esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
## 4 Heterogeneous WBAN Simulator
### The Results of Measurements Used in the Simulator
#### 4.2.2 System Loss Model  
Based on the results presented in [42], the adapted system loss model can be expressed as follows:  
\[L_{\text{SL}[\text{dB}]} = \overline{L_{S}(d_{0})_{[\text{dB}]}}+10\cdot n\cdot\log_{10} \left(\frac{d_{m}}{d_{[m]}}\right)+10\cdot\log_{10}\left[\Lambda\left(n_{B[ \text{dB}]},\sigma_{B[\text{dB}]}\right)\right]+20\cdot\log_{10}\left[\Lambda \left(n_{F[\text{dB}]},\sigma_{F[\text{dB}]}\right)\right], \tag{13}\]  
where:  
* \(\Lambda\left(\mu_{B[\text{dB}]},\sigma_{B[\text{dB}]}\right)\)--random variable with lognormal distribution, which represents the power of the large-scale fading, caused by the body shadowing effect, where \(\mu_{B}\) and \(\sigma_{B}\) are the mean value and standard deviation of this distribution, respectively;
* \(\Lambda\left(\mu_{F[\text{dB}]},\sigma_{F[\text{dB}]}\right)\)--random variable with lognormal distribution, which represents the amplitude of the small-scale fading, caused by the multipath effect, where \(\mu_{F}\) and \(\sigma_{F}\) are the mean value and standard deviation of this distribution, respectively.  
In Table 1, the parameters for the LOS and NLOS conditions for both radio channels in the ferryboat environment are presented.
# Digital Twin for Supply Chain Coordination in Modular Construction
## 4 Case Study
### Results
Therefore, to predict ETA more accurately, it is essential for a digital twin to collect the location of a module while Bing Maps collects traffic conditions in real-time. Figure 4b shows the total idle time in logistics simulation for a total of 80 modules. Idle time is a value calculated by comparing the actual module arrival time (ground truth) in the simulator and ETA. Since all 80 modules have different delivery start times, traffic conditions vary. Therefore, idle time was calculated based on the average traffic pressure (i.e., number of vehicles per hour) during the logistics process. Traffic pressure was set to change randomly from 1 to 1.9 and 100 logistics simulations were performed for both the baseline-route and the DT-route. A traffic pressure value of 1 means that traffic conditions can change, but their average traffic is same as normal condition while transporting 80 modules. The normal condition refers to the average traffic flow for the given route. If traffic flow is greater than 1, the truck's average speed may decrease depending on road conditions and vice versa. Since the digital twin updates its route (DT-route) in real time and calculates a new ETA considering changed traffic, it guarantees less idle time compared to the baseline-route. As a result, while transporting 80 modules, baseline-route showed an average of total idle time about 173.2 h (standard deviation: 33.5 h). DT-route showed an average of total idle time about 15.7 h (standard deviation: 13.0 h). On average, DT-routes showed less idle time by about 157.5 h compared to baseline-route. In addition, the idle time of DT-route and baseline-route differed from the standard deviation by about 20.5. In addition, one important result to note is that logistics risks were explored in near real-time and delivery route and ETA were accurately updated accordingly throughout the logistics process. Also, Figure 4b shows that the DT-route spurs less idle time and standard deviation than the baseline-route in different traffic conditions, which implicates that idle time in logistics can be reduced when ETA is updated in real-time even though average traffic pressure changes.
# Integrated People and Freight Transportation:
## 8 Conclusions  
IPFT, a logistics innovation developed in recent years, has yet to be fully examined. Therefore, this study is carried out to guide users and researchers.  
The study aims to present a roadmap to this developing concept by outlining the general structure of IPFT. It also presents a comprehensive terminology structure for IPFT, detailing the terminologies discussed within its scope and their connections with concepts such as the sharing economy and co-modality. This concept has been introduced and is used in various studies.  
The study details research conducted at strategic, tactical, and operational decision levels. At the strategic decision level, it covers network design and long-term decision studies; at the tactical level, it includes medium-term decision planning and pricing studies; and at the operational level, it discusses scheduling and routing studies within the scope of short-term activities. Additionally, the study addresses research conducted under conditions of uncertainty.  
