esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In this publication, we report about the selectivity and stability of bismuth (Bi)- and tin (Sn)-based electrocatalysts for the electrochemical CO2 reduction reaction (eCO2 RR) for formate production. Bismuth and tin were successfully electrodeposited using the pulse plating technique on top of and inside of the gas diffusion layers (GDLs). The distribution of the catalyst throughout the thickness of the gas diffusion electrodes (GDEs) was investigated by using scanning electron microscopy and computer tomography; it was found that the catalyst morphology determines the performance of the electrode. Inhomogeneous deposits, with their enlarged catalyst surface area, provide more active centres for the eCO2 RR, resulting in increased Faraday efficiency (FE) for formate. The initial electrochemical characterisation tests of the bismuth- and tin-loaded GDEs were carried out under laboratory operating conditions at an industrially relevant current density of 200 mA\(\cdot\)cm\({}^{-2}\); complete Sn dissolution with a subsequent deformation of the GDL was observed. In contrast to these results, no leaching of the electrodeposited Bi catalyst was observed. An FE of 94.2% towards formate was achieved on these electrodes. Electrodes based on an electrodeposited Bi catalyst on an in-house prepared GDL are stable after 23 h time-on-stream at 200 mA\(\cdot\)cm\({}^{-2}\) and have very good selectivity for formate.  
electrochemical deposition; Sn; Bi; gas diffusion electrodes (GDE); electrochemical CO2 reduction reaction (eCO2 RR)
# Centimeter-Level Precise Orbit Determination for the Luojia-1A Satellite Using BeiDou Observations
## 4 Methodologies for the Beidou-Based LEO POD
### POD Strategy of Luojia-1A Satellite  
The reduced dynamic orbit determination method is used for Luojia-1A satellite POD. In the data processing, both code and carrier-phase observations are used to form the ionosphere-free linear combination, and the observations are resampled into 5 s. The details of the data processing strategies for Luojia-1A satellite POD are presented in Table 1
## 3 Tool Design
### Tool for Optimizing the RTD-A Controller Parameter (Tool-IV)
#### 3.4.3 Genetic Algorithm  
The genetic algorithm (GA) is a metaheuristic algorithm that depends on natural selection. The genetic algorithm works on three stages such as mutation, crossover and selection. In a genetic algorithm, individuals are generated randomly. This is an iterative process where the algorithm checks the fitness function. The fitness function produces the fitness value that represents the closeness towards optimized results. The genetic algorithm converges towards the values with optimized results [33]. In particular, the genetic algorithms avoid the local minimum efficiently [34].
# Design and Verification of a Modular Reconfigurable Test Platform for Electric Tractors
## 3 Framework Design of the Test Platform
### Control and Measurement System Design
#### 3.2.2 Communication Protocol  
CAN is attractive to the automotive and automation industries due to its simplicity, reliability, low-cost, and high-performance. More important, CAN offers a serial bus communications protocol between actuators, controllers, sensors, and other nodes in real time and is known for its strong anti-electromagnetic interference and anti-noise interference abilities [24]. Therefore, in this test platform, the CAN bus protocol was selected as the communication mode for each subsystem controller and measurement  
Figure 3: The structure of the control and measurement system for the test platform.  
system. All commands from the Controllesk are sent to the subsystem controllers and measurement system, which returns the signals and records the data through the CAN bus. The input/output interfaces of each subsystem controller need to be defined by the CAN protocol. The control system is composed of an engine electronic control unit, a generator controller, two drive motor controllers, two load motor controllers, a PTO motor controller, and a battery management system (BMS). Notably, the communication mode of torque-speed sensors is usually RS232/485. Therefore, an ST51 single-chip microcomputer was designed for the CAN communication conversion interface of the measurement system for transmitting the commands and receiving the messages.  
There is a total of six independent real-time interfaces (RTI) CAN channels in the control and measurement system for this test platform. Specifically, CAN1 is the CAN communication channel of the three load motor controllers, including two load motor controllers and one PTO motor controller; CAN2 is the CAN communication channel of the engine electronic control unit and the generator controller; CAN3 is the CAN communication channel of the six torque-speed sensors of the measurement system; CAN4 is the CAN communication channel of the BMS; and CAN5 and CAN6 are the CAN communication channels of the two drive motor controllers, respectively. The configuration of each RTI CAN channel was set up based on the ID address and the message composition (including the transmitted message and the received message) of their controllers.
