esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Problem Statement
### Slow Start  
The slow start algorithm has been used as a tentative growth plan for data transmission rates when the network state and resources are unknown. On the one hand, transmission with a small amount of data will likely be completed in the slow start stage, reducing data transmission efficiency [24]. On the other hand, to reach the performance limit as soon as possible, the initial threshold for a slow start should be set to the maximum value. This means that the first slow start transmission process always ends with the occurrence of congestion events, which means that congestion is inevitable. Therefore, the exponential growth of congestion windows in classic slow start algorithms is undoubtedly a behavior that may harm network performance. To obtain higher average speeds, algorithms need to increase transmission rates faster, exacerbating the adverse impact on network performance.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Controller** & **Scheme** & **Characteristic** \\ \hline \multirow{8}{*}{Sending node} & Reno & Slow start and congestion avoidance \\ \cline{2-3}  & NewReno & Improved fast retransmit \\ \cline{2-3}  & Cubic & Use a cubic function of the time since the last \\  & & packet loss when the window grows \\ \cline{2-3}  & Vegas & Using delay as a congestion signal \\ \cline{2-3}  & Compound & Combining two methods based on packet loss \\  & TCP & and delay \\ \cline{2-3}  & \multirow{2}{*}{Bbr} & Regularly adjust the transmission rate to detect \\  & & bandwidth and RTT \\ \cline{2-3}  & \multirow{2}{*}{COUPLED} & Congestion of a subflow results in a halving of \\  & & the window length for all subflows, and the \\  & & congested subflows are terminated \\ \cline{2-3}  & SEMI- & Congestion of a subflow only results in a \\  & COUPLED & halving of the subflow window length \\ \cline{2-3}  & LIA & Solved the problem of unequal fairness between \\  & & subflows of different RTTs \\ \hline \multirow{8}{*}{Receiving node} & ICP & Reduce the sending window to A (0 \(<\) A \(<\) 1) \\  & & times when congested \\ \cline{2-3}  & \multirow{2}{*}{ICTP} & Considering the trade-off between traffic \\  & & control, security, and overhead brought about \\  & & by the size of data blocks \\ \cline{2-3}  & \multirow{2}{*}{BBR-CD} & Using average RTT instead of minimum RTT \\  & & and using filters to remove noise from \\  & & RTT samples \\ \hline \multirow{8}{*}{Network node, sending node, and receiving node} & \multirow{2}{*}{ECN} & When a network node discovers congestion, it \\  & & sets flag bits in the data packet, and the sending \\ \cline{1-1}  & & node adjusts the rate based on the flag bits in \\ \cline{1-1}  & & the received data packet \\ \cline{1-1} \cline{2-3}  & \multirow{2}{*}{XCP} & Add congestion control information to the data \\ \cline{1-1}  & & packet, and the router performs periodic \\ \cline{1-1}  & & decision processing \\ \hline \hline \end{tabular}
\end{table}
Table 1: Research on transmission rate control.
###### Abstract  
Diabetic nephropathy (DN) contributes to increased morbidity and mortality among patients with diabetes and presents a considerable global health challenge. However, reliable biomarkers of DN have not yet been established. Phosphorylated proteins are crucial for disease progression. However, their diagnostic potential remains unexplored. In this study, we used ultra-high-sensitivity quantitative phosphoproteomics to identify phosphoproteins in urinary extracellular vesicles (uEVs) as potential biomarkers of DN. We detected 233 phosphopeptides within the uEVs, with 47 phosphoproteins exhibiting significant alterations in patients with DN compared to those in patients with diabetes. From these phosphoproteins, we selected phosphorylated aquaporin-2 (p-AQP2[526]) and phosphorylated glycogen synthase kinase-3\(\beta\) (p-GSK3[7216]) for validation, as they were significantly overrepresented in pathway analyses and previously implicated in DN pathogenesis. Both phosphoproteins were successfully confirmed through Phos-tag western blotting in uEVs and immunohistochemistry staining in kidney sections, suggesting that phosphoprotein alterations in uEVs reflect corresponding changes within the kidney and their potential as candidate biomarkers for DN. Our research proposes the utilization of phosphoproteins in uEVs as a liquid biopsy, presenting a highly feasible diagnostic tool for kidney disease.  