Opportunities and challenges for IPFT are also presented. From an economic perspective, IPFT can reduce transportation costs and support economic development. Socially, it can expand the transportation network and usable space and reduce transportation time, traffic density, and travel time. Environmentally, it contributes to sustainability and the SDGs. The study identifies the most significant challenges for IPFT as incomplete policies, high initial investment costs, passenger dissatisfaction, and planning difficulties. It discusses these challenges and offers suggestions for future work and strategies to overcome them.  
The applications highlighted in the study are also discussed in detail. The general structure of this study is expected to provide many benefits to the newly developing field of IPFT and contribute to future studies and applications.  
This research received no external funding.  
Not applicable.  
All data shared.  
[PERSON], a postdoctoral researcher at Eindhoven University of Technology (TU/e), The Netherlands, would like to thank TUBITAK (Scientific and Technological Research Council of Turkey) and Tarsus University for their financial support (Grant No: 1059B192202556).  
The authors declare no conflicts of interest.
## 3 Proposed Algorithm
### Collision Prediction and Avoidance Procedures  
The vehicle that successfully occupies the control time-slot periodically broadcasts an FI message through the corresponding control time-slot every frame. Each vehicle updates the FI message received from the 1-hop neighbor vehicle together with its FI message and broadcasts it again. Suppose that there are five vehicles as shown in Figure 8. Vehicles 2 and 5 are 1-hop neighbors, vehicle 3 is a 2-hop neighbor, and vehicle 4 is a 3-hop neighbor of vehicle 1. The third time-slot is reused by both vehicles 1 and 4, which are 3 hops away from each other. Vehicle 1 broadcasts the FI message including the information of its 1-hop neighbors, vehicles 2 and 5. And then, vehicle 2 broadcasts its FI message including the information of vehicles 1, 2 and 5, to vehicle 3. Vehicle 3 broadcast its FI message to vehicle 4, and vehicle 4 can recognize that the same time-slot is shared by its 3-hop neighbor, vehicle 1. Then vehicle 4 changes its time-slot to another time-slot to avoid collision. In this manner, the information of a vehicle is spread over all the network, so the information of each vehicle in the network can be theoretically shared across the network. However, considering the latency required to relay FI messages and the network topology change that might occur during this latency, it is unrealistic and inefficient to share the information of each vehicle across all vehicles in a network. Therefore, when constructing the FI message, it is necessary to consider the information acquisition of the vehicle within the 3-hop communication range, in which the possibility of merging collision is high. Therefore, in this study, we limit the maximum value of \"Hop info\" in the FI message by 2, so that the neighbor vehicles updated by the FI messages are located equal to or less than two hops away, and consequently each vehicle receiving the FI message can recognize up to 3-hops neighbor vehicles.  
The proposed resource collision prediction and merging collision avoidance procedures are as follows. Each vehicle verifies the existence of vehicles that use the same time-slot to that of itself. If a vehicle finds a 3-hop neighbor vehicle that uses the same time-slot as that of itself, the position of the vehicle at the next frame is periodically estimated using the proposed mobility model. When it is  
Figure 8: Broadcasting procedure.  
