the Ultra-fast diode with very low reverse recovery time (t\({}_{\text{rr}}\)) and reverse recovery charge (Qrr) is necessary to reduce the switching loss.  
In this work Schottky diode is used as the boost diode, the new diode technology of silicon carbide (SiC) Schottky diode with part number of (IDH16G65C5) shows its outstanding performance with almost no reverse recovery behavior. So that, the switching loss due to this diode can be ignored, and only the conduction loss due to Vf is considered.
# The Challenges of Advanced CMOS Process from 2D to 3D
## 3 Process Integration of New Transistor Architecture
### 3D Gate and Spacer Patterning  
To form long fins increases the complexity of integration of poly gate, spacer, and replacement metal gate. For example, it is difficult to etch the poly gate with high aspect ratio and precise control of dimensions [25]. Charging and micro-loading in etching lead to variable gate length (_Lg_). Significant over-etch is required to clear the poly residual on the fin sidewalls, and significant over-etch is also required to clear the offset spacers on the fin sidewalls for epitaxial S/D growth [28; 29]. Both these over etchings results in damages of the Si fins. Careful optimization of dry and wet etching is needed to produce 3D gates with minimum _Lg_ variation and fin loss.  
The replacement metal gate module also poses challenges, as it requires two new steps which can interact during the STI CMP. The control of gate height is essential in a replacement gate process. If the gate is over-polished, the raised source-drain is exposed to the polish, resulting in external resistance (_Rext_) and mobility variation. Meanwhile, when the gate is under-polished, the contact taper causes _Rext_ variation (in extreme case resulting in an open-contact yield issue). Therefore, more precise and more controllable CMP process is required [30].
# _Sci_
## 3 Results
### Technical Challenges of Employing Lasers versus Radio Frequency Communications
#### 3.2.1 Beam Divergence, Vibration, and Jitter  
The frequency advantage of lasers comes from their incredibly small wavelengths. By comparison, optical (i.e., laser) wavelengths are ten-thousand-times shorter than microwaves, allowing data to be transmitted in narrow or tight beams [52]. The narrowness of those beams (beam width) is equivalent to their wavelength, divided by the diameter of the optical aperture of the transmitting telescope, scaled by a multiplicative factor from 2.24-2.28 [51; 59].  
Referencing Figure 5, narrow beams spread less during travel through space and require less power for transmission [46; 53]. [PERSON] [46] provides the following quote:  
_\"For example, a typical Ka-Band signal from Mars spreads out so much that the diameter of the energy when it reaches Earth is larger than Earth's diameter. A typical optical signal, however, will only spread over the equivalent of a small portion of the United States; thus, there is less energy wasted.\"_  
Beam divergences are proportional to the wavelength and inversely proportional to the aperture diameter, thus beam spread is more favorable for optical laser transmission. The smaller wavelength permits smaller antennae, whose gain scales are inversely proportional to the square of the wavelength. Reference Equation (1) for a comparison by ratio of antenna gain.  
\[\theta\approx\frac{wavelength}{aperture\ diameter}=\frac{\lambda}{D_{r}} \tag{1}\]  
\[\frac{Gain_{optical}}{Gain_{radio\ frequency}}\approx\frac{4\pi/\theta_{ optical}^{2}}{4\pi/\theta_{anis\ frequency}^{2}}\approx\frac{4\pi/(\frac{\lambda}{D_{r}})_{optical}^{2}}{4\pi/( \frac{\lambda}{D_{r}})_{anis\ frequency}^{2}} \tag{2}\]  
Unfortunately, the transmitting platform's physical vibration can produce errors (i.e., the rate of bit errors or bit error rate), akin to the light from a flashlight held by a  
Figure 4: Radio frequency atmospheric attenuation in decibels per kilometer (on the ordinate) versus frequency and wavelength (on the abscissa).  
frightened person. That vibration may source certain pieces of equipment within the satellite (e.g., solar arrays, reaction wheels, control movement gyros.) The vibration can also manifest as a \"jerkiness\" of the transmitting platform as it moves along in orbit [53]. Satellites in orbit experience the four-hundred to one-thousand hertz of vibration and shaking [51].  
