esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Developed Drone System for TEM  
The main geological task that needs to be solved with the help of UAV electrical prospecting was detailed areal electromagnetic sounding, which would allow relatively quickly and cheaply obtaining large amounts of data suitable for solving inverse problems in the class of 3D models. The idea is to replace the ground survey, not the aerial. To do this, it needs to get closer to the level of terrestrial surveying detail. The ground-based version of sounding is quite expensive, and therefore usually areal 3D electrical prospecting will be carried out in separate, most promising parts of the license areas identified at the previous stages of geological prospecting. Recently, it can be integrated with UAV surveys.  
This task needs a large operating radius. Therefore, a line-to-loop survey was implemented, where the power source is a long line, since such a current source provides an acceptable operating radius, but the measuring system is an induction loop, since such a sensor can measure without contact with the ground. This measurement geometry is atypical, since usually the transmitter and receiver are of the same type--\"line-line\" or \"loop-loop\". The power source is placed on the ground, while the measurement system is on the aircraft (Figure 2). The transmitter is a galvanically grounded power line with length up to several kilometers long. The signal is bipolar current pulses with a pause. The survey lines are parallel to transmitter line and located at a distance of 40 to 100 m from each other.  
When the transmitter is stationary, and the measuring system moves across the area, a number of ground-based electrical prospecting methods are implemented, but all solutions known on the market are of the \"line-to-line\" type, where both the measuring line and the power supply are galvanically grounded. The authors are not aware of serial line-to-loop systems. Many methodological issues of surveying by the \"line-loop\" array, and even from the air, have been poorly studied, and therefore the development of the UAV system was carried out by trial and error method.  
The first working prototype of the system, the survey results of which are discussed in this work, to optimize the development process, was created with the widespread use of technologies from other developments of the authors--the unmanned airborne geophysical complex SibGIS UAS [2; 5; 10; 11] and the electrical prospecting system MARS for ground electrical exploration works by the 'electromagnetic soundings with induced polarization (EMS-IP)' method [17]. In this regard, the prototype had a number of drawbacks of a purely technical nature, later easily eliminated.  
The developed hardware and software complex consists of:  
* airmobile part, including an unmanned vehicle, a sensor, a meter unit and a recorder (Figure 3);
* the ground part, the solution of the power source is of primary interest;
* software for data processing.  
Figure 2: Geometry of measurements by the UAV-TEM method.
## 3 Materials and Methods
### Method Validation  
Validation of optimized SPME-Arrow method for bound VOCs was performed by means of 20 compounds (Supplemental Table S3) belonging to the following groups: aldehydes (4 compounds), alcohols (6 compounds), C\({}_{13}\)-norisoprenoids (2 compounds), acids (4 compounds), and monoterpenes (4 compounds). Calibration curves were constructed using five different concentrations of standards in citric buffer (pH 2.4). The linearity of analyzed compounds was completed by estimation of the regression curves and expressed by the squared determination coefficient (R\({}^{2}\)). The limit of detection (LOD) was defined, according to IUPAC, as the smallest amount of analyte concentration in the sample that can be reliably distinguished from zero, with the acceptance criteria that signal-to-noise (S/N) ratio is 3. The limit of quantitation (LOQ) is the lowest amount of analyte in the sample, which can be quantitatively determined with suitable precision and accuracy, with the acceptance criteria that the S/N ratio is 10. The intraday precision was determined from 3 successive injections of the mix of standard compounds prepared in citric acid buffer (pH 2.4). The interday precision was determined by 3 injections on 3 different days of the week. The precision was calculated using the relative standard deviation (RSD %).