# Sensory Profile of Greek Islands Thyme Honey
###### Abstract  
The sensory profiles of thyme honey from the Greek islands with different thymus pollen grain contents (A: >60%, B: 40-60%, and C: 18-40%) were studied. The results of the physico-chemical analyses fulfilled the criteria set by international quality standards and, specifically, Greek legislation (moisture content < 18%, hydroxymethylfurfural < 10 mg/kg, and diastase activity > 20 DN). The sensory results showed that there were significant differences between groups with different pollen grain contents (\(p<0.01\)) for all attributes except for floral aroma, with the Group A samples being the lightest in color (4.9 \(\pm\) 1.8) and having the highest floral odor intensity (5.0 \(\pm\) 2.0) and salty taste (3.5 \(\pm\) 1.1). Additionally, samples with the highest pollen grain content (i.e., Group A) had olfactory notes of wood/was/resin and a chemical aroma.  
uniformal thyme honey; physico-chemical parameters; descriptive sensory analysis 2021 20  
Thyme honey is one of the main blossom honeys in Greece and represents 10% of the total annual Greek honey production. It is mainly produced on the islands and on the mainland where plants of the genus _Thymus_ grow. Thyme blossoms in summer and its nectar flow depends on the weather (i.e., Mediterranean climates). Honeybees collect the nectar and produce aromatic honey that has been famous since ancient times. This type of Greek honey presents higher values of diastase activity and proline than other monofloral honeys [8], and because of its appreciated sensory characteristics, it is sold at higher prices. According to Greek legislation, thyme honey can only be labeled as unifloral if its thyme pollen percentage is equal to or greater than 18% of the total nectariferous pollen grains, and the total number of pollen grains per 10 g of honey must also be lower than 90,000.  
Several papers have been published on the physico-chemical and microscopic characteristics of thyme honey [9, 10, 11, 12, 13]. Especially concerning Greek thyme honey, studies have been conducted on its physico-chemical characteristics, pollen spectrum, mineral content, bioactive compounds, and volatile substances [8, 14, 15, 16, 17], but no data regarding its sensory characteristics were found. Over the last few years, few studies have been conducted regarding the sensory characteristics of thyme honey [12, 13, 18, 19].  
The aim of this study was to determine the sensory profile of thyme honey from the Greek islands with different thymus pollen grain contents.
# An Energy Efficient Sink Location Service for Continuous Objects in Wireless Sensor Networks
## 4 Performance Evaluation
### Total Energy Consumption
Figure 15: Comparison of total energy consumption according to simulation time (**left**) and the number of sensor nodes (**right**). Figure 16 right shows the total energy consumption according to the frequency of location updates which indicates the agility to the mobility of the sink. We vary the frequency of location updates from 1 to 4 per 5 s. As the frequency increases, the influence of the location update to the total energy consumption increases. Therefore, Figure 16 right indicates the location update efficiency of each scheme. The energy consumption of TTDD increases most sharply because the location update messages are propagated to each source individually. The energy consumption tendencies of both LBDD and OCOT are similar but considering that the location update messages in LBDD are propagated to not sources but a few inline-nodes, the location update in OCOT is more efficient than LBDD because the location update in OCOT are propagated to each boundary cluster head. This integrated location update reduces the energy consumption for location updates.
## 3 Materials and Methods
### Sentinel-1 Data Acquisition and Pre-Processing  
Sentinel-1 consists of a constellation of two satellites--Sentinel-1A and Sentinel-1B--which carry C-band SAR instruments to observe the Earth's surface. Sentinel-1 has a frequent repeat cycle of 12 days and the repeat cycle of the two-satellite constellation can offer a  
Figure 1: Study area location map for Makhuduthamaga in Limpopo, South Africa.  
