esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Hardware Detection Circuit Debugging and Result Analysis
### Bandpass Filter Module Testing  
This section emulates the transmission of a signal through a differential amplifier module followed by its passage into a bandpass filter. The purpose of employing the  
Figure 9: Modeling of differential amplification module. (**a**) Circuit of differential amplifier, (**b**) input/output waveform of differential amplification circuit signal.  
bandpass filter is to retain the signal within proximity of its center frequency, thereby alleviating the burden on the multiplier chip. Figure 10 displays the band-pass filter test circuit. The signal source produces a 100 mV signal with a frequency of 1 MHz as the effective signal. The noise source generates a white noise signal ranging from 0 to 1 MHz and a DC signal of 1 mV as the noise. The experiment aims to decouple the effective 1 MHz signal using the band-pass filter. Oscilloscope 2's left channel (Channel-A) detects the input signal waveform, while the right channel (Channel-B) detects the output signal waveform. Voltmeter 3 and voltmeter 4 measure the AC voltage amplitude and DC offset of the output signal, respectively. Distortion analyzer 2 measures the total harmonic distortion rate after the band-pass filter.  
Figure 10 displays the results from oscilloscope 2. The blue waveform represents the input signal mixed with noise signal, while the red waveform represents the output signal after differential amplification. The delay response of the output signal is 140 us, and the period of the output signal is 996.5 ns. The voltage amplitude is 198.51 mV, and the total harmonic distortion is \(-62.889\) dB. The signal noise distortion is \(56.535\) dB, and the DC bias voltage is \(-65.376\) uV. The DC bias voltage is \(-65.376\) uV. Upon comparing the waveforms of the input and output signals, it is evident that the band-pass filter amplifies the effective signal by a factor of two while filtering out the noise more effectively. This meets the design requirements of an amplifier with a band-pass filter.
## 1 Introduction
According to the soundscape approach, sounds are differentiated based on people perception, experience, and understanding of the acoustic environment, in context [43]. In this perspective, sounds can be unwanted or wanted, and as such a \"resource\" to be exploited for generating positive indoor soundscapes according to people preference [44]. As such, the soundscape framework reinforces the need to prevent \"noise\" exposure, as a serious public health issues, and encourages \"sound\" exploitation to foster less annoying, as well as more comfortable environments, in line with a salutogenic approach to the building design [45; 46]. The novelty of this concept paper is represented by the application of the indoor soundscape approach to the NV context. This means valuing sounds provided and filtered by ventilation openingsthrough the application of soundscape assessment methods, in order to tackle the apparent conflict between acoustic comfort and NV from a different, perceptual view. The main goal is to derive future directions of research that may be possibly worth exploring, by providing a new research perspective for the development of acoustic requirements in naturally ventilated buildings and facade control strategies enabling NV. The analysis, for this paper, follows the structure which is graphically represented in Figure 1, where the sections composing the main body of this paper are indicated. Methodologically, this concept paper provides, at first, context on (i) the approach that will be applied, by briefly introducing the soundscape concept and the recent trends in indoor soundscape research and (ii) the research field where such an approach could be applied, that is, acoustic comfort in naturally ventilated residential buildings. To this aim, acoustic criteria required for naturally ventilated residential buildings are reviewed, and a summary of the facade noise control solutions developed so far to meet those criteria is provided. The underpinning research questions are:  
* What is the conceptual framework of indoor soundscape? * What are the limits in the current approach towards acoustic comfort in naturally ventilated buildings? Finally, the indoor soundscape approach will be tuned to the NV context, with the aim of answering the main research question of the study:  
* How can the highlighted limits be overcome by the application of the indoor soundscape approach to the NV context? This will derive future directions for research that could possibly be worth exploring in future field or laboratory investigations. Figure 1: Graphical representation of the concept paper’s structure.
## 3 Results and Discussions
### Static Modulus of Elasticity  
As previously mentioned, the static modulus of elasticity in compression was determined in accordance with currently available standards [14]. The results are presented in Figure 6 as the average values of 19 determinations each of these individual values were, in turn, obtained as the average of three measurements, as shown in Figure 3.  