# Predicting Electromagnetic Performance Under Wrinkling in Thin-Film Phased Arrays
## 2 Wrinkling of Step-Stiffness Structure and Dual-Domain Displacement Mod
### Surface Deformation of STMA
The deformation in the copper foil-plated area of the array antenna becomes progressively more pronounced, with its peak value rising from 0.05 mm to 0.19 mm. Near the boundaries, the copper foil region exhibits even larger displacements, a consequence of the composite structure's edge constraints. The deformation pattern of the copper foil patch clearly reflects the growing tension-bending coupling effect under higher tensile loads. On the right of Figure 4 is the radiator-layer film contour: with increasing prestress, the region of maximum deformation consistently occurs at the inner suspension cables, and its extreme value increases from 0.36 mm to 0.66 mm. Deformation in the copper-clad region also becomes more evident, with its peak rising from 0.38 mm to 0.70 mm. The maximum and minimum value information is summarized in Table 2.  
Figure 5 presents the out-of-plane displacement contours for the 5 \(\times\) 3 configuration. The left panel (array layer) exhibits a deformation pattern similar to that of the 7 \(\times\) 3 case but with larger magnitudes: the copper foil region's peak displacement increases from 0.10 mm to 0.30 mm. The right panel (radiator layer) shows that the maximum deformation remains centered on the internal suspension cables, growing from 0.63 mm to 1.10 mm as prestress rises, while the copper foil region's peak displacement increases from 0.40 mm to 0.88 mm. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Maximum Deformation/mm**} \\ \cline{2-5}
**Prestress/N** & \multicolumn{2}{c}{**5 \(\times\) 3 Suspension Cable Configuration**} & \multicolumn{2}{c}{**7 \(\times\) 3 Suspension Cable Configuration**} \\ \cline{2-5}  & **Radiator Layer** & **Ground Layer** & **Radiator Layer** & **Ground Layer** \\ \hline
1.0 & 0.6332 & \(-\)0.4000 & 0.3698 & \(-\)0.3807 \\
2.1 & 1.117 & \(-\)0.8091 & 0.6395 & \(-\)0.6479 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Maximum deformation vs. prestress. Figure 4: Displacement contour of the thin film with a 7 \(\times\) 3 catenary array (**Left**: upper membrane; **Right**: lower membrane; **Up**: under equivalent tension force of 0.5 N; **Below**: under equivalent tension force of 2.1 N). Combining the thin-film antenna deformation characteristics shown in Figures 4 and 5, it can be seen that the upper antenna exhibits more pronounced local deformations with the periodic features of the repeating array units. In contrast, the patch area of the lower antenna shows small-amplitude, uniformly distributed deformations. Therefore, to analyze how structural deformation affects the antenna's electrical performance, one can focus on a representative unit--namely, a single patch element of the antenna. Furthermore, given the deformation magnitude of the upper film, the out-of-plane deformation of the lower film may be neglected for a simplified analysis.
# E-MQTT: End-to-End Synchronous and Asynchronous Communication Mechanisms in MQTT Protocol
## 5 Experimental Results
### Experimental Environments  
In this subsection, we describe environment information of the experiments that we conducted with our test clients and broker applications. The experiments of delay measurement (described in Sections 5.2-5.4) were conducted utilizing a pair of distinct devices. Specifically, the test broker and subscriber applications were executed on a desktop PC, whereas the test publisher application was carried out on a laptop PC. These devices are respectively designated as PC1 (for the desktop) and PC2 (for the laptop). We assumed no network congestion or failure during the experiments. Table 1 shows the detailed device specifications and network configurations of PC1 and PC2.  
For the experiments of delay measurement, we started one publisher, one broker, and ten subscriber applications. To measure one delay value, the publisher sent a query message and received a delay value. In the PUBLISH packet of the query message, we set the topic field with a one-byte string and the payload message with six bytes. The other headers of the packet remained empty or default values. In each experiment, we measured delay with sixty tests and obtained an average value. We conducted the same experiment while increasing the number of subscribers by ten until it reached eighty. In synchronous E-MQTT, the number of subscribers corresponded to the minimum number of response packets to be awaited, and the list of subscriber identifiers remained empty.  
We set another environment of experiment (described in Section 5.6) because this supplementary experiment was conducted later for the approximate measurement of energy consumption. As a specific IoT environment was not available, we executed the publisher solely on a laptop operating on battery power, while the broker and subscribers were run on a desktop PC. To measure battery usage, the publisher regularly sent a PUBLISH packet every second for 1200 times per experiment. When each experiment started and ended, we recorded the battery level provided by the operating system and obtained the amount of battery usage using the difference between the two values. Table 2 presents the specifications of the devices utilized in this experiment. Apart from the devices, the remaining experimental conditions remained consistent with the previous experiments.