Jitter is a special category of vibration, particular to optics. Jitter is a high-frequency, typically sinusoidal, undesired fluctuation that causes a reduction in beam intensity at the target (irradiance). [PERSON] et al. [60] demonstrate, with the example of a softball-sized beam, that one milliradian of jitter will have a one-hundred fold decrease in irradiance at a target positioned five-hundred kilometers away.
# Advances in the IoT and Smart Cities
## 2 Overview of Contributions  
This Special Issue features high-quality papers that advance our understanding and application of IoT technologies within smart city environments. In this collection, the integration of the digital Building Information Modelling (BIM) process and IoT in the construction industry is investigated, thus revealing a promising synergy between data-rich digital models and real-time sensor networks. Through a systematic literature review, the authors highlight the potential of BIM-IoT integration in improving construction safety, risk management, and sustainability, but also note that practical implementation remains limited due to technological and organizational constraints (contribution 1).  
Moreover, an innovative real-time data processing framework for pavement quality monitoring using IoT and NoSQL technologies is also presented in this Special Issue. The system architecture presented supports rapid data ingestion and analytics at scale, with the experimental results demonstrating a 52-fold improvement in data processing speed over traditional systems. The research in this Special Issue shows how infrastructure monitoring in smart cities can benefit from optimized cloud-based data architectures (contribution 2).  
In addition, other researchers address the complexity of modelling concurrent behaviors in IoT systems through enhancing the Gherkin language for behavior-driven development (BDD). A tool called concurrentSpec is proposed, which enables the accurate specification and execution of concurrent behaviors typical in distributed IoT environments.  
Their work fills a methodological gap, facilitating better alignment between IoT software specifications and real-world execution (contribution 3).  
Furthermore, the privacy implications of personal and pseudo-anonymized data collection in smart cities are explored. Based on a research review, the authors identify the risks of de-anonymization and side-channel attacks while also surveying current anonymization techniques. The research presented in this Special Issue emphasizes that privacy-preserving architectures are critical in building citizen trust and enabling responsible data reuse in smart urban platforms (contribution 4).  
Finally, a practical contribution to IoT interoperability in the form of a narrowband IoT (NB-IoT) relay for integrating IPv6-based 6 LoWPAN sensor networks into legacy IPv4 infrastructures is presented. The approach leverages protocol translation and cloud integration through Home Assistant to simplify data exchange and increase platform compatibility. The work presented in this Special Issue directly responds to challenges of protocol diversity in IoT networks and exemplifies a lightweight solution for seamless integration (contribution 5).
## 2 Materials and Methods  
### Diatom Exposure Trials and Biomarker Analysis  
Data regarding growth and biomarker activity/concentration were collected from previously published works [15; 22; 23; 24; 25]. _Phaeodactylum tricornutum_ Bohlin (Bacillariophyceaeae; strain IO 108-01, Instituto Portugues do Mar e da Atmosfera (IPMA)) axenic cell cultures (maintained under asexual reproduction conditions) were placed to grow in f/2 medium [26], under constant aeration in a phytoclimatic chamber, at 18 \({}^{\circ}\)C, programmed with a 14/10 h day/night photoperiod (RGB 1:1:1, maximum PAR 80 \(\upmu\)mol photons m\({}^{-2}\) s\({}^{-1}\)), a sinusoidal function to mimic sunrise and sunset, and light intensity equal to noon, set to replicate a natural light environment [27]. Exposure trials were conducted according to the Organization for Economic Cooperation and Development (OECD) recommendations for algae assays [28], with minor adaptations, and as described in [15; 22; 23; 24; 25]. Briefly, cultures were exposed to the compounds and target concentrations for 48 h. Target concentrations were selected aiming to cover a concentration gradient reflecting, not only the detected environmental concentrations found in the literature, but also concentrations known to have significant biological effects in _P. tricornutum_[29; 30]. Growth inhibition concentration (IC\({}_{50}\)) was calculated according to the OECD guidelines for the algae inhibition test [28]. Biomarker analysis was performed according to standard spectrophotometric procedures as described in [15; 22; 23; 24; 25]. Briefly, catalase (CAT), ascorbate peroxidase (APx) and superoxide dismutase (SOD) activities were assayed by spectrophotometric means using specific substrates as previously described [31; 32; 33]. Lipid peroxidation products were analyzed spectrophotometrically [34], using trichloroacetic acid extraction before the reaction with thiobarbituric acid.