6 day repeat cycle depending on the availability of observations from both of them [41]. The advantages of this configuration in the current study is that Sentinel-1 can capture the spatio-temporal variations of smallholder farms. This study used Sentinel-1 Level-1 Ground Range Detected (GRD) images, which cover the maize cropping season (November 2018-July 2019) inclusive of all the smallholder farms. These images were 22 in total, and they were acquired from the Copernicus Open Access Hub in the Interferometric Wide (IW) mode. Both the VV and VH polarizations with a 10 m spatial resolution were used.  
Pre-processing of the radar images was done in the Sentinel Application Platform (SNAP) according to [PERSON] [42]. Firstly, the orbit files were applied to update the orbit state vectors in the metadata files. Secondly, radiometric calibration was done by applying annotated image calibration constants to convert the intensity values into sigma nought values. Thirdly, speckle filtering was performed to reduce the granular noise caused by many scatters. Fourthly, the geometric distortions caused by topography were corrected for using the Range Doppler terrain correction with a 3 sec Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). Finally, the two polarizations (VV and VH) were converted from a linear scale to a decibel scale and the ratio VV/VH was calculated.  
Figure 2 illustrates the mean polarizations for selected planted maize farms and non-planted maize areas during the planting season. The mean backscatter values for the VV, VH, and VV/VH polarizations for maize are \(-13.66\), \(-20.14\), and \(0.68\) dB, respectively. The aggregated class has mean values of \(-14.83\), \(-20.67\), and \(0.72\) dB for VV, VH, and VV/VH polarizations, respectively. The VH polarization has the highest variance of 6.31 dB compared to VV polarization with 2.65 dB and the VV/VH ratio with 0.0009 dB. The VH polarization seems to respond more effectively to the growing stages of maize. A similar observation was made by [PERSON] et al. [43] when they studied the rice crop also using Sentinel-1 data. This response is attributed to an increase in the volumetric structure of maize, which increases multiple reflections of the incoming signal.
# Design and Implementation of a Multi-Function Hydrophone for Underwater Acoustic Application
## 2 System Overview  
The prototype of the proposed multi-function hydrophone is shown in Figure 1. The multi-function hydrophone consists of a piezoelectric ceramic hydrophone, a watertight compartment, and a connection. Respectively, the purposes of those components are to transform the acoustic signals to electromagnetic signals, to protect the battery and hardware, and to connect cables. The length of the multi-function hydrophone is 450 mm, and the diameter is 60 mm. The weight in the air is approximately 2.5 kg, and the power consumption in continuous working mode is about 1.8 watts. The duration of continuous working time is 7 days. The maximum capacity of the SD card is 2 TB. The working frequency band is 20 Hz to 200 kHz. The average receiving sensitivity is about \(-\)205 dB @ 1 V/\(\upmu\)Pa. The maximum sampling frequency is 256 kSPS, and the maximum gain of pre-amplifier is 56.1 dB. The parameters of our multi-function hydrophone are summarized in Table 1.  
In the following subsections, the details of the multi-function hydrophone are described in terms of hardware and software.  
Figure 1: The overview of hardware.
# Fault Prediction for Rotating Mechanism of Satellite Based on SSA and Improved Informer
## 3 Methods
### Threshold Generation  
After obtaining the prediction sequence, dynamic thresholds for each time step are generated based on the quartile threshold generation method. The quartile threshold generation method replaces the mean and standard deviation used in traditional statistical methods with the median and standard interquartile range [30], respectively. The statistical parameters in the quartile method include the data volume (N), the lower quartile (Q1), the upper quartile (Q3), and the interquartile range (IQR). The anomaly detection of the reaction wheel speed is performed by comparing the predicted data with the generated thresholds. The upper and lower limits of the threshold for the (i)-th step of the prediction sequence are set by the formulas represented as  
\[up_{i}=Q_{-}75+3*(Q_{-}75-Q_{-}25)+output_{i} \tag{13}\]  
\[low_{i}=Q_{-}25-3*(Q_{-}75-Q_{-}25)+output_{i} \tag{14}\]  
where \(Q_{-}25\) and \(Q_{-}75\) are the lower and upper quartiles of the dataset, respectively, \(output_{i}\) is the i-th output of the prediction sequence, and \(up_{i}\) and \(low_{i}\) are the upper and lower thresholds of the predicted value, respectively.