phosphoproteome; urinary extracellular vesicles; diabetic nephropathy; biomarker Article
# Optical Design of the Goaly3 Multi-Mirror Telescope System with a Wide Field of View
###### Abstract  
A Golay3 multi-mirror telescope (MMT) system is designed in this paper. The fill factor of the Golay3 MMT is derived from the angular resolution of the telescope. An initial configuration is established according to the paraxial optical theory. A three-element aspheric corrector group is designed and placed in the converging light cone to enlarge the field of view (FOV) of the Golay3 MMT. The tolerance analysis for each surface of the Golay3 MMT is conducted using the Monte Carlo method. The design results show the FOV of the Golay3 MMT system can be increased to \(1.5^{\circ}\) with the insertion of a three-element aspheric corrector group. The results of the tolerance analysis indicate that most tolerances are loose, while some decenter tolerances relating with the aspheric surfaces are relatively tight, but still within an acceptable range.  
multi-mirror telescope; field of view; fill factor; corrector group +
Applied
## 3 Experimental Section
### Experimental Setup
In the demodulation part, firstly, the raw movie file captured by the mobile-phone CMOS image sensor was converted into grayscale format. Based on the analysis of the underwater channel attenuation under the bubbles and the rolling shutter effect (RSE) characteristics, a de-bubble algorithm was proposed to support robust UOCC transmission. A proper column matrix of grayscale values was selected from the grayscale image and linearly interpolated. The iterative threshold method [21] was employed. To mitigate the sampling point offset (SPO), we also proposed a novel sampling scheme based on binary fringe correction (BFC). When the sampling was completed, the header needed to be located in the image frame for packet reconstruction. After the above steps, the recovered data packet was examined for the bit error rate (BER) calculation so as to evaluate the transmission performance of the RES-based UOCC system. The experimental scene is illustrated in Figure 6.
# Recent Applications of Explainable AI (XAI): A Systematic Literature Review
## 4 Results
### Evaluating XAI
User studies and model retraining confirmed the practical benefits of improved explanations [213, 295]. However, the authors mentioned that the explainability of their results was limited by the lack of suitable metrics for evaluating the explainability of algorithms [294]. Finally, for the most frequent ML task of classification, the analysis of the papers, which used some metrics to evaluate their explainability results, emphasizes the importance of explainability in enhancing model transparency, robustness, and decision-making accuracy across various applications, from object detection from SAR images [182] and hate speech detection [296] to classification of skin cancer [32] and cyber threats [297]. Techniques like SHAP, LIME, and Grad-CAM provided insights into feature importance and model behavior (e.g., [124, 298, 299]). In some situations, the adopted XAI methods showed improved performance and more meaningful explanations, aiding in tasks like malware detection [177], diabetes prediction [82], extracting concepts [298], and remote sensing [300]. Evaluations confirmed that aligning explanations with human expectations and ensuring local and global consistency are key to improving the effectiveness and trustworthiness of AI systems [235]. The authors concluded that while explanation techniques showed promise, there is still a long way to go before automatic systems can be reliably used in practice [32], and widely adopted XAI metrics can help here a lot. In summary, the results reveal distinct preferences and practices in using XAI. Tree-based models, commonly used in health applications, employ various explanation forms like feature importance, rules, and visualization, while deep neural networks primarily utilize visualization. Linear and logistic regression models favor feature importance. In finance and education, tree-based and regression models are more prevalent than deep neural networks. However, despite the widespread application of XAI methods, evaluation practices remain underdeveloped. Over half of the studies did not assess the quality of their explanations, with only a minority using quantitative metrics. There is a need for standardized evaluation metrics to improve the reliability and effectiveness of XAI systems.