It can be observed that irrespective of the mix, there is a decrease in the values of the static modulus of elasticity. The decrease ranged from 17% for the reference mix up to 60% for RuC80. Small variations in the values of modulus of elasticity were reported in the literature for concrete with fly ash, but the curing and exposure conditions were different compared to the present study [21]. The storage conditions of the specimens presented in this study favored the loss of water by evaporation through pores and capillaries.  
Rubberized concrete specimens were most affected by this due to the fact that the presence of rubber aggregates favor the occurrence of weak links at the interface between the cement paste and rubber particles, thus favoring migration of water towards the surface of the specimens. A similar decrease in the values of mechanical and elastic properties of RuC was reported in the scientific literature, although for much smaller replacement percentages [22].  
The decrease in the values of the static modulus of elasticity ranged from 38.6% for RuC40 to 65.23% for RuC80 mix compared to the reference mix.  
Figure 6: Variation in the static modulus of elasticity in time.
## 7 Conclusions  
Based on the study of hyperspectral imaging data in Qidashan iron mine, the following conclusions are drawn:  
1. The results of mineral mapping and chlorite spectral features extraction in Qidashan Iron Deposit show that chlorite both occurs in the wall rocks around BIFs and high-grade iron ore. The wavelength position of OH, Fe-OH, and Mg-OH absorptions of chlorite around high-grade iron ore are between 1400 and 1410, 2260 and 2265, and 2360 and 2370 nm, respectively, whereas the corresponding wavelengths are between 1390 and 1400, 2245 and 2255, and 2330 and 2340 nm around BIFs.
2. The higher spatial resolution laboratory-based hyperspectral imaging can reflect the specific information of mineral species, mineral content, structure, and even the polytypes of the rock sample.
3. The relationship between cations in the chlorite octahedral layer and the absorption wavelengths of OH, Fe-OH, and Mg-OH indicates that Fe is positively related to the wavelength, whereas Mg and Mg/(Mg + Fe) are inversely related. The wavelength appears to be weakly influenced by AIVI. Nevertheless, the relative absorption depths of the OH, Fe-OH, and Mg-OH are a poor guide to chemical composition of chlorite.
4. The difference in the chemical composition of chlorite caused by the different formation conditions of BIFs and high-grade iron ore in Qidashan Iron Deposit is well recorded in the wavelength position of chlorite. This difference of the wavelength, in turn, can be used as a favorable tool for the exploration of high-grade iron ore in the Anshan-Benzi area. This chlorite hyperspectral imaging tool may also provide a basis for the aerial or satellite hyperspectral remote sensing mineral exploration in Anshan-Benzi area.  
[PERSON] processed the data and wrote the paper; [PERSON] conducted the paper revision and the discussion of the results; [PERSON] provided financial support and useful suggestions for the paper; [PERSON] provided assistance in HySpex data acquisition; [PERSON] reviewed the paper. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key Research and Development Program of China (grant 2016 YFC0801603).  
We thank DiMap for access to the HySpex instruments used in the PSML, and we were also deeply indebted to the Qidashan Iron Deposit, Anshan Iron & Steel Group, for their kind help in field investigation and sampling.  
The authors declare no conflict of interest.
# Performance Evaluation of Random Access Methods for IoT-over-Satellite
## 4 Emulation Results and Discussion
### Energy Wasted in Different Access Methods  
Based on the provided energy model in Section 3.4.3, we simulate and depict the energy wasted for different access scenarios illustrated in Figure 14. Noticeably, case III has the highest energy wastage, which is due to packet re-transmission. Furthermore, the energy wasted for case III is also shown in Figure 13 whereby the energy wasted increases as the number of re-transmissions increases even as the PER is reduced. On the other hand, case IV (without the overhead power due to synchronization) provides lower energy wastage due to the interference-free environment achieved by network synchronization. If we assumed the overhead power due to synchronization is equal to 250 mW, the energy wastage of case IV as shown in Figure 14, is still somewhat lower than the energy wastage in case II, since the power used for synchronization reduces the chance of packet collision. We can see that access methods that heavily rely on scheduling and synchronization, such as case IV, require a large amount of overhead power. However, this is not included in this work because the amount of energy consumed depends on the particular system implementation. The energy wasted can be reduced by increasing the size of the constellation due to the increased availability. However, as the availability approaches its maximum, the energy enhancement saturates. This is illustrated in Figure 15 for both Walker-Delta and Walker-Star where a minimum of 200 mJ energy wastage is achieved as the number of satellites increases and the availability approaches its maximum.  