###### Abstract  
The purpose of this study is to enable emergency recovery of damage caused by earthquakes in structures and prevent secondary damage by controlling progressive collapse. Although there have been many previous studies using reinforcing bars and meshes, there have been few studies using carbon grid fibers as a substitute for tension members. This study aims to quantitatively present disaster response seismic performance by manufacturing concrete panels with no layers, one layer, or two layers of carbon fiber grids inserted and to compare the flexural strength and energy dissipation capacity. Flexural strength increased by 7% with one layer and 15% with two layers compared with no layer. Energy dissipation capacity increased by 30 times with one layer and by 56 times with two layers compared with no layers, and showed great improvement in terms of seismic performance. Especially because of the large increase in the energy dissipation capacity, the carbon fiber grid reinforcement method is considered to be an effective method for improving seismic performance.  
evaluation; carbon fiber grid; reinforced concrete panel; disaster response; seismic performance
# Systematic Review of Anomaly Detection in Hyperspectral Remote Sensing Applications
## 2 Part A: Bibliometric Analysis
### Authors Analysis
Part B: An Overview of Hyperspectral Image Processing for Anomaly Detection in Remote Sensing Applications  
This section provides a mathematical framework for anomaly detection, followed by the description of specific anomaly detection techniques that are generally divided into methods that adopt structured background models or unstructured background models.
## 3 Results and Discussion
### Dependence of Extraction on SC4A Concentration  
In order to determine the stoichiometry of the extracted complex containing Cs(I) and Sr(II), the effect of SC4A concentration on the extraction was investigated. Under fixed experimental parameters, varying the SC4A concentration in the organic phase altered the distribution ratio. As shown in Figure 4, the distribution ratios of Cs(I) and Sr(II) were enhanced as SC4A concentration increased, and a linear relationship was established between log \(D\) and log [SC4A]. Specifically, the plot of log \(D_{\text{Cs}}\) versus log [SC4A] showed a slope of 1.07, suggesting 1:1 stoichiometry of Cs(I) and SC4A. Similarly, another straight line with a slope of 1.78 was obtained for Sr(II), this value indicated the participation of two molecules of SC4A and one Sr(II) in the extracted complex.
# Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines
## 2 The State-of-the-Art of UVs Performing in OWT IMR Operations
However, to realize these opportunities, the challenges that come with them need to be addressed as well, which are discussed in the next section. \begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Types** & **Ref.** & **Purposes** & **Methods** & **Application** \\ \hline \multirow{9}{*}{**UAV-UUV**} & [57] & Localization, power supply, communication hub & - & Using a waypoint tracking algorithm on a USV to provide relative heading and coordination to UUV. & Underwater survey \\ \cline{2-5}  & [58] & Navigation & - & Using the position on the aerial view acquired from a UAV to manually guide a UUV towards a target. & Survey and waste management \\ \cline{2-5}  & [59] & Communication platform & - & Using an acoustic device attached to a UAV, data can be transferred from a UUV directly to a floating UAV. & Underwater survey \\ \hline \multirow{9}{*}{**UAV-UUV**} & [60] & Mission planning, path planning, localization, navigation & - & Using visual imagery from a UAV and a UUV, a USV acts as data and an intelligent hub to autonomously plan and distribute survey missions. & Surveying of floating targets \\ \cline{2-5}  & [61] & Path planning & - & Using a USV GNSS positioning system to guide the UUV through underwater communication. & \\ \cline{2-5}  & [62] & Communication platform & - & Using an underwater acoustic channel characterization to enable effective communication between UAV, USV, and UUV. & General \\ \cline{2-5}  & [63] & Power supply, communication platform & - & Using tethered connections from a USV to UAVs and UUVs to prolong operation time. & Inspection and survey missions on offshore infrastructures \\ \cline{2-5}  & [24] & Transportation, power supply & - & Using a USV with battery charging capability to transport UAVs and CRs to an offshore wind farm. & IMR for offshore wind farms. \\ \cline{2-5}
**CR** & & - & Using a UAV or UAVs to carry CRs to an inspection site. & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._
## 7 Conclusions  
We have presented the current state of authentication, access control, and secure integration in the SG. We first defined seven objectives of the authentication protocol in order to fully provide efficient and secure communication environment. We critically evaluated the existing work, and identified future directions for developing efficient and secure authentication protocols for the future SG and V2G systems. We observed that mutual authentication among all entities and privacy prevention of communicated information is still a great challenge in the home environment as well as in the V2G network. We also found that some recent contributions based on access control mechanism are able to overcome some of the existing security and privacy issues. Further, the secure integrated communications among different control modules and entities in the SG need to be explored in detail.