# Research on a UAV-View Object-Detection Method Based on YOLOv7-Tiny
## 5 Conclusions  
This study introduced a series of improvements that significantly enhanced the performance of the YOLOv7-tiny algorithm in UAV object-detection tasks. First, the VarifocalLoss function was introduced to replace the traditional _CloI_ loss function, enhancing the algorithm's ability to handle scale variations, occlusions, and class imbalances. Second, the feature fusion network was upgraded from PANet to BiFPN, improving information flow between feature layers and increasing adaptability to multi-scale objects and complex scenes. Additionally, the Partial_C_Detect detection head and Adaptive Kernel Convolution (AKConv) were incorporated, further optimizing detection accuracy and resource efficiency. Finally, the Dilated Wide Residual (DWR) attention module strengthened feature  
Figure 16: Comparison of the heat map between the algorithm of this study and the YOLOv7-tiny algorithm, with the algorithm of this study on the left and the original YOLOv7-tini algorithm on the right.  
representation, particularly in handling dynamic backgrounds and small object scenarios, improving detection performance. These enhancements collectively enabled the proposed model to balance high detection accuracy with computational efficiency, addressing the challenges posed by resource-constrained UAV platforms.  
Experimental results on the VisDrone2019 dataset demonstrated that the improved algorithm outperforms the original YOLOv7-tiny and other mainstream lightweight models, achieving higher detection accuracy and robustness while maintaining computational efficiency. The proposed model effectively reduces missed and false detections in challenging scenarios such as dense object distributions, occlusions, and complex backgrounds.  
While the proposed algorithm addresses many key challenges in UAV-based object detection, limitations remain in detecting tiny objects and densely overlapping targets. Future research could focus on refining the model's lightweight design and enhancing its robustness to extreme conditions, further broadening its applicability.  
Conceptualization, Y.M. and X.W.; methodology, Y.M. and N.Z.; software, K.W.; validation, Y.M., X.W. and K.W.; formal analysis, N.Z.; investigation, Y.M.; resources, N.Z.; data curation, K.W.; writing--original draft preparation, Y.M.; writing--review and editing, Q.G. and L.S.; visualization, X.W.; supervision, L.S. and Q.G.; project administration, L.S.; funding acquisition, Q.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
Author [PERSON] was employed by Inspur Communication Information System Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 3 Security Analysis
### Intercept-and-Resend Attack  
Intercept-and-resend attack has two situations. One is that an eavesdropper, [PERSON], intercepts quantum information form the dealer and copied it. Then she sends the copied quantum information to legitimate participants. Because of quantum no-cloning theorem, the copied quantum information can not happen for the GMCS-involved CVQSS system. The other is that eavesdroppers intercept quantum information form the dealer and send false quantum information to the legitimate participants rather than copy it. In this case, the GMCS-based (t, n)-threshold scheme protects quantum states by randomly inserting some decoy particles to the coding sequence. Every decoy particle is selected randomly from CV quantum states. Eavesdroppers can not determine the initial state and position of each decoy particles. We assume that the coding sequence has \(\Omega\) decoy particles. The attack is found with the probability \(1-(\frac{3}{4})^{\Omega}\). For \(\Omega\rightarrow\infty\), the probability will converge to 1 [33].
## 4 Results
### Comparison on a Daily Scale
In region 3, Figure 5g-i, MSWEP produced a significant ECDF for precipitation events of \(\geq\)2.5 mm/day, however, precipitation was overestimated. For precipitation events of \(\geq\)5 mm/day CHIRPS and TMPA had a significant similarity to in-situ data. PERSIANN-CDR underestimated in-situ precipitation. The performance of gridded data improved when capturing precipitation events of \(\geq\)10 mm/day, for which the ECDFs of CHIRPS, PERSIANN-CDR and TMPA were significant, although they underestimated the in-situ precipitation at daily scale. From Figure 5j-l, in region 4, MSWEP and TMPA produced significant ECDFs for all precipitation events ranging from \(\geq\)2.5 to \(\geq\)10 mm/day. For precipitation events of \(\geq\)10 mm/day, PERSIANN-CDR showed significant distribution with respect to in-situ. The GPPs consistently underestimated these precipitation events, except MSWEP and TMPA, which followed the precipitation distribution of in-situ very closely. From Figure 5, we see that on daily scales, the ECDF of GPPs and in-situ precipitation estimates for different thresholds over different regions are subjected to deviations and differences. The similarity of GPPs and in-situ precipitation increases with increase in the magnitude of precipitation, except PERSIANN-CDR. Excluding region 2, we observe that precipitation events (\(\geq\)2.5 and \(\geq\)5 mm/day) of MSWEP, TMPA showed relatively significant similarity with those of in-situ precipitation. The varying degree of similarity can possibly be attributed to different factors which may include the climate, land cover and altitude. A detailed assessment is however required to identify the source of variability. We note that these results are in agreement with [47; 51], who also reported similar performances for TMPA, CHIRPS and PERSIANN-CDR products.
