esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Methodologies and Implementation
### Challenges and Limitations in Implementing DDPM for Biomedical Image Segmentation
#### 4.3.5 Sensitivity to Image Characteristics  
DDPM may exhibit sensitivity to certain types of biomedical images, especially those with highly complex anatomical structures or specific imaging artifacts. Ensuring robust performance across diverse image characteristics is essential [101; 102].
## 3 Results
### Evaluation of Phosphorus Release in Ruminal Fluid  
The amounts of phosphorus released in the ruminal fluid from oleogels with 10%, 15% and 20% CW are presented in Table 3 (and in Figure S1 for cumulative percentage comparisons). The system with 10% CW released 55.6% (126.11 \(\pm\) 1.03 mg/L) of the initially added phosphorus after 84 h, while the oleogel with 15% CW released 92.07% (208.73 \(\pm\) 3.56 mg/L) and the oleogel with 20% CW released 98% (221.85 \(\pm\) 1.13 mg/L). The phosphorus release trends as a function of the CW concentration were similar to those of the systems evaluated in the model with an aqueous medium. However, the results obtained in the model with ruminal fluid reflected that there was a greater release of phosphorus in this medium, which may be due to the effect of the conditions that generated the presence of bacteria, enzymes and other natural components of the ruminal fluid. Currently, there are no methodologies or reports on the evaluation of the nutrient release efficiency of commercial supplements in goats, so this work's methodological proposal is the first in this area. Likewise, the bolus formulation based on a CW oleogel, as well as its use and functional efficiency as a phosphorus vehicle, are also presented for the first time in this research. One of the main problems with commercial mineral supplements is that, due to their low concentration, it is difficult for goats to consume enough of the supplement to cover their requirements for this mineral [46]. Because of the formulation of oleogels  
Figure 4: Cumulative percentages of phosphorus release (P\({}^{+}\)) of oleogels with 10%, 15% and 20% candleilla wax (CW) in an aqueous medium for 84 h.  
formulated with vegetable oil and CW, it is possible to provide a better vehicle to supply phosphorus to goats and ensure the required phosphorus contribution. Evaluating the effectivity of phosphorus release in goats in vivo is the next step to investigate.
## 3 Experimental Setup and Measured Results in the Salt Mine
### Node Deployment Analysis in the Mine
#### 3.2.3 Packet Error Rate (PER) Analysis  
In Figure 7a, PER was calculated in different environments at 433 MHz using wizzi nodes, where the separation between a stationary node and a mobile node was varied in order to observe the change in PER values. The measurements were taken in an anechoic chamber, indoor corridor, outdoor plane pathway, and underground salt mine to validate the viability of the sensor nodes and to define reference propagation link performance. The PER remained consistent at 0% in the anechoic chamber; however, for outdoor environments, the PER was recorded up to 1.1% lower at 433 MHz compared to the indoor hallways results. Moreover, the peak value was recorded to be up to 1.4% for changing weather conditions. Experiments were also carried out in an underground salt mine, where reflections from lossy mine walls and irregular structures were most likely to occur and affect the overall performance of the radio link. At a Tx power of 12.6 dBm, the PER remained consistent at 0% within a range of 20 m at 433 MHz. However, it increased exponentially from 0.1 to 1.9%, with abrupt changes occurring until a range of 70 m, which means a maximum of 19 out of 1000 packets were lost during each transmission, as illustrated in Figure 7a.  
An asymmetrical link refers to a connection where there is a difference in connectivity and transmission between the Tx-Rx link and vice versa. Various factors, such as the orientation of the experimental setup, the presence of metal objects, unpredictable multi-paths, and human movement directions, can affect the number of packet deliveries over the  
Figure 7: (**a**) PER for different link ranges and (**b**) the no. of packets delivered for different RSSI values.  
radio link, resulting in significant differences in link characteristics between nodes, even with a fixed transmission power. Figure 7b displays the link asymmetry in terms of the difference in RSSI for different environments. In indoor and outdoor environments, the number of received packets was always counted between 3 to 6%, along with the highest link asymmetry of 9 dBm. A difference of 0 to 3 dB in RSSI was observed for 95% of the received packets. The underground mine behaved the same as indoor and outdoor environments and showed an asymmetry of 9 dBm. Moreover, an average variation of 3.5% was noticed for a 2 dBm asymmetry at 433 MHz for almost 80% of the received packets. In an anechoic chamber, a difference in RSSI of 0 to 2 dB was observed, with link asymmetry of up to 5 dBm at 433 MHz for 92% of the received packets. The RSSI had a mean variation of 2.36 dB and an average standard deviation of 1.8 dB for all the discussed environments.