## 4 Discussion  
The obtained test results are characterized by a normal distribution close to the Gaussian curve (\(p>\alpha\)). The power of the test (\(>\)80%) was sufficient to show the differences between the tested parameters of human upper limb movements. Most of the parameters determined in the studies of human hand movements are characterized by a low coefficient of variation (\(C_{v}\)\(\leq\) 25%). Therefore, they can be applied to most people, and give very important information about the dynamics of the human hand as an element controlling the movement of the anthropomorphic manipulator effectors and about the possibilities of controlling anthropomorphic manipulators by means of hand movements, controlling the position of the effector in a master-slave system.  
The values of averaged maximal speeds and averaged maximal accelerations obtained as a result of the conducted tests indicate that there are significant differences between the reaching and precise movements of the human limb. The direction of the movement (longitudinal, lateral, and vertical) has no significant influence on the maximal speed achieved. The median value of the maximal speed of reaching movements is 1 m/s, while the maximal speed for the three quartiles is approximately 1.3 m/s.  
The speed values obtained as a result of precise hand movement tests are nearly 50% lower than the speeds of reaching movements. A significant reduction in the speed value, in relation to the reaching movements, indicates that a task that requires strictly defined precision forces the operator to work at lower speeds, which significantly extends the time needed to complete the task. The results are consistent with the test results presented in [103]; however, the presented research covers a much larger range of motion and various directions.  
The conducted research showed that there are no significant differences between the velocity of motion to achieve the target and return movement--longitudinal movement--Figure 7, lateral movement--Figure 6, and vertical movement--Figure 5.  
The median value of maximal acceleration during reaching movements (all phases) was 4 m/s\({}^{2}\) and was about 50% higher than in the case of precise movements. It should be noted that the acceleration values are not fixed in the acceleration and deceleration phases. The maximal acceleration values usually occur in the initial phase and decrease quickly, although there are incidental hard deceleration cases. It is confirmed by a large difference between the values of averaged maximal accelerations and the effective values of RMS accelerations. Direct copying of such movements can result in significant dynamic loads on the manipulator. In the case of mechanical hand tracking systems, it is possible to reduce acceleration by increasing the resistance to hand movement by introducing friction or using  
Figure 20: Errors of putting the object off in relation to the \(x\) and \(y\) axis of precision tests.  
servos with haptic feedback. In the case of optical tracking systems, it may be necessary to optimize the control signals in the master-slave control system.
## 2 Materials and Methods
### Sample Preparation and Data Collection  
In order to build a data library that could train the instrument to correctly identify the different corrosive substances, the available samples were divided into two groups, training and testing set, in the proportions 60:40 (as represented in Figure 1) to ensure proper validation could be performed [28].  
For each combination of corrosive substance/container type and concentration, 3 sets of 5 samples were prepared by pouring 100 mL of the solution into 5 plastic bottles of each plastic material. Before analysis, the bottles were left to settle for 10 min to assess any potential damage to the container by the solution. After ensuring that the solution was compatible with the plastic material, each sample was scanned by holding the instrument on the side, approximately 5 mL away from the bottle. This was repeated 10 times. The procedure has been illustrated in Figure 2.  
