esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Data and Method
### Workflow of the Developed Methodology
#### 3.2.2 Data Processing  
The constituent materials of building envelopes and structural elements exhibit dynamic responses to fluctuations in environmental parameters, including ambient temperature and humidity. Consequently, longitudinal analysis of three-dimensional thermal point cloud data offers a robust methodology for the identification and mitigation of material degradation, while simultaneously enabling the optimization of building energy efficiency [13].  
Following established protocols [14], thermographic data acquisition was conducted pre-surrise to minimize solar radiative heating. To ensure data integrity, the infrared camera was orthogonally aligned with the target facade and calibrated, with a 50% overlap between sequential thermograms. Post-acquisition, environmental parameters (ambient temperature, humidity) and contact temperature measurements at discrete facade locations were recorded to facilitate calibration and validation of the thermographic data [15].  
The thermal images were then orthorectified in order to be applied to the 3D digital model using the projective transformation. This type of transformation introduces two plane coordinate systems using a central projection. All projection rays are straight lines passing through the centre of the perspective; the equations that allow this type of projection are as follows: [16; 17]  
\[x=\frac{a_{1}x^{\prime}+a_{2}y^{\prime}+a_{3}}{c_{1}x^{\prime}+c_{2}y^{\prime}+ 1}y=\frac{b_{1}x^{\prime}+b_{2}y^{\prime}+b_{3}}{c_{1}x^{\prime}+c_{2}y^{\prime }+1} \tag{1}\]  
where:  
* \(x,\ y\) coordinates of thermal original images;
* \(x^{\prime},\ y^{\prime}\) coordinates of rectificated thermal images in a local frame;
* \(a_{1},\ a_{2},\ a_{3},\ b_{1},\ b_{2},\ b_{3},\ c_{1},\ c_{2}\) projective parameters.
## 3 Methodology
### Source Localization Using MUSIC Algorithm  
The MUSIC algorithm is then employed as:  
1. Both eigenvectors, i.e., \(\{\hat{\mathbf{v}}_{1},\hat{\mathbf{v}}_{2},\hat{\mathbf{v}}_{3},\dots\hat{ \mathbf{v}}_{M}\}\), and the corresponding eigenvalues, i.e., \(\{\varepsilon_{1},\varepsilon_{2},\dots\varepsilon_{M}\}\) are computed from \(\mathbf{D}_{v}\).
2. The signal space is represented by the largest Eigen vector, i.e., \(\hat{\mathbf{v}}_{1}\), and noise space is represented by the remaining vectors as there is the only one source in \(\mathbf{D}_{v}\). The DOA is estimated from the peak of the spatial spectrum [1]: \[P_{\text{MUSIC}}(\theta_{v})=\frac{1}{\sum_{i=2}^{M}\left|\mathbf{a}(\theta_{v} )\hat{\mathbf{v}}_{i}\right|^{2}},\] (20)
## 2 Advances in Multiple Access Techniques for 6G Mobile Wireless Networks
### Rate-Splitting Multiple Access  
Existing multiple access technologies, SDMA and NOMA, handle interference by treating it as noise or fully decoding the interference, respectively [19]. Note that RSMA combines these two philosophies. The key idea of RSMA is to split each user's message into a common part and a private part. The common parts from multiple users are combined and encoded as a common message. The private parts of each user are encoded as private messages. At the receiver, each user first decodes the common message and removes it using SIC, and then decodes their private message. When the common message rate is appropriately determined, RSMA can mitigate interference between users and achieve better spectral efficiency compared to existing MA techniques.
## 4 Conclusions  
The samples studied show a visible replacement of the original minerals (pyroxene, amphib, plagioclase and mica) by secondary species consisting of mordenite and smectite, and their presence favors the behavior of these andesites as typical natural pozzolans. This fact can be explained by the inherent characteristics of zeolites, such as their high content of reactive SiO\({}_{2}\), their cation exchange capacity and their marked pozzolanic reactivity.  
In the chemical composition of the samples of altered pyroxenic andesites compared to unaltered ones, there is an increase in reactive SiO\({}_{2}\), alkaline compounds on alkaline-earth and loss on ignition, as well as a decrease in Al\({}_{2}\)O\({}_{3}\), causing a better pozzolanic response.  