# Low-Cost Wireless Sensing System for Precision Agriculture Applications in Orchards
## 3 Results and Discussion
### Communication Range  
The communication range between the nodes in the field depends on the communication protocols and the frequency used by the network. In our network we used the 868 MHz radio frequency for the communication of the End-nodes with the Coordinator due to its reliability, despite its shortest nominal range compared to other protocols [9]. The communication range between the Coordinator and the End-nodes was tested in real field conditions. For the in-field evaluation, one of the nodes was programmed as the Coordinator working in continuous operation and a peripheral node was programmed to send a packets every 10 s. The Coordinator was temporarily installed at a steady location in the experimental orchard, and the End-node was relocated further from the Coordinator until the point where the communication was lost. According to the results of the in-field communication range evaluation, the nodes could communicate untroubled, without missing any packets, at distances considerably longer that 250 m. Therefore, in our calculations, a maximum communication range of 250 m was taken into account. Considering that our network was based on a Star communication topology, the maximum field size that this network can serve is 36 ha, depending on the shape of the field (in our calculations we assumed the field was rectangular shaped, which is the best case, but quite common scenario). According to the official statistics released by Eurostat, in 2013 the average size per agricultural holding in the European union was 16.1 ha [24]. Therefore, the developed wireless sensors network can serve as a viable low-cost solution applicable to the majority of orchards and other agricultural crops in European countries.
## 3 Dual-Band Doherty Power Amplifier
### Linearization of Dual-Band DPA
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Reference**} & \multicolumn{6}{c}{**Lower Band**} & \multicolumn{6}{c}{**Upper Band**} & \multicolumn{6}{c}{**Test**} \\ \cline{2-13}  & \begin{tabular}{c} **Frequency** \\ **(GHz)** \\ \end{tabular} & \begin{tabular}{c} **FPeak** \\ **(dBm)** \\ \end{tabular} & \begin{tabular}{c} **Efficiency** \# \\ **(dBm)** \\ \end{tabular} & \begin{tabular}{c} **Back-Off** \\ **(GBOO \%)** \\ \end{tabular} & \begin{tabular}{c} **Efficiency** \\ **(GHz)** \\ \end{tabular} & \begin{tabular}{c} **Frequency** \\ **(dBm)** \\ \end{tabular} & \begin{tabular}{c} **FPeak** \\ **(dBm)** \\ \end{tabular} & \begin{tabular}{c} **Efficiency** \#** \\ **(dBm)** \\ \end{tabular} & \begin{tabular}{c} **Back-Off** \\ **(dBm)** \\ \end{tabular} & \begin{tabular}{c} **Efficiency** \\ **(dBm)** \\ \end{tabular} & \
\begin{tabular}{c} **Signal Type** \\ **(dBm)** \\ \end{tabular} &
\begin{tabular}{c} **Signal Bandwidth** \\ **(dBm)** \\ \end{tabular} \\ \hline
[17] & 0.85 & 28.9 & 36.8* & 6 & 29.9 & 1.7 & 27 & 25.4* & 6 & 16.8* & NB-1670+QAM/256-QAM & 12*180k / 20 MHz \\  & & & & & & & & & & & & \\
[18] & 2.15 & 47.3 & NA & 6 & 52 & 3.4 & 47 & NA & 6 & 51 & WC/DA/LTE & 20 MHz \\
[25] & 1.8 & 43 & 64* & 6 & 60* & 24 & 43 & 54* & 6 & 44 & CW/WC/DA/LTE & -/ 10 MHz \\
[7] & 0.9 & 41.9 & NA & 5 & 39.8 & 2 & 41.2 & NA & 5 & 41.4 & CW & - \\
[29] & 2.14 & 39 & 50 & 6 & 45 & 3.5 & NA & NA & NA & NA & CW & - \\
[64] & 0.88 & 41 & 40* & 6 & 33* & 1.96 & 40 & 38* & 6 & 30* & CW & - \\
[22] & 2 & 42 & NA & 6 & 49 & 2.72 & 42 & NA & 6 & 44 & CW/WC/DCMA/LTE & -/ 5 MHz \\
[21] & 2.1 & 50 & NA & 6 & 47* & 2.2 & 50 & NA & 6 & 47* & CW/WC/DCMA & -/ 5 MHz \\
[43] & 0.9 & 46 & 6 & 9 & 65 & 21.5 & 46 & 56 & 9 & 46 & CW & - \\