## 1 Introduction
### Notation  
We use \(V(G)\), \(E(G)\), \(v(G)\) and \(e(G)\) to denote \(V\), \(E\), \(|V|\) and \(|E|\) for a graph \(G=(V,E)\). We let \(N(v)\) denote the neighbourhood of a vertex \(v\), and let \(N^{+}(v)\) denote \(N(v)\cup\{v\}\), also called the closed neighbourhood of \(v\). If \(G=(V,E)\) and \(S\subseteq V\), then \(G[S]\) denotes the subgraph induced by \(S\). Let \(\mathcal{GS}^{+}\) be the set of all unipolar graphs and let \(\mathcal{GS}\) be the set of all generalised split graphs. Fix \(G=(V,E)\in\mathcal{GS}^{+}\). If \(V_{0},V_{1}\subseteq V\) with \(V_{0}\cap V_{1}=\emptyset\) and \(V_{0}\cup V_{1}=V\) are such that \(V_{0}\) is a clique and \(V_{1}\) is a disjoint union of cliques, then the ordered pair \((V_{0},V_{1})\) will be called a _unipolar representation_ of \(G\) or just a _representation_ of \(G\). For each unipolar representation \(R=(V_{0},V_{1})\) we call \(V_{0}\) the _central clique_ of \(R\), and we call the maximal cliques of \(V_{1}\) the _side cliques_ of \(R\). A graph is unipolar iff it has a unipolar representation.  
**Definition 1.1**.: _Let \(R=(V_{0},V_{1})\) be a unipolar representation of a graph \(G\). A partition \(\mathcal{B}\) of \(V(G)\) is a block decomposition of \(G\) with respect to \(R\) if the intersection of each part of \(\mathcal{B}\) with \(V_{1}\) is either a side clique or \(\emptyset\)._
# Review of Traffic Assignment and Future Challenges
## 3 Traffic Assignment: Theoretical Background
### Static Traffic Assignment (STA)
#### 3.1.3 Approaches to Solving Static Assignment  
To solve problems (7) and (12), several studies have relied on the Generalized Non-linear Optimization Algorithm by [PERSON] (_FW_) (1956) [30]. The minimization problem of a convex function under linear constraints is approximated from a feasible solution through manageable linear optimization problems using the simplex algorithm. The main drawback of [PERSON]'s algorithm is its slow convergence rate [31]. To improve algorithm convergence in the context of traffic assignment, related methods have been proposed in [32; 33; 34; 35]. In addition, Refs. [36; 37] have proposed methods based on restricted simplicial decomposition (\(DSR\)) to handle large networks by decomposing the assignment problem into sub-problems. Other iterative approaches are suggested in the literature. Some are based on routes [38; 39; 40]. This approach begins with an assignment solution where all used routes and their associated flows are known. Iteratively, flows may shift from high-cost routes to low-cost routes to reach equilibrium. In [38], for each \(o\)-\(d\) pair considered sequentially in a cyclic order, flows are shifted from the highest-cost route to the lowest-cost route until both routes have the same cost. When the cost derivatives at the links between the routes are known, they have been used to estimate flow movements toward the minimum-cost route for each \(o\)-\(d\) pair [37; 41]. Other approaches are origin-based [17; 40; 42] or destination-based [43; 44]. These approaches pose a challenge when circuits exist. The authors in [18] propose an origin-based search approach, limiting solutions to acyclic ones. The quasi-Newton method is employed to effectively shift flows at each iteration and eliminate residual flows. Additionally, the authors in [45] proposeda Barzilai-Borwein-based approach to expedite convergence, moving flows from costlier to less costly routes [46]. Apart from the differences in the techniques for allocating flows to the least-cost routes and the stopping criteria, the resolution of static traffic assignment works according to an iterative approach, as presented in the Algorithm 1.  
```
Initialization: Calculate initial routes (e.g., all-or-nothing assignment).  Iterations with a stopping criterion: -  Road network loading: Load demand onto the road network along the routes and obtain generalized costs (travel time: congestion). -  Generation of choice set: Compute new routes based on the network's updated generalized costs (travel time). -  Choice: Allocate demand among the routes based on the updated generalized route costs (The allocation strategy varies depending on the optimization approach used, e.g., quasi-Newton method). This involves transferring a portion of the flow to the least costly routes.