The mechanical strengths of the specimens prepared with partial substitution of Portland cement by altered pyroxenic andesites increases exponentially from the initial curing ages (2 and 7 days) to normal and late (28 and 90 days), reaching equal, and even occasionally exceeding, the values of resistances of the reference specimen.  
The values of mechanical resistance obtained by the formulations of 75:25% and 70:30% show an increase in resistance when the substitution is 25%; however, these differences are not very high, so for practical purposes both dosages could be equally profitable in the production processes of pozzolanic cements.  
The samples of altered pyroxenic andesites are part of the host rocks of the deposit of natural zeolites located in the Caldera de Los Frailes; therefore, the establishment of their pozzolanic properties could be considered for rational and simultaneous exploitation of both materials, to a better use.  
The results presented in this work could be used as a practical guide within the applied sciences to guide local industries in the optimal use of natural resources of volcanic origin.  
The results achieved suggest that the altered pyroxenic andesites investigated in this work could guarantee the quality of more environmentally friendly cements, through which CO\({}_{2}\) emissions to the atmosphere and global warming could be mitigated. In addition, these results could be taken into account in sustainable development objectives, in the circular economy and in the recycling of new materials.  
Conceptualization, D.A.M. and J.L.C.; methodology, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; software, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; validation, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; formal analysis, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; investigation, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; resources, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; data curation, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; writing--original draft preparation, D.A.M. and J.L.C.; writing--review and editing, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; visualization, D.A.M., J.L.C., M.A.S. and J.L.C.-V.; supervision, D.A.M. and J.L.C.; project administration, D.A.M. and J.L.C.; funding acquisition, M.A.S. All authors have read and agreed to the published version of the manuscript.  
Figure 7: Mechanical resistance of specimens made with PC: 70% / PAAZ: 30%.
## 3 Results and Discussion  
### Analysis of Hyperspectral Reflectance  
With the aim to compare the differences between healthy and infected leaves, the six representative wavelengths distributing in the red light, green light, blue light, red edge, and near-infrared region, respectively, were selected for analysis. Figure 2a displays the representative color and spectral images of healthy and infected (asymptomatic and symptomatic) _A. thaliana_ leaves. No significant difference can be observed from color images between healthy and asymptomatic leaves, implying the challenges of SSR identification only using color images. With the development of _S. scleroorum_ infection, it could be found that some typical spots appear in symptomatic leaves. Consideringspectral images at different wavelengths, the images in the near-infrared range showed a better performance in comparison with those in the visible range and that the infected tissues (asymptomatic and symptomatic leaves) presented a great contrast to uninfected ones. Figure 2b shows the mean spectra of healthy and infected leaves. A general reflectance pattern of green leaves in the range of 450-1023 nm can be observed. The reflectance from 450 to 700 nm that carried carotenoids, surface color, and the chlorophyll contents information, while reflectance from 700 to 1023 nm was associated with the internal characteristics of _A. thaliana_ leaves. The reflectance of infected leaves in the invisible range presented some overlaps to that of healthy ones, except for a slight difference in the blue and green light region, which indicated the difficulty of detecting the infected leaves of _A. thaliana_ with sole color images. That is consistent with the spectral images shown in Figure 2a. The difference of reflectance in the near-infrared region between healthy and infected leaves is significant. The lower reflectance of infected leaves in the near-infrared region might result from tissue collapse and cell structure breakdown due to _S. scleroorum_ infection, which suggests the potential of HSI for discriminating infected leaves from healthy ones.  
Figure 2: (**a**) The color images and six representative spectral images of the healthy and infected samples (asymptomatic and symptomatic). (**b**) Mean spectra and standard deviations of the healthy (\(n=138\)) and infected (\(n=147\)) samples in the range of 450–1023 nm.
# Energy Efficient Multipath Routing Algorithm for Wireless Multimedia Sensor Network
## 4 Energy Efficient GA-Based Multipath Routing  
In this section, we present the proposed multipath routing for a wireless multimedia sensor network. We refer to the proposed algorithm as efficient multipath routing based on GA (EMRGA). As shown in Figure 3, the proposed routing protocol is a cluster-based multipath framework that allows message transfer between the cluster heads and the base station. The main aim is to minimize the energy consumption as well as the overhead due to routing. We describe the dynamic cluster formation, the cluster head selection, and the multipath formation for data communication in detail below.