# Covert Anti-Jamming Communication Based on Gaussian Coded Modulation
## 2 Signal Design  
In this section, we describe the proposed signal design. In the proposed system, the codeword alphabet consists of Gaussian-distributed real numbers rather than a finite-field  
Figure 2: Block diagram of the proposed system. The message is encoded by Gaussian coding, described in Section 2.2. [PERSON] transmits the codeword to [PERSON] and [PERSON] after a time-frequency modulation, introduced in Section 3.1. [PERSON] estimates and removes the effect of the jammer by using the sparse jamming estimation algorithm proposed in Section 3.4, in order to decode the message from [PERSON]. Meanwhile, [PERSON] aims to determine if the signal is present or not. The signal detection by [PERSON] is discussed in Section 4.  
alphabet. The transmitted Gaussian codeword appears as additive white Gaussian noise (AWGN) to [PERSON]. In contrast, the receiver who knows the exact codebook can detect the transmitted codeword even with a significantly low SNR setting. Figure 3a illustrates the time-domain signal waveform of the proposed system at the 0 dB SNR setting. The waveform with noise in Figure 3c is hardly distinguishable from the AWGN in Figure 3b. A detailed analysis of this undetectability is presented in Section 4. In this section, we consider two encoding methods used to construct such codewords. We first introduce the simplest method, linear block coding (LBC), as proposed in previous studies [5; 7]. Then, we present the limitations of that method and propose two methods to address these limitations.
## 3 Results
### Experimental Results
We also tried our model on real life images collected by ourselves. The results illustrated in Figure 6 show that our model could do well on real life images. Keywords such as beach were used in the description. When a user wants to retrieve when he/she went to a beach, a simple query with the keyword \"beach\" would help retrieve such events easily. Our model could also reason where to look while generating the description, as shown in Figure 7.  
We used our trained model in our system. It took about 2 s to process an input image and our model could process 64 images simultaneously in one forward running. In real time running, the server would take 2 s to process the image taken from camera every minute. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **BLEU-1** & **BLEU-2** & **BLEU-3** & **BLEU-4** & **METEOR** & **ROUGE-L** & **CIDEr** \\ \hline Watson Multimodal [30] & 0.781 & 0.619 & 0.470 & 0.352 & 0.270 & 0.563 & 1.147 \\ Postech\_CV [31] & 0.743 & 0.575 & 0.431 & 0.321 & 0.255 & 0.539 & 0.987 \\ ATT [15] & 0.731 & 0.565 & 0.424 & 0.316 & 0.250 & 0.535 & 0.943 \\ Google-NIC [11] & 0.713 & 0.542 & 0.407 & 0.309 & 0.254 & 0.530 & 0.943 \\ Montreal/Toronto [14] & 0.707 & 0.492 & 0.344 & 0.243 & 0.239 & - & - \\ Nearest Neighbor [32] & 0.697 & 0.521 & 0.382 & 0.28 & 0.237 & 0.507 & 0.886 \\ NeuralTalk [12] & 0.650 & 0.464 & 0.321 & 0.224 & 0.21 & 0.475 & 0.674 \\ \hline
80\_tags\_model [17] & 0.701 & 0.527 & 0.384 & 0.277 & 0.230 & 0.511 & 0.835 \\ \hline
9000\_tags\_model (ours) & **0.723** & **0.554** & **0.414** & **0.310** & **0.250** & **0.532** & **0.942** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of our models compared to other methods. Figure 5: Some generate captions of our model from MSCOCO test set.
## 1 Introduction
In contrast, Fuzzy PID control demonstrates unique advantages: it dynamically adjusts PID parameters via fuzzy inference, reducing overshoot without requiring an exact system model while significantly shortening the step response time [11]. To improve the scanning speed and stability of the dual-grating electro-optical tracking system on shipborne platforms, this paper designed a Fuzzy PID-based servo control system based on the dual-grating two-dimensional scanning model, combined with inertial navigation feedforward technology [12, 13, 14].