It is noted that the distance between vehicle \(i\) and vehicle \(j\) at time \(t+\Delta t\) is estimated as  
\[d_{ij}(t+\Delta t) =[(x_{i}(t)+v_{i}(t)\Delta t\cos\theta_{i}(t)-x_{j}(t)-v_{j}\Delta t \cos\theta_{j}(t))^{2}\] \[+(y_{i}(t)+v_{i}(t)\Delta t\sin\theta_{i}(t)-y_{j}(t)-v_{j}\Delta t \sin\theta_{j}(t))^{2}]^{1/2}.\]
###### Abstract  
The antidepressant-like activity of ethanol extract of _Ziziphus juju_ Mill var. _spinosa_ seeds (Semen Ziziphi Spinosae, SZS) was investigated by behavioral tests, such as a forced swimming test (FST), a tail-suspension test (TST), and an open field test (OFT), using mice exposed to chronic unpredictable mild stress (CUMS). In the TST, immobility times of the extract-treated groups E100 and E300 (CUMS + 100 and 300 mg/kg extract, respectively) were significantly decreased in a dose-dependent manner compared with the negative control (CUMS; \(p<0.01\), though those of E100 and E300 were higher than those of the positive control (CUMS + 15 mg/kg fluoxetine). In the FST, immobility times of E100 and E300 were decreased compared to the normal control. In the OFT, total and zone distances of E100 and E300 were significantly higher than those of negative controls (\(p<0.01\)) with a dose dependency. In liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis after behavioral tests, norepinephrine (NE) and 5-hydroxytryptamine (5-HT) levels in the hippocampus tissues of E100 and E300 were significantly higher than those of negative controls. Brain-derived neurotrophic factor (BDNF) levels in the hippocampus tissues of E100 and E300 were higher than those of negative controls. From these results, the SZS ethanol extract exhibited significant antidepressant-like effects via immobility decrease, distance increase, hippocampal NE and 5-HT increase, and BDNF expression. These results suggest that the extract could be a potential antidepressant agent.  
Ziziphus jujujuba Mill var. _spinosa_; ethanol extract; antidepressant-like effect; CUMS; FST; TST; OFT; LC-MS/MS; BDNF
## 4 Conclusions  
A novel compact waveguide OMT was discussed. It adapts the concept of twofold rotationally symmetric OMTs recently introduced in the case of side-coupling OMT designs. A specific design was optimized for operations in the K-band, and the experimental results were in line with full-wave model predictions. It has also been demonstrated that folding the single-mode ports has limited impact on the overall performance of the waveguide OMT, providing a design more adapted to additive manufacturing techniques. Compared to equivalent designs with similar very small volumes, the proposed solution has advantages in presenting a much simpler mechanical design, which is expected to reduce its manufacturing cost and to improve its yield. This is particularly significant for the design of large closely spaced array antennas that are currently considered for LEO/MEO satellite communication applications. The proposed OMT may also find applications in the design of passive dual-polarized mechanically steered arrays used for the ground segment. Future works will address the design, manufacture, and test of a representative closely spaced array based on the proposed OMT solution.  
This research received no external funding.  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: Not applicable.  
**Acknowledgments**: The author would like to thank [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] from ESA for their support with respect to the manufacture and test of the prototype.  
**Conflicts of Interest**: The author declares no conflict of interest.
# Ru(terpy)-Based Conducting Polymer in Electrochemical Biosensing of Epinephrine
## 2 Materials and Methods
### Instruments  
All electrochemical tests were carried out using a CHI-650 potentiostat interfaced with a computer using the specific software CHI-650 in a conventional three electrodes voltammetric cell. A gold disk (diameter 2 mm) or a glassy carbon (GC, diameter 3 mm) electrode was the working electrode used for the preparation of the biosensor. An Ag/AgCl (on a 3 mol dm\({}^{-3}\) KCl aqueous solution) was the reference electrode, and a graphite bar was the counter electrode. Working electrodes were polished with alumina powder (0.3 \(\upmu\)m), placed in an ultrasonic bath for 15 min, then rinsed with water and anhydrous acetone. All the electrochemical measurements for the epinephrine determination were carried out in a phosphate buffer solution (0.1 mol dm\({}^{-3}\), pH = 7.0) in an open-air atmosphere. All potential values refer to the aqueous Ag/AgCl electrode.  
Figure 1: Heteroleptic Ru-(II) complex [(TAT)Ru(Tpy-COOH)][PF\({}_{6}\)]\({}_{2}\).
# Product Design Analysis with Regard to Recycling and Selected Mechanical Properties
## 4 Discussion  
As the number of fasteners of a given type decreased, the difficulty of dismantling the product design increased, which is reflected in the values of the Total TFI evaluation measure. However, the difficulty of disassembly should be evaluated in conjunction with other recycling assessment measures such as total recycling profit. In the product design variants analysed, the worst variant (Variant 2a) was 2% less profitable than the best variant (Variant 1a), as a result of the relationship between material recycling profits and product dismantling costs.  
