esa-sceva/satcom-chunk-collection huggingface dataset:
# A Joining Procedure and Synchronization for TSCH-RPL Wireless Sensor Networks
## 4 Joining Procedure and Time Synchronization Problems
### Enhanced Beacon Period Using the RPL Trickle Timer  
This last configuration is featured in the Contiki OS when configuring a network that uses the routing protocol RPL along with the TSCH access mechanism. In this configuration, the TSCH mechanism relies on the RPL Trickle Timer to modify the transmission period of EBTT beacons. This modification avoids transmitting EBs with a fixed period, aiming to send less EBs when the network is more stable and a long period has passed since synchronization started. In this way, network congestion is considerably reduced, since when the network remains stable the number of control messages that is sent is significantly lower. However, the TSCH parameters are being modified based on the needs of RPL, which often results in much longer network connection times. It is necessary for the synchronized nodes to receive a DIS message in order to restart their Trickle Timer and send EBs more frequently. Nodes that are not yet synchronized begin the scanning process to receive beacons; however, these nodes are not able to send DIS messages since the messages are discarded at the MAC level as long as they are not synchronized. As introduced in the description of the Trickle Timer mechanism, the nodes do not restart this timer if they see that the network is circulating redundant information in the RPL control messages. This means that if a node does not receive any DIS messages, restarting the Trickle Timer on its own may take a long time, and no EBs  
Figure 4: Exchange of RPL control messages. DIS, DODAG Information Solicitation.  
will be sent in the interim, which greatly reduces the number of opportunities that new nodes will have to listen to synchronization messages.  
In this configuration, the Trickle Timer is used to modify the EBTT parameter; so, upon receiving a DIS message, nodes would be forced to be transmit more EB messages in addition to the DIOs. However, if the incoming node is not synchronized, DIS messages that can restart the Trickle Timer will not be sent. Only nodes that have synchronized but that have not obtained the RPL topology will be sending DIS messages. Figure 5 represents this configuration, in which the DIS messages are interspersed between the scan periods of the beacons.
## 2 Materials and Methods
### HPLC-DAD-MS Method  
The fruits extracts were subjected to chromatographic separation using Agilent 1200 Series HPLC--DAD (Agilent Technologies--Santa Clara, CA, USA) system, using a reversed-phase chromatography column (Zorbas 300 Extended-C18, 4.6 \(\times\) 150 mm, 5 mm) (Agilent Technologies--Santa Clara, CA, USA), solvent degasser, binary pump, automatic injector (range of up to 100 samples), and UV-VIS detector DAD (diode array detector). To identify the anthocyanin extracts components, an Agilent 6500 Series Accurate-Mass Quadrupole Time-of-Flight (Q-TOF) LC/MS QLC/TOF MS was used (Agilent Technologies--Santa Clara, CA, USA). The extracts were separated at room temperature by injecting a volume of 10 \(\mu\)L concentrated sample and filtered through a PTFE filter of 0.2 \(\mu\)m (Millipore--Merck, Darmstadt, Germany), with a flow rate of 1 mL/min (with splitter to 7:3 mass spectrometer) using several solvent systems and gradient programs. To separate and identify anthocyanins, it was used the following gradient program: isocratic 2% B, 0-7 min, 2-20% B, 7-22 min, 20-30% B, 22-30 min, 30-40% B, 30-40 min, 40-2% B from 40-42 min, and the column equilibration 2% B for another 5 min, where (A) is a mixture of ultrapure water produced with a Milli-Q Millipore system (Bedford, MA, USA): formic acid (99:1, \(v/v\)) (Sigma Aldrich--Steinheim, Germany), and (B) is a mixture of acetonitrile (Sigma Aldrich--Steinheim, Germany).  
Figure 2: Folin–Ciocalteu Gallic Acid Standard Curve.  
Steinheim, Germany):solvent A (80:20, \(v/v\)). Solvents were filtered and degassed before use. The separation was monitored by a UV-VIS DAD detector at 520 nm; an LC system was directly connected to the electrospray ionization source (ESI) mass spectrometry. Conditions selected in Q/TOF MS were: ESI in positive mode, drying gas flow (N\({}_{2}\)) 6 L/min gas temperature 220 \({}^{\circ}\)C; nebulisers pressure of 15 psig, capillary voltage 4200 V; fragmentation voltage of 200 V; and the compounds were investigated on the \(m/z\) 100-3000. The data were processed using the MassHunter Workstation software.