```  
**Algorithm 1** Static Traffic Assignment
## 3 Experiment  
### Accuracy Is Not Heavily Reliant on the Depth of the Neural Networks  
By analyzing the spatial distribution and spectral information of a UGS, it can be found that the UGS constitutes a kind of low-rank feature. This implies that the accurate determination of whether a location is green space can be achieved with just one or a few surrounding pixels. Excessive down-sampling (which means a larger receptive field) does not significantly enhance the accuracy of UGS segmentation task. On the other hand, using conventional methods (convolution, filtering) for down-sampling during the model's input phase leads to a loss of UGS information. To validate this hypothesis, experiments were conducted, as described in this section.  
As shown in Table 1, we used ResNet-50 as the backbone for Model-1 and consider it as the baseline. The other four models are modifications built on Model-1. In comparison with Model-1, which utilizes the complete ResNet-50 as the feature extraction backbone, Model-2 removes the last residual convolutional layer (Conv5) only. This adjustment achieves nearly identical accuracy as Model-1 while reducing device requirements and computational resources. This indicates that the feature maps with a larger receptive field output by the residual convolutional layer Conv5 in Model-1 do not contribute to the accuracy improvement in the UGS segmentation task. To further investigate the characteristics of UGS, we built Model-3 based on Model-2 by removing the max-pooling layer. Compared with Model-2, Model-3, with one fewer down-sampling operation, has larger-sized feature map output by the residual convolutional layers Conv2-4. Although the receptive field is smaller, Model-3 exhibits further improvement in the IoU and OA accuracy evaluation metrics. This suggests that, compared with models with deeper network structures, a wider model can achieve better results in UGS segmentation tasks.  
To minimize the loss of UGS information caused by down-sampling during the model's input stage, we proposed a reverse Pixel Shuffle (RPS) method. RPS is applied to Model-4. Compared with the other models, Model-4 achieves the best results with IoU and OA accuracy evaluation metrics of 86.702% and 94.393%, respectively.
## 3 Observed Damage Mechanisms in Eastern T\(\ddot{\text{u}}\)rkiye's Masonry Buildings
### Damage Modes Attributable to Poor-Quality Units and Mortar
#### 3.1.1 Adobe and Partially Fired Bricks  
The manufacturing procedure for adobe bricks often involves combining local soil, frequently rich in clay, with straw or other fibers to enhance tensile strength. The composite material is subsequently formed and permitted to undergo drying in ambient air for an extended period, spanning several days or weeks. This method is characterized by inconsistency and the absence of rigorous quality assessments. The ratio of straw, the specific kind of clay soil, the moisture content, and the drying conditions may significantly  
Figure 5: Typical failure modes of masonry walls under in-plane loads (**a–d**).  
fluctuate across several batches, leading to bricks with variable mechanical qualities and compressive strengths often recorded below 2 MPa. Freeze-thaw cycles, moisture, and humidity exacerbate the deterioration of these materials, resulting in small fractures that enlarge under lateral seismic stresses.  
Field investigators noted that complete adobe walls disintegrated during mild ground shaking, sometimes beginning with vertical fissures at inadequately bonded edges and resulting in out-of-plane toppling [41]. Primary factors were inadequate cohesiveness at the mortar-adobe contact and the inherent brittleness of the dried blocks. In residences where propriators attempted to mitigate deficiencies by applying multiple adobe layers or partial plastering with low-strength mortar, the issue persisted, signifying that the inherent characteristics of adobe necessitated more profound interventions to adequately meet seismic requirements.  
In some regions, residents or local masons try to overcome the limits of adobe by using burnt clay bricks produced in small-scale kilns. The inconsistent heating and timing mechanisms of the kilns result in partly burnt bricks that provide only slight improvements compared to sun-dried adobe [43]. The bricks often display partial vitrification, resulting in some strata being brittle or crumbly, while others may possess more density. These inherent irregularities are evident in color gradations, where darker areas indicate more intense firing, whereas lighter or muted regions often signify insufficient firing. In Figure 6, examples of this type of damage have been presented.