## 4 Experimental Results and Analysis
### Assessment of Multi-Rx and Multi-Tx LEO-LEO Occultation Constellation Performance
#### 4.3.3 Performance of Multiple-Orbit Constellations  
Figure 15a-c, Figure 15d-f, and Figure 15g-i illustrate the 1-day, 3-day, and 9-day global coverage of occultation events for the 2 Rx/2 Txorbit, 4 Rx/4 Txorbit, and 6 Rx/6 Txorbit constellations, respectively. As shown in Figure 15a-c, the global coverage fraction of 1-day 2 Rx/2 Txorbit occultation events reaches 98% with uniform global coverage. The 3-day global coverage and the 9-day global coverage of 2 Rx/2 Txorbit occultation events reach 100%, and the number of single-grid 9-day occultation event revisited times in some areas is more than 50. Compared with the two-orbit 12 Rx/12 Tx constellation in Figure 11g-i, setting 24 satellites on four orbits, as in the 2 Rx/2 Txorbit configurations, makes it easier to form 100% global coverage. As shown in Figure 15d-i, the 4 Rx/4 Txorbit and 6 Rx/6 Txorbit constellations achieve 100% global coverage just in one day, and the number of times the 9-day 6 Rx/6 Txorbit occultation events are revisited in a single grid in most areas is more than 200.  
Figure 14: Accumulated time dependence of the global coverage fraction (GCF) (blue lines) and the occultation event number (orange lines) for the 2 Rx/2 Tx, 6 Rx/6 Tx, and 12 Rx/12 Tx constellations with the Rxi140 and Txi40 inclination orbital planes.  
The global coverage fraction and the number trend of the occultation events for the 2 Rx/2 Txorbit, 4 Rx/4 Txorbit, and 6 Rx/6 Txorbit constellations are shown in Figure 16. One can see that with the increase in the number of orbits, the slope of the number curves increases significantly; specifically, the rates of growth in the number of 4 Rx/4 Txorbit and 6 Rx/6 Txorbit occultation events are more than 22,500 times/day and 38,000 times/day, respectively. The 4 Rx/4 Txorbit and 6 Rx/6 Txorbit constellations achieve 100% global coverage just in 18 h and 12 h, respectively. It can be seen that the LEO-LEO occultation constellation composed of 36-72 satellites can meet the basic requirements of global numerical weather prediction in terms of occultation numbers and timeliness.  
Figure 15: The global coverage of LEO-LEO occultation events for the 2 Rx/2 Txorbit, 4 Rx/4 Txorbit, and 6 Rx/6 Txorbit constellations with the Rxi98 and Txi98 inclination orbital planes, illustrating the occultation numbers per 5\({}^{\circ}\times\) 5\({}^{\circ}\) latitude and longitude grid cell. The GCFs were calculated using grid cell areas according to Equation (12).
# A Novel High-Precision Imaging Radar for Quality Inspection of Building Insulation Layers
## 1 Introduction
This technology can monitor the condition of the insulation layer in real time under structural stress, but it requires precise sensor placement for long-term monitoring [19, 20, 21]. Ground-penetrating radar (GPR) is a common non-destructive testing method,but traditional radar with a center frequency below 3 GHz has low distance resolution and lateral resolution, making it difficult to achieve high-precision imaging of bonding mortar, thus failing to quantitatively assess the bonding area [22; 23; 24; 25; 26; 27]. A comparative analysis of the advantages and limitations of these detection methods is presented in Table 1. In general, the existing inspection methods are not able to image the structure of the insulation layer, such as bonding mortar, with high precision and thus achieve quantitative detection. In this paper, a kind of high-precision imaging radar specially used for the quality inspection of the external insulation system of buildings is designed by analyzing the relevant technical parameters of the bonding mortar structure determination radar of the insulation system. The radar can realize high-precision three-dimensional imaging of the bonding mortar structure, which provides data support for subsequent quantitative calculation of the laying density and the area of the bonding mortar structure, which is of great significance to the quantitative detection of the bonding mortar layer. This paper consists of five parts. Section 2 proposes the functional requirements of the system based on the structure of the insulation layer and application requirements and refines them into radar technical parameters. Section 3 introduces the composition of the radar system and the design scheme of every part. It selects the radar signal frequency based on the calculation formula of radar technical parameters and designs an ultra-wideband high-bunching antenna. Section 4 describes the radar data acquisition and processing method, which realizes the high-precision imaging of insulation layer bonding mortar structures. The radar can perform high-precision imaging of different insulation layer bonding mortar structures. Section 5 gives the conclusion.