# Fast Type-II Hartley Transform Algorithms for Short-Length Input Sequences
## 3 Fast Algorithms for Small-Size DHT-II
### Algorithm for 3-Point DHT-II  
Now, the algorithm for the three-point DHT-II can be developed. The expression for the three-point DHT-II is as follows:  
\[\mathbf{Y}_{3\times 1}=\mathbf{C}_{3}\mathbf{X}_{3\times 1}, \tag{8}\]  
where \(\mathbf{Y}_{3\times 1}\ =\ \left[y_{0},\ y_{1},\ y_{2}\right]^{\mathrm{T}}, \mathbf{X}_{3\times 1}\ =\ \left[x_{0},\ x_{1},\ x_{2}\right]^{\mathrm{T}}, \mathbf{C}_{3}\ =\ \left[\begin{array}{ccc}1&c_{3}&b_{3}\\ 1&-1&1\\ 1&-b_{3}&-c_{3}\end{array}\right]\) with \(b_{3}=0.366\), \(c_{3}=1.366\).  
We denote \(c_{3}=1+b_{3}\) and decompose the matrix \(\mathbf{C}_{3}\) into two components:  
\[\mathbf{C}_{3} =\mathbf{C}_{3}^{(a)}+\mathbf{C}_{3}^{(b)}, \tag{9}\]  
where \(\mathbf{C}_{3}^{(a)}\ =\ \left[\begin{array}{ccc}1&b_{3}&b_{3}\\ 1&-1&1\\ 1&-b_{3}&-b_{3}\end{array}\right],\mathbf{C}_{3}^{(b)}\ =\ \left[\begin{array}{c}1\\ \phantom{-}1\\ -1\end{array}\right]\).  
Taking into account properties of structural matrices [5; 32], the computational procedure for the three-point DHT-II is represented by the expression  
\[\mathbf{Y}_{3\times 1} =\mathbf{W}_{3\times 5}\mathbf{D}_{5}\mathbf{W}_{5\times 3} \mathbf{X}_{3\times 1}, \tag{10}\]  
Figure 1: Data flow graph of the proposed algorithm for the computation of two-point DHT-II.  
\[\text{where}\,\mathbf{W}_{5\times 3}\,=\,\begin{bmatrix}&1\\ 1&\\ 1&-1&1\\ &1&1\\ &1\end{bmatrix},\mathbf{D}_{5}\!=\!\textit{diag}\!\left(\!1,\,1,\,1,\,s_{0}^{(3)},\,1 \right),s_{0}^{(3)}\!=b_{3},\mathbf{W}_{3\times 5}\,=\,\begin{bmatrix}1&1&1\\ &1&\\ &1&-1&-1\end{bmatrix}\!.\]  
A data flow graph of the proposed algorithm for the three-point DHT-II is shown in Figure 2. As can be seen, we are able to reduce the number of multiplication operations from 4 to 1. However, the number of addition operations is increased from 6 to 7.
# Hom Antenna on Chip Operating at 180 GHz Using the SiGe CMOS Process
## 3 Simulation and Measurement
### 3D Radiation Pattern  
The 3D radiation pattern is a theoretical model that is used to describe the radiation field of an antenna. The 3D radiation field pattern takes into account the radiation distribution in the three-dimensional space, including factors such as the intensity, direction, and frequency of the radiation. Radiation field patterns can accurately simulate radiation phenomena and optimize designs. Figure 7 shows the 3D field pattern radiation diagram of the electromagnetic simulation software. At a frequency of 180 GHz, this simulation result was obtained. It can be seen that the radiation direction is consistent with the expected result and radiates in the positive Z direction.
# A Lightweight High Definition Mapping Method Based on Multi-Source Data Fusion Perception
## 4 Fusion Mapping on Cloud Server
### Semantic Aggregation
#### 4.3.2 Vectorization  
Vectorization is the process of converting the same instance formed after clustering into a unique vector semantic element. For the lane line, we use third-order Bessel curve fitting to vectorize, which generates a smooth curve that closely approximates the lane line. The third-order Bezier curve can be expressed as:  
\[\mathbf{B}(\mathbf{t})=\mathbf{(1-t)^{3}P_{0}+3(1-t)^{2}tP_{1}+3(1-t)t^{2}P_{2}+t^{3}P_{3} },\ \ \mathbf{0}\leq\mathbf{t}\leq\mathbf{1} \tag{15}\]  
where \(\mathbf{P_{0}},\mathbf{P_{1}},\mathbf{P_{2}},\mathbf{P_{3}}\) are the curve control points that define the shape of the curve and \(\mathbf{t}\) is a parameter that varies between \(\mathbf{0}\) and \(\mathbf{1}\). We select four points on the lane line instance as the control points and use the least-squares method to optimize their positions to fit the Bezier curve. The resulting curve is then used to represent the lane line in the vector semantic map. The vectorization result is shown in Figure 6d.  