[23] & 0.92 & 41.5 & NA & 7 & 33* & 1.99 & 41 & NA & 8 & 29* & CW & - \\
[31] & 21.4 & 45.5 & NA & 6.5 & 45 & 2.65 & 45 & 8.5 & 6.5 & 40 & WC/DA & 5 MHz \\
[44] & 0.85 & 43 & 47.5* & 6 & 45* & 2.33 & 42.5 & 32* & 6 & 41 & CW/LTE/LTE & -/ 10 MHz \\
[46] & 0.75 & 40 & NA & 9.4 & 42* & 09 & 43 & NA & 9.4 & 72* & CW/WC/DA/LTE & -/ 15 MHz \\
[19] & 0.6 & 38.5 & 65 & 6 & 50 & 1 & 40.5 & 57 & 6 & 37 & CW & - \\
[41] & 1.7 & 45 & NA & 7 & 51 & 2.4 & 45 & NA & 9 & 45.5 & CW/WC/DA/MAR & -/ 38 MHz / 5 MHz \\
[10] & 1.9 & 36.8 & NA & 6.8 & 501.1 & 2.6 & 36.8 & NA & 6.8 & 501 & LTE/LTE & 10 MHz \\
[53] & 2.3 & 42.5 & NA & 7.2 & 30* & 2.7 & 42.5 & NA & 7.2 & 44.2* & CW/LTE & -/ 10 MHz \\
[34] & 0.6 & 40 & 76.3 & 6 & 54.9 & 1 & 40.2 & 54 & 6 & 38 & CW & - \\
[65] & 1.8 & 44 & 72 & 6 & 63 & 2.6 & 44 & 60 & 6 & 51 & CW/LTE & -/ 20 MHz \\
[52] & 2.02 & 43.9 & 62.1 & 6 & 51.1 & 2.63 & 44.6 & 71.4 & 6 & 53.3 & CW & - \\
[53] & 0.85 & 44.6 & 58 & 9 & 58 & 2.1 & 44.2 & 68 & 9 & 68 & CW & - \\ \hline \hline \end{tabular} NA: Not available. CW: Continuous wave. *: Power added efficiency PA.  
\end{table} 
Table 2: Samples of achieved dual-band DPA.
# Multi-Agent-Supported Tracking Based on Hidden Markov Model with Weighted Entropy
## 5 Discussion  
Through experimental validation, our method has demonstrated promising results. The reduction in IDs achieved by replacing the conventional Kalman filter with the HMM-based variant underscores the importance of motion context. Traditional models often fail to capture the irregular movements inherent in pedestrian trajectories, particularly during occlusions or abrupt direction changes. By modeling the two-phase motion pattern, the HMM-based Kalman filter provides a probabilistic framework that better accommodates practical situations. This improvement directly translates into improved HOTA scores (65.9 on MOT17 and 65.7 on MOT20), reflecting superior trajectory continuity. The weighted entropy mechanism addresses a fundamental limitation of fixed weighting schemes in multi-cue tracking frameworks. While appearance features dominate in sparse scenes, motion cues become more reliable during occlusions or rapid movements. The proposed dynamic calibration strategy achieves a 1.1 improvement in IDF1 and further reduction in IDs in the ablation study by balancing feature contributions in a self-adaptive way. And the multi-agent mechanism provides efficient computations as the underlying support, leading to satisfying performance on the FPS metric.  
However, our work has limitations: The two-phase motion pattern and the model that accompanies it are specialized in tracking pedestrians, resulting in incompatibility for tracking vehicles or other objects. Thus, the suitable datasets for our method are limited. Further, pedestrians from different regions may have vastly different behavioral habits, posing a great challenge to the study of pedestrian movement patterns in this work. And the real-time computation of entropy brings heavy loads to devices, decreasing the FPS metric accordingly.  
In addition, we compare the main contributions of previous works with ours in Table 4.  
\begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline \hline
**Method** & **Contributions and Limitations** \\ \hline \multirow{4}{*}{RTU++ [6]} & Constructs a general Extendable-Multiple-Node Tracking framework. \\  & Proposes RTU++ to score track proposals. \\ \cline{1-1}  & Establishes a Node-based General Tracking Data Generation method. \\ \cline{1-1}  & Lacks analysis of moving patterns for pedestrians. \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison of main contributions between previous works and ours.  