# An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers
## 4 Performance Evaluation
### Constant Carrier Frequency Error Scene  
In test scene B, the carrier frequency error was set to 10 Hz, which indicates the carrier phase error would accumulate linearly with time. \(T_{\text{coh}}\) was set to 1 ms, while the \(C/N_{0}\) was set to 45 dB-Hz, \(d\) was set to 1 chip. This test was aimed at showing the power of FDE in the non-coherent pre-filter in the scene where the carrier phase error is beyond the effective working range of the ATAN discriminator.  
Figure 12 shows the carrier phase error estimation in test scene B. The black line represents the dynamic change of real carrier phase error. It can be seen that the carrier phase error estimated by the ATAN discriminator would be totally wrong when the real carrier phase error is outside the range of (\(-0.25\) cycle, \(0.25\) cycle). The ATAN discriminator outputs are the observations of non-coherent pre-filter, which indicates that the effective working range of the non-coherent pre-filter without FDE for carrier phase error estimation is also (\(-0.25\) cycle, \(0.25\) cycle). If these false observations are not eliminated or their weight is not reduced, the non-coherent pre-filter's estimation error will increase. Through the FDE structure, the work range of the non-coherent pre-filter for carrier phase error estimation is extended from (\(-0.25\) cycle, \(0.25\) cycle) to (\(-0.5\) cycle, \(0.5\) cycle). The enhanced non-coherent pre-filter has comparable performance as coherent pre-filter in test scene B, as shown in Table 3.
###### Abstract  
Carotenoids are crucial photosynthetic pigments utilized for light harvesting, energy transfer, and photoprotection. Although most of the enzymes involved in carotenoid biosynthesis in chlorophototrophs are known, some are yet to be identified or fully characterized in certain organisms. A recently characterized enzyme in oxygenic phototrophs is 15-_cis_-zeta()-carotene isomerase (Z-ISO), which catalyzes the _cis_-to-_trans_ isomerization of the central 15-15\({}^{\prime}\)_cis_ double bond in 9,15,9\({}^{\prime}\)-tri-_cis_-\(\zeta\)-carotene to produce 9,9\({}^{\prime}\)-di-_cis_-\(\zeta\)-carotene during the four-step conversion of phytoene to lycopene. Z-ISO is a heme B-containing enzyme best studied in angiosperms. Homologs of Z-ISO are present in organisms that use the multi-enzyme poly-_cis_ phytoene desaturation pathway, including algae and cyanobacteria, but appear to be absent in green bacteria. Here we confirm the identity of Z-ISO in the model unicellular cyanobacterium _Synechocystis_ sp. PCC 6803 by showing that the protein encoded by the shrl1599 open reading frame has \(\zeta\)-carotene isomerase activity when produced in _Escherichia coli_. A _Synechocystis_ shrl1599 mutant synthesizes a normal quota of carotenoids when grown under illumination, where the photolabeling 15-15\({}^{\prime}\)_cis_ double bond of 9,15,9\({}^{\prime}\)-tri-_cis_-\(\zeta\)-carotene is isomerized by light, but accumulates this intermediate and fails to produce'mature' carotenoid species during light-activated heterotrophic growth, demonstrating the requirement of Z-ISO for carotenoid biosynthesis during periods of darkness. In the absence of a structure of Z-ISO, we analyze AlphaFold models of the _Synechocystis_, _Zan mays_ (maize), and _Arabidopsis thaliana_ enzymes, identifying putative protein ligands for the heme B cofactor and the substrate-binding site.  
carotenoid; cyanobacteria; _Synechocystis_; zeta-carotene isomerase (Z-ISO); photosynthesis 40/1