After the spectra from the training set were collected, the bottles with corrosive solutions were kept under conditions of room temperature and lighting for a period of time no longer than 8 h to observe any potential visible changes to the plastic materials in contact with the corrosive substance. Examples of the raw spectra gathered at this stage can be found in Figure 3. Since this study exclusively explored the capabilities of the commercial tools associated with the device used, only the raw spectra could be plotted at this stage.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Corrosive** & **Stock Solution** & **Concentration 1** & **Concentration 2** \\ \hline Sulfuric acid & 97\% & 30\% & 15\% \\ Ammonium & 30–33\% & 10\% & - \\ Hydrochloric acid & 37\% & 10\% & - \\ Sodium hydroxide & 50\% & 12\% & - \\ Sodium hypochlorite & 10–15\% & 4\% & 1\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Working concentrations of the corrosive aqueous solutions explored as analytical targets.
## 3 Synchronization-Integrated Feedrate Scheduling
### Feedrate Deformation for Tool Orientation to Achieve Synchronization  
The tool-tip position curve at the curve segment joint parameters \(\bar{u}_{i},i=0,\dots,m\) and the tool orientation curve at the parameter \(\bar{v}_{i},i=0,\dots,m\) are synchronized spontaneously. Since the feedrate scheduling of the tool-tip position is completed, the motion time \(t_{k}\) along the tool-tip curve \(\mathbf{C}(u)\) in the parameter interval \([\bar{u}_{k-1},\bar{u}_{k}]\) is fixed. Thus the motion time along the tool orientation curve in the parameter interval \([\bar  
where \(T_{a}=2t_{1}+t_{2}\) represents the acceleration time, \(T_{d}=2t_{5}+t_{6}\) represents the deceleration time. Denote the constant feedrate duration \(t_{4}\) as \(T_{c}\). The feed displacement is calculated as:  
\[L_{p}=\frac{v_{s}+v_{\max}}{2}T_{a}+v_{\max}T_{c}+\frac{v_{\max}+v_{e}}{2}T_{d}. \tag{22}\]  
The goal of feedrate deformation is to generate a tool orientation feedrate profile segment by segment with the same motion time as tool-tip position and nominal orientation displacement while keep tangential kinematics under constraint. Given the tool orientation start feedrate \(w_{s}\), the tool orientation segmented arc-length \(L_{o}\), the feedrate deformation begins with computing the new constant feedrate derived form Equation (22):  
\[w_{m}=(2L_{o}-w_{s}T_{a})/(T_{a}+2T_{c}+(1+k)T_{d}), \tag{23}\]  
where \(k=w_{e}/w_{m}\) is user-defined and \(T_{a}\), \(T_{c}\) and \(T_{d}\) are the same as tool-tip position. By adjusting \(k\), different constant feedrates can be obtained to meet the tangential constraints. The updated tangential acceleration and jerk is calculated as:  
\[\left\{\begin{array}{l}a_{s}=(w_{m}-w_{s})/(t_{1}+t_{2})\\ J_{s}=a_{s}/t_{1}\\ a_{s}=(w_{m}-w_{e})/(t_{5}+t_{6})\\ J_{e}=a_{e}/t_{5}.\end{array}\right. \tag{24}\]  
If \(J_{s}\) or \(a_{s}\) still exceed the tangential constraint, we can consider stretching the acceleration time to \(T_{a}^{\prime}=T_{a}+\Delta t\) and then compute a new constant feedrate so that \(J_{s}\) and \(a_{s}\) are reduced. The deceleration process can be handled in the same way. Figure 6 is an illustration of the feedrate deformation method. The orientation feedrate profile is obtained from deformation of the position feedrate profile so that they share the same motion time but get through respective displacements to reach a specific synchronized cutter location.  
With the new constant feedrate, tangential acceleration and jerk, the tool orientation feed time is adjusted to match the tool-tip position feed time while the segmented arc-length remains the same. As a consequence, the tool-tip position and tool orientation arrive at specific points simultaneously where the two curves are synchronized.  
Figure 6: Illustration of feedrate deformation method.