On the other hand, the opposite trend can be observed with regard to product performance. Due to the clearances occurring between the bolts and the holes in the plates to be connected, the stiffness of multi-bolted connections was significantly lower than that of corresponding multi-riveted connections. In the case of connections with seven fasteners, the relative difference in the stiffness of the connections was almost 84% and increased even slightly as the number of fasteners was reduced. Similarly, the reduced stresses occurring in multi-bolted connections reached higher values than those observed in multi-riveted connections.  
It should also be noted that, as the number of fasteners, both bolts and rivets, decreased, the mechanical properties of the connection deteriorated. Removing one bolt from the connection resulted in a stiffness reduction of almost 11%, while removing two bolts from the connection resulted in a stiffness reduction of almost 26%. In contrast, in the case of riveted connections, the removal of one rivet from the connection led to a stiffness reduction of about 3%, while the removal of two rivets from the connection led to a stiffness reduction of less than 5%.  
To combine the advantages of multi-bolted and multi-riveted connections, one could consider creating a hybrid connection that uses both types of fasteners (bolts and rivets). An attempt to analyse such connections was made, for example, in [70]. In contrast, when considering the need to melt aluminium alloy and steel during the recycling process together (if the connection could not be dismantled), it would be necessary to investigate how impurities would affect the mechanical properties of the aluminium alloy after recycling [71].  
Two limitations of the presented study can be identified. The first limitation concerns the omission of factors such as the effect of fastener preload on connection strength [72,73] or fatigue caused by external loads [74]. The second limitation concerns the disassembly of the rivets. This study assumes that material loss during disassembly of this type of  
Figure 17: Reduced stress maps for the fasteners in the following cases: (**a**) Variant 1a; (**b**) Variant 2a.  
connection is negligible, due to the relationship between the masses of the connected and connecting parts. These limitations will provide directions for future research.
# Bounce: A High Performance Satellite-Based Blockchain System
## 8 Limitations and Future Work  
The main experimental limitation of our prototype system is that it's end-to-end performance has been tested only in a terrestrial setup. The earth-to-satellite numbers are derived from our previous experiments with the International Space Station (ISS) [3]. Since the ISS operates at an altitude of 400 km and near-Earth satellites (like Starlink) are slightly higher at 550 km, communication with near-Earth satellites should experience an increased latency of a little less than one millisecond compared to the ISS.  
As it happens, the primary delay observed in communication with the ISS during previous experiments was not due to the speed of light, as the latter accounts for only 1.33 milliseconds for a 400-kilometer distance. Instead, the delays stemmed from other factors such as relays, communication protocol overhead, and retransmissions caused by packet loss. Packet loss may result from cosmic radiation, electromagnetic interference, or Earth's atmospheric disturbances. Future work is needed to test with various brands of low earth orbiting satellites.  
Experiments involving wide-area inter-cluster communication are another direction for future work. In the current setup, the Sending Station and the Broadcast Ground Stations to which it distributes transactions are within the same cluster, using homogeneous hardware. Although the hardware differs across clusters in our experiments, the effects of heterogeneous and geographically distributed hardware on performance remain unexplored. Investigating the use of multicasting to accelerate inter-cluster communication could be a valuable direction for future studies, given recent advances in high-throughput multicast systems for the cloud [59].  
Figure 10: The processing times of the accumulator are different for different numbers of transactions. One billion wallets were initialized, and the transactions were generated with randomly selected sender wallet ID and receiver wallet ID from the one billion wallet pool. Based on five runs on a single node of CloudLab c220g5 hardware, 8 million transactions can be handled in 2 s. This is more than the 5.2 million transactions that the CloudLab implementation delivers but less than a larger distributed system could handle. We leave parallel accumulator design to future work.  
If distribution causes the construction of individual Merkle Trees to increase in time, that will increase the response time. However longer Merkle Tree construction times will not affect the throughput, because construction and sending can be done in a pipelined fashion.
## 3 Experiments and Analysis
### Speed Analysis  
The execution times of all methods are measured as frames per second (FPS). All of the FPS are generated on a personal computer with a 2.10 GHz six-core i7-9750H CPU and GeForce GTX1660 Ti-6G graphics card.  