Figure 3: Tracking results of our method in crowded scenarios of MOT20 benchmark. First row is from MOT20-04. Second row is from MOT20-08.
# Experimental Tests on Solvent Solutions for the Recycling of Coated Polypropylene in Food Packaging
## 2 Material and Methods
### Selective Dissolution  
The selective dissolution technique is based on the concept that different substances are dissolved in multiple solvents or with the same solvent but at different temperatures. This technique has been studied for the recycling of materials composed of different types of plastics [21].  
Coated film samples were cropped into 5 cm squares, creating specific specimens. Two solvents, one composed of 99.9% methanol and one of KOH 1M solution, were tested for the selective dissolution reaction, which should remove the coated surface layer of the pp film samples. The KOH 1M solvent and 99.9% methanol were selected as solvents because they are used to remove non-polymeric layers from the film by manual scrubbing. This procedure is commonly performed by the Quality Control Centre of the Jindal Films Europe Brindisi s.r.l. Both solvents are relatively inexpensive and easy to produce [22]. The FDA (U.S. Food and Drug Administration) considers the two solvents risk-free when operated under good manufacturing practice [23]. Moreover, neither potassium hydroxide (National Toxicology Program, the International Agency for Research on Cancer, or the Occupational Safety and Health Administration) [24] nor methanol [25] are classified as carcinogen substances.  
In order to test for the possible effects of the magnetic stirring mechanical action, a deionized water solution was used as the control.  
Each specimen was immersed in 50 mL of the three different solvent solutions and subjected to magnetic stirring at room temperature for 15 min. After the reaction time, specimens were washed with deionized water and dried on a stove at 45 \({}^{\circ}\)C overnight. Each type of film was treated in triplicate for each of the three solutions, obtaining a total of 18 film specimens treated with selective dissolution. The specimens were labeled with a name indicating the treated film (AC or ACRC) and the solvent used (_SH\({}_{2}\)O = treated with deionized water as solvent; _SKOH = treated with potassium hydroxide 1M as solvent; _SMET = treated with methanol 99.9% as solvent).
# Bio-Inspired Dynamic Trust and Congestion-Aware Zone-Based Secured Internet of Drone Things (SIoDT)
###### Abstract  
The Internet of Drone Things (IoDT) is a trending research area where drones are used to gather information from ground networks. In order to overcome the drawbacks of the Internet of Vehicles (IoV), such as congestion issues, security issues, and energy consumption, drones were introduced into the IoV, which is termed drone-assisted IoV. Due to the unique characteristics of the IoV, such as dynamic mobility and unsystematic traffic patterns, the performance of the network is reduced in terms of delay, energy consumption, and overhead. Additionally, there is the possibility of the existence of various attackers that disturb the traffic pattern. In order to overcome this drawback, the drone-assisted IoV was developed. In this paper, the bio-inspired dynamic trust and congestion-aware zone-based secured Internet of Drone Things (BDTC-SIoDT) is developed, and it is mainly divided into three sections. These sections are dynamic trust estimation, congestion-aware community construction, and hybrid optimization. Initially, through the dynamic trust estimation process, triple-layer trust establishment is performed, which helps to protect the network from all kinds of threats. Secondly, a congestion-aware community is created to predict congestion and to avoid it. Finally, hybrid optimization is performed with the combination of ant colony optimization (ACO) and gray wolf optimization (GWO). Through this hybrid optimization technique, overhead occurs during the initial stage of transmission, and the time taken by vehicles to leave and join the cluster is reduced. The experimentation is performed using various threats, such as flooding attack, insider attack, wormhole attack, and position falsification attack. To analyze the performance, the parameters that are considered are energy efficiency, packet delivery ratio, routing overhead, end-to-end delay, packet loss, and throughput. The outcome of the proposed BDTC-SIoDT is compared with earlier research works, such as LAKA-IOD, NCAS-IOD, and TPDA-IOV. The proposed BDTC-SIoDT achieves high performance when compared with earlier research works.  