To instantiate discrete semantic elements, such as ground arrows, poles, traffic signs, etc., we define the distance measurement method of density clustering based on their spatial characteristics. For ground arrows, we calculate the intersection area between two samples, which is the overlapping area between two rectangular boxes. The clustering process uses the weighted average method for vectorization. To calculate the spatial relationship in all clustering processes, we use the C++ Boost.Geometry library.
## 1 Introduction
In this paper, we applied the noise or signal removal algorithm based on SS-CWT proposed by [PERSON] et al. [25] to a 1-h passive seismic dataset acquired in Sichuan, China, and verified the effectiveness of this method in enhancing passive surface waves from short time series. First, we used this method to preprocess the 1-hour passive seismic data in Sichuan to remove the prominent noise events and used cross-correlation to produce virtual shot gathers from the preprocessed noise records. Then, after cross-correlation, the method was used as a post-processing step to denoise the virtual shot gathers, improving the signal-to-noise ratio (S/N) of the virtual shot gathers and further improving the reconstructed surface waves. Next, after preprocessing and post-processing, virtual shot gathers were used for dispersion analysis with an active scheme based on the phase-shift measurement, and inversion was conducted to obtain the underground shear wave velocity profile in this area. Finally, the applicability and shortcomings of this method are discussed.
# Peroxidase-Like Metal-Based Nanozymes: Synthesis, Catalytic Properties, and Analytical Application
## 2 Materials and Methods
### Sensor Evaluation  
#### 2.5.1 Apparatus, Measurements, and Statistical Analysis  
The amperometric sensors were evaluated using constant-potential amperometry in a three-electrode configuration with an Ag/AgCl/KCl (3 M) reference electrode, a Pt-wire counter electrode, and a graphite working electrode. Graphite rods (type RW001, 3.05 mM diameter) from Ringsdorff Werke (Bonn, Germany) were sealed in glass tubes using epoxy glue to form disk electrodes. Before sensor preparation, the graphite electrode (GE) was polished with emery paper and a polishing cloth using decreasing particle sizes of alumina paste (Leco, Germany). The polished electrodes were rinsed with water in an ultrasonic bath.  
Amperometric measurements were carried out using a CHI 1200A potentiostat (I) Cambria Scientific, Burry Port, UK) connected to a personal computer and performed in a batch mode under continuous stirring in an electrochemical cell with a 20 mL volume at 25 \({}^{\circ}\)C.  
\begin{table}
\begin{tabular}{c c c} \hline
**No** & **NPs** & **Reaction Mixture and Conditions** \\ \hline
11 & Ag/Ce & 2 mL 50 mM AgNO\({}_{3}\) + 2 mL 15 mM Ce(HCO\({}_{3}\))\({}_{4}\), vigorous stirring for 5 min at 20 \({}^{\circ}\)C followed by adding 0.1 mL 100 mM NaBH\({}_{4}\); stirring for 5 min; incubation without stirring for 24 h at 20 \({}^{\circ}\)C. \\
12 & Au/Cu & 2 mL 50 mM CuSO\({}_{4}\) + 2 mL 15 mM Ce(HCO\({}_{3}\))\({}_{4}\), vigorous stirring for 5 min at 20 \({}^{\circ}\)C followed by adding 0.1 mL 100 mM NaBH\({}_{4}\); stirring for 5 min; incubation without stirring for 24 h at 20 \({}^{\circ}\)C. \\
13 & Au & 0.145 mL 58.5 mM HAuCl\({}_{4}\) + 10 mL 10 mM CTAB, vigorous stirring + 0.18 mL 100 mM NaBH\({}_{4}\); stirring for 2 h at 20 \({}^{\circ}\)C. \\
14 & Ag/Cu & 2 mL 50 mM CuSO\({}_{4}\) + 2 mL. AgNO\({}_{3}\), vigorous stirring for 5 min at 20 \({}^{\circ}\)C followed by adding 0.1 mL 100 mM NaBH\({}_{4}\); incubation without stirring for 24 h at 20 \({}^{\circ}\)C. \\
15 & Pt/Ag & 0.2 mL 48 mM H\({}_{2}\)PtCl\({}_{6}\) + 2 mL AgNO\({}_{3}\), vigorous stirring for 5 min at 20 \({}^{\circ}\)C followed by adding 0.1 mL 100 mM NaBH\({}_{4}\); stirring for 5 min; incubation without stirring for 24 h at 20 \({}^{\circ}\)C. \\
16 & Ag/Zn & 2 mL 50 mM AgNO\({}_{3}\) + 2 mL 50 mM ZnSO\({}_{4}\), vigorous stirring for 5 min at 20 \({}^{\circ}\)C followed by adding 0.1 mL 100 mM NaBH\({}_{4}\); stirring for 5 min; incubation without stirring for 24 h at 20 \({}^{\circ}\)C. \\ \hline \end{tabular} \({}^{\circ}\)—NPs obtained by a sulfide method.  