# 3D Void Handling Geographic P2P-RPL for Indoor Multi-Hop IR-UWB Networks
## 4 Performance Evaluation
### IR-UWB Based 3D Multi-Hop Self Localization with Bounding-Box and Mobile Tracking Scheme  
The positioning error simulation result of the proposed IR-UWB based 3D multi-hop self-positioning system is shown in Figure 13 in a CDF form. One hundred simulation runs are conducted for three different numbers of static node cases: 100, 125, and 150. The static nodes are deployed in a grid pattern with (\(\pm\)5 m, \(\pm\)5 m, \(\pm\)5 m) randomness. The network size is 75 m \(\times\) 75 m \(\times\) 75 m, the same as the routing simulation environment configuration. Eight mobile nodes move around the network. The maximum ranging error value \(e_{r}\) is set to 50 cm according to the Decawave DW1000 module ranging measurements [17]. The maximum mobile tracking error value \(e_{p}\) is set to 30 cm/s, referring to the experimental statistics of the position errors presented in [14]. The average positioning error values for three cases are 162 cm, 151 cm, and 143 cm, respectively. In a simulation where no mobile nodes are deployed, the positioning error result of 2791 cm was acquired in the case of 125 static nodes. With the mobile nodes, roaming around the network to provide the static nodes with their real-time B-box states and ranging measurements, the positioning results are significantly improved, compared to the case where no mobile nodes participate. In all routing simulations, the acquired statistical positioning error information of the 125 static nodes case is used for each node location estimation and the greedy next-hop selection procedure.  
Figure 12: IEEE802.15.4 UWB PHY protocol data unit (PPDU) structure and transmission timing model. The transmission time of PPDU \(T_{PPDU}\) is the sum of \(T_{SHR}\), \(T_{PR}\) and \(T_{PSDU}(n_{PSDU})\). \(n_{PSDU}\) is the number of bytes in the PSDU. The transmission time of PSDU \(T_{PSDU}(n_{PSDU})\) is a function of \(n_{PSDU}\) where the Reed–Solomon encoding adds 48 bits to every block of 330 bits or less as shown.
# Effective Adsorption of Phenoxyacetic Herbicides by Tomato Stem-Derived Activated Carbons
## 3 Results and Discussion
### Adsorption Study  
#### 3.2.1 Adsorption Kinetics  
Figure 3 depicts the adsorption kinetics of 2,4-D and MCPA on tomato stem-derived activated carbon (TS-AC) as a function of time, demonstrating the rapid adsorption in the initial stage (within the first few minutes) and then slowing down, reaching equilibrium after about 60 min. Figure 3: Adsorption kinetics of 2,4-D and MCPA on tomato stem-derived acid (MCPA) on tomato stem-derived activated carbon (TS-AC) (lines mean the fitting of the pseudo-second-order (PSO) kinetic model). Conditions: adsorbate initial concentration = 1 mmol/L, adsorbent dosage = 0.25 g/L, pH = original (-3.3), temperature = 23 \({}^{\circ}\)C.  
The correlations obtained clearly show that TS-AC prepared at the same activation temperature has similar adsorption properties (the plot curves are similar). However, two kinetic models, pseudo-first-order (PFO) and pseudo-second-order (PSO), were used to compare the adsorption kinetics reliably. The following dependence expresses the PFO model proposed by [PERSON] [26]:  
\[\log\ (q_{\rm e}-q_{\rm t})=\log\ q_{\rm e}-\frac{k_{1}}{2.303}t \tag{8}\]  
where \(k_{1}\) is the pseudo-first-order adsorption rate constant (1/min). The rate constant of the PFO model was determined from the slope and intercept obtained for the linear function \(\log(q_{\rm e}-q_{\rm t})=f(t)\). The pseudo-second-order kinetic model, proposed by [PERSON] and [PERSON] [27], can be represented as follows:  
\[\frac{t}{q_{\rm t}}=\frac{1}{k_{2}q_{\rm e}^{2}}+\frac{1}{q_{\rm e}}\ t \tag{9}\]  
where \(k_{2}\) is the pseudo-second-order adsorption rate constant (g/mmol-min) determined from the slope and intercept obtained for the linear relationship \(t/q_{\rm t}=f(t)\). The determination coefficients (\(R^{2}\)) and chi-square (\(\chi^{2}\)) values were used to assess the kinetic model's fit to the experimental data. \(R^{2}\) values were calculated using the following formula:  
\[R^{2}=\frac{\sum_{i=1}^{n}\left(q_{e(\rm cal)}-\overline{q_{e(\rm exp)}} \right)^{2}}{\sum_{i=1}^{n}\left(q_{e(\rm cal)}-\overline{q_{e(\rm exp)}} \right)^{2}+\sum_{i=1}^{n}\left(q_{e(\rm cal)}-q_{e(\rm exp)}\right)^{2}} \tag{10}\]  
where \(q_{e(\rm exp)}\) and \(q_{e(\rm cal)}\) are the adsorption capacities (mmol/g) obtained experimentally and calculated from the kinetic model (Equations (4) and (5)), respectively. The \(\chi^{2}\) value was calculated using the following equation:  
\[\chi^{2}=\sum_{i=1}^{n}\frac{\left(q_{e(\rm exp)}-q_{e(\rm cal)}\right)^{2}}{ q_{e(\rm cal)}} \tag{11}\]  
A better fit of the model is indicated by higher \(R^{2}\) (closer to 1) and lower values of \(\chi^{2}\).