Table 4 shows that with an input image size of 720 \(\times\) 576, YOLOv4 [24] is the fastest at 31 FPS, followed by our method at 21 FPS. The results of speed prove the near real-time performance of our method. In addition, the frame rate of the GHPNet network with \(1\times 1\) convolution and without \(1\times 1\) convolution is also compared. It can be seen that the frame rate after adding \(1\times 1\) convolution is increased by 2.2 FPS, indicating our algorithm can improve the efficiency of target detection by reducing network parameters.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & \multirow{2}{*}{**Year**} & \multirow{2}{*}{**Backbone**} & \multicolumn{3}{c}{**Detection(\%)**} \\ \cline{3-5}  & & & **P** & **R** & **F1** \\ \hline U-Net [29] & 2015 & U-Net & 78.5 & 76.3 & 77.3 \\ Faster R-CNN [17] & 2017 & VGG16 & 75.8 & 71.0 & 73.3 \\ Mask R-CNN [18] & 2017 & ResNet-101-FPN & 80.4 & 77.6 & 79.0 \\ YOLOv4 [24] & 2020 & CSPDarknet-53 & 87.7 & 85.5 & 86.2 \\ DRU-Net [31] & 2021 & U-Net & 86.8 & 83.6 & 85.2 \\ DNA-Net [32] & 2021 & U-Net & 84.4 & 78.4 & 81.2 \\ Our method & 2022 & VGG16+U-Net & 88.3 & 87.4 & 87.8 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of detection performance on TIV dataset.  
Figure 7: \(Cont.\)
# A LiDAR-Based Backfill Monitoring System
## 3 Methods
### Slurry Points Determination and Generation
#### 3.2.2 Surface Point Generation Using the Moving Sampling Method  
The process of 3D surface reconstruction creates a continuous 3D surface from a set of scattered 3D point data. It is necessary to ensure that the point cloud model is watertight, otherwise the void will cause the normal vector to be miscalculated, and the generated 3D grid model may not be watertight. However, according to the work in the previous section, substituting the coefficient of the plane equation into the tunnel point cloud model can only obtain the intersection boundary between the backfill slurry surface and the tunnel. However, there is no point on the slurry plane. Therefore, it is necessary to generate points on the slurry surface.  
Since the front of the LiDAR scanning space is the positive direction of the x-axis, which is also the orientation of the tunnel, the moving sampling method can be used to generate plane point clouds according to this feature. First, the points with the maximum and minimum x values in the intersection boundary between the slurry surface and the tunnel are obtained, and named as x_max and x_min, respectively. Sampling points are arranged every certain distance from x_min to x_max. If there are more than two points on the intersection boundary equal to the x-coordinate of the sampling point, a line point cloud is uniformly generated on the line between the two farthest points between these points. By moving the sampling point from x_min to x_max according to the above method, a uniform point cloud covering the plane of the intersection boundary can be generated, as illustrated in Figure 5.  
Figure 4: Slurry points determination.
# Defense and Security Mechanisms in the Internet of Things: A Review
## 5 Defense Mechanisms in IoT Environments
### Summary  
Considering the techniques and methods used for security mechanisms in IoT environments, we can indicate the following advantages and disadvantages.  
* High protection effectiveness thanks to encryption (e.g., ECC, TLS) and multi-factor authentication.
* The use of blockchain technology ensures non-repudiation and data transparency.
* Lightweight protocols are optimised for devices with limited resources.  
* High computational complexity for some protocols (for example, blockchain in low-power IoT systems).
* Lack of scalability in some protocols, especially in environments with many devices.
* Dependence on specific formal analysis tools, such as AVISPA or Scyther, limits solutions' universality.  
A similar list can be drawn in the context of defense mechanisms dedicated to IoT solutions:  
* IDS and AI-based anomaly detection systems achieve high precision in detecting threats.
* System optimisations, such as feature selection and hybrid learning, improve detection efficiency.
* Machine learning-based protection mechanisms are flexible to new types of attacks.  
* High demand for data for training AI models can be problematic in real time.
* Many false alarms in IDS can reduce the system's operational efficiency.
* Hybrid mechanisms (e.g., TIML) can be challenging to implement in resource-constrained environments.