Figure 12: The average BER as a function of the transmit power for different access cases. The constellation size and altitude are equal to \(N_{s}=480,h=550\) km, respectively.  
Figure 13: The PER and energy wasted per day with respect to varying packet repetitions, \(L\), in case III assuming a transmit power \(P_{t}=27\) dBm.
## 3 Approximate Inverse Kinematics Solution for Imposed End-Effector State
### Robot Cables' (Tendons') Length Calculation According to the Robot Spine Curvature
Furthermore, the cable \(l_{31}\), \(l_{32}\), \(l_{33}\) holes were rotated the same way as \(l_{21}\), \(l_{22}\), \(l_{23}\) but by \(80^{\circ}\). Figure 17a-c depicts all cable hole positions. Based on the specified hole positions on all robot cable guide disks and Equations (48)-(51) from [36], Equations (52)-(57) for \(l_{21}\), \(l_{22}\), \(l_{23}\) and for \(l_{31}\), \(l_{32}\), \(l_{33}\) cable length expressions are  
\[l_{21}=q_{1}r_{1}+q_{2}r_{2}-\left(D_{1}q_{1}\sin(\varphi_{1}+\frac{2\pi}{9} )\right)-(D_{2}q_{2}\sin\varphi_{2}), \tag{52}\]  
Figure 17: Robot cables’ hole positions on the connecting disks: (**a**) Cables’ hole positions on the first segment connecting disk in the first segment coordinate system; (**b**) cables’ hole positions on the second segment connecting disk in the second segment coordinate system; (**c**) cables’ hole positions on the third segment connecting disk in the third segment coordinate system. \[l_{22} =q_{1}r_{1}+q_{2}r_{2}+\left(D_{1}q_{1}\sin\left(\varphi_{1}+\frac{5 \pi}{9}\right)\right)+\left(D_{2}q_{2}\sin\left(\varphi_{2}+\frac{\pi}{3}\right) \right), \tag{53}\] \[l_{23} =q_{1}r_{1}+q_{2}r_{2}-\left(D_{1}q_{1}\cos\left(\varphi_{1}+\frac {7\pi}{18}\right)\right)-\left(D_{2}q_{2}\cos\left(\varphi_{2}+\frac{\pi}{6} \right)\right),\] (54) \[l_{31} =q_{1}r_{1}+q_{2}r_{2}+q_{3}r_{3}-\left(D_{1}q_{1}\sin\left( \varphi_{1}+\frac{4\pi}{9}\right)\right)-\left(D_{2}q_{2}\sin\left(\varphi_{2} +\frac{2\pi}{9}\right)\right)-\left(D_{3}q_{3}\sin\varphi_{3}\right),\] (55) \[l_{12}\overset{\frac{1}{n}=r_{1}}{\rightarrow}q_{1}\Big{(}r_{1}+D_{1}\sin \Bigl{(}\frac{\pi}{3}+\varphi_{1}\Bigr{)}\Big{)}, \tag{49}\]0 (56) \[l_{12}\overset{\frac{1}{n}=r_{1}}{\rightarrow}q_{1}\Big{(}r_{1}+D_{1}\sin \Bigl{(}\frac{\pi}{3}+\varphi_{1}\Bigr{)}\Big{)}, \tag{49}\]1  
Here, the robot second segment cable lengths are \(l_{21}\), \(l_{22}\), \(l_{33}\), and the third segment cable lengths are \(l_{31}\), \(l_{32}\), \(l_{33}\). The first, second, and third segments' circle arc radii are \(r_{1}\), \(r_{2}\), and \(r_{3}\). The distances from the robot spine center point to the robot cable center point on the robot connecting disk plane of the three segments are \(D_{1}\), \(D_{2}\), and \(D_{3}\). The angle \(\varphi_{n}\) is between vector \(\overset{\wedge}{\mathbf{s}}_{\text{orienn}}\) and the \(n\)-th segment coordinate system \(x\)-axis on the \(x\)-\(y\) plane (the angle around the \(z\)-axis).
# Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion
## 7 Conclusions  
The purpose of this study was to develop a truck routing framework to improve the process of selecting alternative truck routes to measure the effectiveness of rerouting approaches on travel time and to determine the resulting effects on the economy and the environment. The study shows that truck rerouting strategies for relieving traffic congestion have substantial economic and environmental impacts. The framework methodology developed in this study can be used to measure these impacts on any segment of limited-access highway with an alternative route.  
The use of an efficient traffic diversion strategy during incident-induced congestion provides safety and mobility benefits to highway users. The application of appropriate diversion criteria utilizing truck VOT analysis, fuel consumption aspects, safety studies, and environmental impact analysis can lead to the selection of alternative routes that reduce travel time, meet the restrictions for truck operations, and sustain an acceptable level of service on the alternative route.  
This framework provides a decision-support tool for decision makers and traffic management centers that can enable them to cope more efficiently and effectively with nonrecurrent congestion on highway networks.  
This study has some limitations, such as a lack of comprehensive evaluation of the impact of truck drivers' behavior on route preference. The proposed model can be expanded by integrating more analysis layers, such as weather conditions and road construction. Additionally, the framework can be integrated with other traffic management strategies such as traffic signal control and dynamic toll collection to enhance the operational efficiency of the traffic system. Finally, more detailed environmental analyses can be conducted to assess the impact of emissions due to rerouting.  
These limitations suggest a direction for future research to advance the congestion management process and create more efficient traffic flows.  
Given the limitations noted above, together with the investment gap in infrastructure expansion in the U.S., there is a need to embrace alternative strategies to detect, manage, and efficiently mitigate traffic congestion.  
All authors (S.Y. and A.O.) contributed equally to this work. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Florida Department of Transportation grant BDV24-977-28.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors wish to thank the Florida Department of Transportation for funding this research.  
The authors declare no conflicts of interest.
# A Multi-Band Circularly Polarized-Shared Aperture Antenna for Space Applications at S and X Bands
###### Abstract  
In this article, a compact multiband antenna design and analysis is presented with a view of ensuring efficient uplink/downlink communications at the same time from a single antenna for CubeSat applications. This design shares the aperture of an S-band slot antenna to accommodate a square patch antenna operating in the X-band. Shared aperture antennas, along with an air gap and dielectric loading, provided good gain in both frequency bands. The S-band patch had an S\({}_{11}=-10\) dB bandwidth of 30 MHz (2013-2043 MHz, 1.5%), and the X-band antenna demonstrated a bandwidth of 210 MHz (8320-8530 MHz, 2.5%). The Axial Ratio (<3 dB) bandwidth of the slot antenna in the S-band is 7 MHz (2013-2020 MHz, 0.35%), and it is 67 MHz (8433-8500 MHz, 0.8%) in the case of patch antenna in the X-band. While the maximum gain in the S-band reached 7.7 dBic, in the X-band, the peak gain was 12.8 dBic. This performance comparison study shows that the antenna is advantageous in terms of high gain, maintains circular polarization over a wideband, and can replace two antennas needed in CubeSats for uplink/downlink, which essentially saves space.  
CubeSat; shared aperture antenna; multiband; high gain; circular polarization Article
# Comparative Study of Minimally Invasive Microwave Ablation Applicators
## 3 Results
### Performance of the Two-Compartment Model for All Designs  
In this segment of the study, simulation results for Specific Absorption Rate (SAR) and temperature distribution are presented for all designs within a two-compartment model corresponding to a mean biological tissue \(\varepsilon_{\mathrm{r}}\) = 46.8 and \(\sigma\) = 0.861 and tumor with \(\varepsilon_{\mathrm{r}}\) = 57.09 and \(\sigma\) = 1.05 at 915 MHz [52; 53]. The simulations were conducted with consistent power deposition and the same insertion depth across all designs. Explicit comparisons follow in the two next subsections.
## 4 Modeling Techniques for Composite Members and Structures Under Earthquake Excitation
### Modeling Techniques for Composite Members and Structures Under Earthquake Excitation: Key Findings  
Some of the key findings regarding the seismic analysis of steel-concrete composite buildings are as follows:  
* The seismic response of composite buildings is significantly influenced by the modeling of composite action, which alters the stiffness, strength, and energy dissipation capacity of the structure compared to non-composite systems.