# ReFuse: Generating Imperviousness Maps from Multi-Spectral Sentinel-2 Satellite Imagery
## 3 Materials and Methods  
As described in Section 1, in this paper we introduce a web-based system leveraging a new deep-learning model for generating imperviousness maps from Sentinel-2 satellite images. The resulting system has been integrated within a GIS web-based application to support non-expert operators in easily generating imperviousness maps. Figure 2 shows the interface presented to the user for requesting a map of imperviousness in a specific part of the globe. Users only need to draw their area of interest and then select the date range in which they are interested. Once the area and date range has been selected, a map calculation phase for the specific area starts. An asynchronous process handles the whole computation. All these processes happen in the background and are transparent to the user. Figure 3 reports a logical diagram of the inference pipeline: after the user request, satellite images are collected from the stores and sent to the inference pipeline, which produces the imperviousness map as the final output. It is worth noting that such a web application requires an inference process that can handle and scale toward enormous quantities of satellite data. The following sections detail each of the three main components: Section 3.1 describes the steps followed for the training dataset generation; Section 3.2 introduces the designed deep-learning model; Finally, Section 3.3 describes the inference pipeline in detail, investigating the scalability requirements of the proposed solution.  
Figure 2: Example of the area of interest selection in the proposed tool.
# Future Perspectives for Gamma-ray Burst Detection from Space
## 10 Strobe-X
### Expected Performance  
STROBE-X will make major advances in several areas of GRB and multi-messenger astronomy (Figure 18). The WFM will detect and localize \(>\)5 short GRBs per year and distribute the position accurate to 2 arcmin, brightness, and timing to the ground in \(<\)5 min. In some cases, it will measure the redshift directly from the X-ray data (from the location of absorption edges in their spectra). STROBE-X will study the plateau emission of both short and long GRBs and provide unique diagnostics of whether the emission comes from millisecond magnetars or structured jets, revealing the nature of the central engines.  
STROBE-X will also be triggered by ground-based GW detections and get the pointed instruments on source within \(<\)11.5 min, given access to early afterglows with the tremendous collecting area and CCD-quality spectral resolution of LEMA.  
The large grasp and softer response than many GRB missions will give STROBE-X access to unusual GRB phenomena that have not been well studied so far, including X-ray flashes (XRFs) and ultra-long GRBs (ULGRBs). Detecting and localizing \(>\)10 XRFs per year will increase the samples of these sources and break the degeneracies in the models for the source mechanisms.  
Figure 17: Rendering of the STROBE-X spacecraft, showing the 3 science instruments. LEMA and HEMA are co-aligned narrow FoV instruments, while the WFM has an instantaneous FoV of 1/3 of the sky.
## 4 Enabling Technologies for FSO Communication
### Robust Beam and Multi-Modulation Compatible System Design
#### 4.1.2 Multi-Modulation Compatible Miniaturization System  
Free-space optical (FSO) communication has been extensively used to establish satellite-to-earth, inter-satellite, and deep-space links for purposes such as environmental monitoring, information transmission, and celestial exploration [124]. The electro-optical conversion in FSO links typically relies on various modulation techniques, including intensity modulation (IM) and phase modulation (PM). IM is widely utilized due to its simple architecture and ease of operation [125; 126]. In contrast, PM is considered a more suitable solution for long-haul links, offering higher data rates and improved receiving sensitivity [127; 128]. Therefore, achieving compatibility between IM and PM within the same communication system is of practical significance.  