\end{table}
Table 1: Cont.  
All the experiments were carried out in triplicate trials. Analytical characteristics of the electrodes were statistically processed using OriginPro 8.5 software. The error bars represent the standard error derived from three independent measurements. Calculation of the apparent Michaelis-Menten constants (\(K_{M}\)\({}^{app}\)) was performed automatically by this program according to the Lineweaver-Burk equation.
# Selection Methodology of an Electric Actuator for
## 3 Analysis
### Computational Analysis Using MSC ADAMS
#### 3.2.1 Calculation of Stroke, Velocity and Power  
In MSC ADAMS(r) problem was setup in the work space and constraints were defined along with forces applied on the CAD model, refer to Figures 5 and 6. After setting up the problem, dynamic analysis was implemented on the nose landing gear in order to find out the power required by the actuator for retraction in 15 s. The Landing Gear was retracted by 88 degrees in 15 s on MSC ADMAS(r), as shown in Figure 7. The graphs as shown in Figure 8 were plotted for actuator stroke, translational velocity, and power consumption across time on the x axis. It can be observed that when landing gear is initially fully extended, time is taken to be 0 s. Actuator needs a stroke of 0.363 m  
Figure 4: Analytical evaluation of Stroke, Velocity, and Power for Nose Landing Gear.  
(36.3 cm) for the nose landing gear to reach the fully retracted position. Initially, the velocity is zero at fully extended position, but, as the gear starts to retract, the velocity increases until it reaches the maximum velocity of 0.0365 m/s (3.65 cm/s) at 7.5 s and then starts to decrease as the landing gear reaches it fully retracted position at 15 s. The maximum force required came out to be 2273 N, with a power requirement of 27.98 watt. The maximum power required during analysis is at 11.25 s of retraction cycle. It is concluded that maximum velocity and maximum power did not occur at same time for landing gear retraction, since there are other factors that also contribute to the power required for the retraction.  
Figure 5: Modelling of aircraft with landing gears in extended configuration.  
Figure 6: Modelling of aircraft with landing gears in retracted configuration.  
Figure 7: Computational result of retraction angle variation with time. This figure shows a total of 15 s are required for complete retraction of landing gear by 88 degree.  
The results from both the methods (computational and analytical) are compared in Table 2, and it was found that analytical expressions derived for the retraction cycle yields almost same results as the computational method. The retraction angle for both of the methods was 88\({}^{\circ}\) in 15 s. The error in stroke was calculated to be 0.16%, while it was 6.4% for maximum translational velocity. The maximum power and force requirement were also calculated with acceptable error of 3.31% and 3.62%, respectively. This verifies the authenticity of analytical expressions derived. Because analytical solution methods are usually limited to highly simplified problem in simple geometries, there is much less possibility that they can yield exactly the same results as the computational method.
# A Multisensor Approach to Satellite Monitoring of Trends in Lake Area, Water Level, and Volume
## 4 Discussion
During the same time period, this study finds similar rates (the average for the four largest lakes is 6.9 mm/day with Method 1, and 7.0 mm/day with Method 2). [PERSON] et al. also predicted that, in the absence of additional inflows, the larger lakes would disappear in 2012 (Lake 3), 2014 (Lake 1), and 2020 (Lake 4). Those predictions were accurate for Lakes 3 and 1. In this study, Lake 4 is projected to disappear between 2020 and 2022, barring any further inputs of surface water from Lake Nasser. While this study has applied its methods to one particular set of lakes with their own history and circumstances, the methods should be broadly applicable to many other lakes and reservoirs that have experienced declining water levels due to evaporation. Globally, the problem of water loss from artificial reservoirs is of increasing concern ([PERSON] and [PERSON], 2012; [PERSON] and [PERSON], 2013) and the use of automated, remote-sensing-based methods to characterize these losses and to assess variability in these systems is very promising ([PERSON] and [PERSON], 2013), though the latter focuses on water levels in only the largest lakes worldwide.