* Accurate modeling of interfaces, such as the steel-concrete interface behavior, is crucial for overall structural performance, including slip and partial interactions.
* Nonlinear behavior, including inelastic deformations in steel and concrete components, as well as their composite action, must be taken into account for realistic seismic analysis.
* The performance of beam-column joints, especially in moment-resisting frames, is greatly influenced by connection details, affecting energy dissipation and overall ductility.
* The modeling of floor diaphragms is important, as composite floor systems affect load distribution and structural dynamics, requiring careful consideration in the modeling process.
* Material degradation due to cyclic loading should be considered, as it can lead to strength and stiffness degradation in both steel and concrete, affecting the seismic response.
* Three-dimensional modeling is often necessary to capture effects, such as torsion and bidirectional loading, which can be significant in composite structures.
* Utilizing sophisticated numerical techniques, like finite element analysis incorporating intricate material models, has the potential to offer precise assessment of the local and global performance of composite structures.
* Future research should focus on creating standardized protocols for assessing the durability of composite structures under different seismic intensities and frequencies.
# Impact of Carpets on Indoor Air Quality
## 3 Effects of Carpets on IAQ
### Particulate Matter
#### 3.2.1. Particulate Matter Deposition on Carpets  
It is known that carpets deposit more particles, dust, and allergens than non-carpet floors and possibly cause worsening of asthma and allergies [72; 73; 74]. A study using an isolated room (volume = 14.2 m\({}^{3}\)) showed that a carpet contributed to a higher deposition loss rate of particles (<10 \(\upmu\)m) under airflow conditions (mean air speed = 5 to 19 cm/s) compared to a bare room [72].  
Moreover, the surface of carpets has the potential to support chemical and biological transformations, including particle-bound SVOCs or fungal growth [39]. For example, one study showed that dust presence is an important factor in fungal growth in carpets, and the elevated RH (\(\geq\)85%) is also an essential variable of increased fungi in carpets [75]. It is also suggested that the material of carpet fibre relates to the potential fungal growth and allergen production, and Olefin fibre showed less fungal and _A. alternata_ growth compared to nylon and wool fibres [75].  
In addition, a recent study reported the persistence of viruses (MS2 and Phi6 bacteriophages) on carpets for several hours to days, and vacuum cleaning and hot water extraction did not show significant effects in reducing the concentration of viruses [76]. Therefore, understanding the environmental conditions or cleaning methods that reduce the resuspension of deposited particles from carpets is needed to improve IAQ and human health.
# Broadband Millimeter-Wave 5G Power Amplifier Design in 22 nm CMOS FD-SOI and 40 nm GaN HEMT
## 3 Results
### Single-Ended GaN (GaN #1) PA Measurement Results
Figure 6: Measured maximum PAE, \(S_{21}\) and \(P_{OUT,SAT}\) vs. frequency of the broadband single-ended GaN PA at (**a**) \(V_{DD}\) = 4 V and (**b**) \(V_{DD}\) = 6 V.  
Figure 7: ACLR measurements of the broadband single-ended GaN PA at 24 GHz using a (**a**) 50 MHz, (**b**) 100 MHz, (**c**) 400 MHz, and (**d**) 9 \(\times\) 100 MHz 256-QAM 5G NR signal with PAPR = 8 dB.
# Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network
###### Abstract  
As a lateral load-bearing system, the steel plate shear wall (SPSW) is utilized in different structural systems that are susceptible to seismic risk and because of functional reasons SPSWs may need openings. In this research, the effects of rectangular openings on the lateral load-bearing behavior of the steel shear walls by the finite element method (FEM) is investigated. The results of the FEM are used for the prediction of SPSW behavior using the artificial neural network (ANN). The radial basis function (RBF) network is used to model the effects of the rectangular opening in the SPSW with different plate thicknesses. The results showed that the opening leads to reduced load-bearing capacity, stiffness and absorbed energy, which can be precisely predicted by employing RBF network model. Besides, the suitable relative area of the opening is determined.  
artificial neural network; steel shear wall; finite element method; opening; radial basis function +
Footnote †: journal: Applied sciences