Traditional IM and PM both rely on the Mach-Zehnder modulator (MZM) and its associated supporting devices [129; 130]. As a result, an IM/PM-compatible system requires two independent sets of modulation modules along with numerous auxiliary devices, significantly increasing system complexity. However, the limited resources on satellites impose strict conditions on the size, weight, and power (SWaP) of laser communication terminals in practical applications. Therefore, solutions that enhance compatibility and allow for seamless IM/PM switching while maintaining optimal SWaP are highly desirable.  
Multi-modulation-format compatible laser communication refers to a laser communication system designed to support and efficiently manage multiple modulation formats. This capability allows for seamless communication between different devices. Such a system can dynamically switch between or simultaneously support various modulation formats to optimize performance based on changing conditions, including channel conditions, data rate requirements, power efficiency, and compatibility with various systems and standards. By being adaptable to multiple modulation formats, a laser communication system enhances its flexibility, efficiency, and reliability across diverse applications and environments.  
Since the intensity or phase change of an optical signal can be controlled by the input electrical level of a chirp-managed laser (CML) [131; 132], the CML has emerged as a convenient solution for achieving IM/PM compatibility. This CML-based modulation technique eliminates the need for traditional Mach-Zehnder modulators (MZMs) and their supporting devices, thus reducing the size, weight, and power (SWaP) requirements and aiding in the miniaturization of optical communication terminals. In [133], a CML-based IM/PM compatible transmitter is designed, demonstrating the ability to switch seamlessly between On-Off Keying (OOK) and return-to-zero differential phase-shift keying (RZ-DPSK) using a single set of devices.
## 4 Analysis and Discussion
### PUF-Based Authentication Challenges and Solutions  
#### Challenge 1: Delay Gates  
In electronics and digital circuits, the propagation delay, also called the gate delay, is the amount of time between when the input to a logic gate becomes stable and valid to change and when the output of that logic gate becomes constant and rational to change [110].  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Study**} & \multirow{2}{*}{
\begin{tabular}{c} **Current** \\ **IoT** \\ **Protocols** \\ \end{tabular} } & \multirow{2}{*}{**Objectives**} & \multirow{2}{*}{**Results**} & \multicolumn{2}{c}{**Evaluation Methods**} & \multirow{2}{*}{**Major Disadvantages**} \\  & & & & **Analyzer** & & & \\  & & & & **Software** & & \\ \hline \multirow{4}{*}{[105]} & CoAP, & Investigate three IoT & Overhead and & Arduino Uno & Packet & \\  & MQTT, & communication protocols: & latency both & Rev3, & overhead, & \\  & MQTT/TLS, CoAP/DTLS, & MQTT/TLS, CoAP/DTLS, & increased for at least & WireShark, & latency, & latency, \\  & & and XMPP/TLS & & threefold for each & Raspberry Pi 3 & scalability & \\  & & and XMPP/TLS & & protocol. & Model B & \\ \hline \multirow{4}{*}{[106]} & & & & This paper reviews & & \\  & & & & This paper reviews & & \\  & & Present the functions of the & & modern IoT & & \\  & MQTT, & IoT and its applications in & technologies and & & & \\  & AMQP, & various domains such as & use cases, & & \\  & CoAP, & smart cities, health care, & future-generation & & & \\  & CoAP, & environmental, Industry & protocol. IoT & & & focus area & \\  & XMPP & 4,0, and beyond and & disputes were & & & \\  & & infrastructural applications. & examined to & & \\  & & enhance R\&D in & & & \\  & & the fields. & & & \\ \hline \hline \end{tabular}
\end{table}
Table 8: _Cont._The time that passes during normal operation when the PUF unit receives the input and when it begins producing output is referred to as the stabilization time. The critical and emergency systems at this location cannot tolerate this kind of delay. It is a very significant research challenge for scholars to design novel PUFs that can affect the initiation and handling times [111]. Recent studies have shown that unbalanced ternary logic gates and arithmetic circuits can help reduce the delay [112, 113].