## 2 Materials and Methods
### Remote Sensing Data and Analysis  
RS techniques provide an appropriate tool for delineating spatiotemporal patterns of crop status on a per-pixel basis. The spectral characteristics of the data may be affected by a mixed-pixel problem due to the relatively coarse resolution of spatial and temporal data [41]. Therefore, we used moderate-resolution HJ-1A/B CCD imagery for analysis because this satellite constellation can revisit the same location within two days, resulting in higher temporal precision for long-term dynamic rice monitoring [68].
# From Feed to Fish--Nutrients' Fate in Aquaculture Systems
###### Abstract  
Aquaculture is increasing globally, providing protein to a growing population, but little is known regarding the nutrient budgets in aquaculture. To obtain insight into how management practices impact nutrient fluxes in freshwater aquaculture earthen ponds worldwide, we conducted a literature review. Our literature search yielded 23 papers in which nutrient budgets were reported. Our results showed that the main nutrient inputs are inlet water, feed, and fertilizers, but they varied according to location and management practices. Overall, feed and fertilizers constituted the predominant nutrient sources, accounting for up to 99% of the total inputs. The most quantified outputs were outlet water, fish, and sedimentation. Our findings indicate that only up to 20% of carbon, 45% of nitrogen, and 60% of phosphorus are assimilated by the fish. In some systems, up to 80% of carbon, 80% of nitrogen, and 60% of phosphorus accumulate in pond bottoms; in other systems, the outflow represents substantial losses of up to 16% of carbon, 76% of nitrogen, and 55% of phosphorus. More insight into nutrients' fate in fishbonds is crucial from a sustainability perspective, as feed and fertilizer use can likely be optimized, reducing operational costs and the potential impact on the surrounding environment and atmospheric greenhouse gas concentrations.  
nutrient fluxes; carbon; nitrogen; phosphorus; fish production +
Footnote †: journal:  
wastewater or--in the case of carbon and nitrogen--to the atmosphere and sedimentation) or assimilated by non-target biota. Given that feed is generally the major operational cost [8], this implies an enormous economic loss. In addition, the nutrient inputs in aquaculture are a matter of concern due to the eutrophication of the fishponds and the receiving waters [2] and as anthropogenic sources of greenhouse gas emissions [9; 10].  
Insight into nutrient fluxes, in combination with different management techniques, can eventually contribute to optimizing fish growth and minimizing potential environmental impacts. A comprehensive understanding of the nutrient dynamics in aquaculture is essential to develop effective nutrient management strategies that minimize environmental impact and promote the long-term viability of aquaculture [11].  
Hence, here we provide an overview of studies on nutrient budgets of freshwater earthen (excavated) fishponds, which are the most commonly used facility to produce finfish [1]. We aim to link observed differences in nutrient budgets to the cultured fish species and to pond management (e.g., way of feeding, fertilizer use) to obtain insight into how different practices impact the nutrient budget. Therefore, our main question is, \"How do management practices in freshwater aquaculture systems impact the nutrient fluxes, and what practices can be implemented to optimize these parameters and promote the sustainability of these systems?\".
## 2 Autonomous Driving in Adverse Weather Conditions
### Algorithmic Challenges in Adverse Weather
#### 2.2.1 Object Detection and Classification Issues  
Object detection and classification become particularly challenging in adverse weather conditions such as heavy rain, snow, or fog. These conditions can obscure or distort the appearance of objects, making them harder to detect and classify accurately. [PERSON] et al. [42] addressed this challenge by developing DriveNet, a robust multi-task, multi-domain neural network for autonomous driving. DriveNet demonstrates improved  
Figure 2: Integrated sensor systems in advanced driver assistance technologies [36].  
performance across various weather conditions by leveraging a unified architecture that simultaneously handles multiple perception tasks.  
The impact of adverse weather on object detection is not limited to visual sensors. [PERSON] et al. [43] investigated the effects of adverse weather on various sensor modalities, including cameras, LiDAR systems, and radar systems. They developed a deep multimodal sensor fusion approach that can effectively \"see through fog\" even without labeled training data for foggy conditions. This work highlights the importance of combining different sensor modalities to overcome the limitations of individual sensors in challenging weather.