interher of drone things (IoDT); internet of vehicles (IoV); dynamic trust estimation; congestion control; ACO and GWO
## 3 Experiments and Results
### Unidirectional Probe
As in the case with the amplitude sensitivity, there is also a high deviation in frequency and the probe sensitivity for the concentration range of 0-4 mmol/L was 20 MHz/(mmol/L). According to Table 3, the dependence of the amplitude and frequency on the change in glucose concentration was also plotted. Figure 15 presents data with errors, as well as a regression curve predicting the behavior of the amplitude of the reflected signal with a change in concentration and a regression curve for a frequency change. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Concentration Level**} & \multicolumn{2}{c}{**Amplitude of the**} & \multicolumn{2}{c}{**The Minimum**} & \multicolumn{1}{c}{**Frequency at**} \\  & **Reflected Signal at a** & **Amplitude of the** & **Minimum** \\  & **Frequency of 2.235** & **Reflected Signal (dB)** & **Amplitude (GHz)** \\ \hline Blood 0 mmol/L & \(-10.722\pm 0.685\) & \(-15.131\) & \(2.336\pm 0.035\) \\ Blood 4 mmol/L & \(-18.765\pm 0.192\) & \(-19.687\) & \(2.256\pm 0.0075\) \\ Blood 5.3 mmol/L & \(-20.493\pm 0.156\) & \(-20.646\) & \(2.246\pm 0.0056\) \\ Blood 7.5 mmol/L & \(-22.265\pm 0.12\) & \(-22.636\) & \(2.235\pm 0.0048\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Values of the amplitude and frequency of the reflected signal at various glucose concentrations. Figure 14: Frequency dependence of the reflected signal from the unidirectional probe for various glucose concentrations. Frequency range 2-2.4 GHz. The data obtained indicate a high sensitivity of the probe, although there is a slight difference from numerical simulation. The sensitivity in the experimental study was 1 dB/(mmol/L) in comparison with the modeling of 1.5 dB/(mmol/L). The slight discrepancy between the experimental results and the numerical model can be explained by imperfect experimental conditions and many possible sources of noise. These can be both external factors (external radiation, re-reflections, etc. ), and internal (noise in electrical appliances and cable, the quality of the probe, the degree of evenly of the probe sticking to the investigated object, the degree of roughness of the resulting phantom surface, the electrophysical characteristics of the phantom, etc.). The very nature of the reflected signal in the experimental study is similar to the signal in the simulation. The main feature of the unidirectional probe is the change in the reflected signal when the concentration changes, both in frequency and in amplitude, which will make it possible to more accurately determine the concentration when it changes.
# Global Repeat Map (GRM) Application: Finding All DNA Tandem Repeat Units
###### Abstract  
Tandem repeats (TRs) are important components of eukaryotic genomes; they have both structural and functional roles: (i) they form essential chromosome structures such as centromeres and telomeres; (ii) they modify chromatin structure and affect transcription, resulting in altered gene expression and protein abundance. There are established links between variations in TRs and incompatibilities between species, evolutionary development, chromosome mis-segregation, aging, cancer outcomes and different diseases. Given the importance of TRs, it seemed essential to develop an efficient, sensitive and automated application for the identification of all kinds of TRs in various genomic sequences. Here, we present our new GRM application for identifying TRs, which is designed to overcome all the limitations of the currently existing algorithms. Our GRM algorithm provides a straightforward identification of TRs using the frequency domain but avoiding the mapping of the symbolic DNA sequence into numerical sequence, and using key string matching, but avoiding the statistical methods of locally optimizing individual key strings. Using the GRM application, we analyzed human, chimpanzee and mouse chromosome 19 genome sequences (RefSeqs), and showed that our application was very fast, efficient and simple, with a powerful graphical user interface. It can identify all types of TRs, from the smallest (2 bp) to the very large, as large as tens of kilobasepairs. It does not require any prior knowledge of sequence structure and does not require any user-defined parameters or thresholds. In this way, it ensures that a full spectrum of TRs can be detected in just one step. Furthermore, it is robust to all types of mutations in repeat copies and can identify TRs with various complexities in the sequence pattern. From this perspective, we can conclude that the GRM application is an efficient, sensitive and automated method for the identification of all kinds of TRs.  
t  
t ademem repeats; variations; higher order repeats; human genome Article
## 3 Experimental Analysis  
In the analysis, multi-GNSS data collected from 19 to 28 May 2013 at 10 stations in the Asia-Pacific region were employed. The sampling interval was set as 30 s. The geographic distribution of these GNSS stations is shown in Figure 1. Listed in Table 1 are the antenna types and receiver types of the 10 stations, eight of which are equipped with TRIMBLE NET89 receivers. Unfortunately, primary investigation shows that no triple-frequency BDS observable is available at the stations JOG2 and NNOR, so the following analyses, especially those relevant to BDS measurements, is mainly based on the data from TRIMBLE NET9 receivers.