esa-sceva/satcom-chunk-collection huggingface dataset:
# Unbridled Integons: A Matter of Host Factors
## 4 Host Factors Influencing the Expression of the Integrase
### Other Factors Influencing the Expression of the Integrase  
#### 4.2.1 Catabolite Repression of the Integrase  
As mentioned above, a CRP box is present upstream of the P\({}_{\text{C}}\) promoter of the SCI in _V. cholerae_ (Figure 3) [18]. This is also true in other species of _Vibrio_, so this might be characteristic of SCI in general [18]. Contrary to class 1 MI, in which P\({}_{\text{C}}\) and P\({}_{\text{int}}\) are facing each other, in SCI, they are back-to-back. Consequently, the CRP box that regulates the expression of SCI cassettes also regulates the expression of the integrase. Upon binding of the cAMP-CRP complex on its motif, the expression of the integrase is enhanced to reach a significant level and allow for cassette rearrangement. As mentioned above, the CRP regulon is activated when rapidly metabolizable carbon sources are scarce and can therefore be considered as a stress response just like the SOS response, except that the range of stresses that can induce it is much broader. In its natural aquatic niche, _V. cholerae_ forms biofilms on the shells of crustaceans and mostly grows using chitin as a carbon source. In this adverse environment, where both the metabolic stress and the interspecies competitiveness are high, the induction of the CRP regulon and subsequent SCI rearrangements might provide a decisive adaptive advantage. Obviously, there is also a cross talk with the regulation of competence through the metabolization of chitin, especially since CRP induces the HapR quorum-sensing regulator that is another essential player in the induction of competence in _V. cholerae_. The synergy between the CRP regulation and HGT induced SOS response highlights the very high adaptive potential provided by SCI in environmental contexts. In contrast, CRP represses virulence factors of _V. cholerae_ (the cholera toxin and the toxin-coregulated pilus), promoting its ability to colonize a medium rich in nutrient that is the human intestine. Hence, the catabolite repression of the integrrase is illustrative of the bimodal lifestyle of _V. cholerae_ that alternates between a marine environment and a pathogenic context. The CRP regulation adds another layer of complexity that links plasticity of the SCI with multiple environmental cues. Importantly, this link does not exist in MI since, as said above, they are devoid of CRP boxes. We might argue that, by nature, MI are susceptible to be active in many different bacteria with many different lifestyles, while SCI are much more adapted to their host since they co-evolved for hundreds of millions of years [65]. The double regulation pathway of the SCI integrases represents the ability of the host to optimally exploit the \"adaptive machines\" that are SCI.
## 7 Conclusions  
To further enhance the service quality of the AOS for handling massive heterogeneous services, this paper proposes an advanced intelligent frame generation (AIFG) algorithm designed to meet differentiated QoS requirements. Based on the classification framework for delay-sensitive and non-delay-sensitive services, real-time frame generation and high-efficiency frame generation algorithms are designed for each type of service. In the real-time framing algorithm, this paper models the optimal framing time threshold calculation problem of delay-sensitive services as a Markov decision process and uses the reinforcement learning algorithm to obtain the optimal solution. For non-delay-sensitive services, the high-efficiency frame generation algorithm ensures that the frame is filled before transmission and it is adopted to maximize frame utilization. Simulation results show that compared to traditional frame generation algorithms and the learning-based DQN algorithm, the proposed algorithm accommodates the different transmission needs of real-time and non-real-time services, reduces the average queue delay for real-time services, increases the average multiplexing efficiency for services, and improves the overall network service quality of the AOS. For future work, efforts can focus on extending AIFG to real-world scenarios with more complex environmental dynamics and hardware constraints. The algorithm's reinforcement learning-based structure and modular framing design also provide a flexible foundation for further research in intelligent communications across other delay-constrained or resource-limited network environments.  
Conceptualization, J.P. and J.C.; methodology, J.P.; software, J.P.; validation, J.P., H.S. and J.C.; formal analysis, J.P.; investigation, J.P., H.S. and Y.F.; resources, J.P.; data curation, J.P.; writing--original draft preparation, J.P.; writing--review and editing, J.P. and H.S.; visualization, J.P.; supervision, J.P. and J.C.; project administration, J.P.; funding acquisition, H.S. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the Key Laboratory of Intelligent Support Technology for Complex Environments, Ministry of Education (No. B2202401).  
Not applicable.  
Data Availability Statement: Data are contained within this article.  
We would like to thank for the technical support provided to us by the Key Laboratory of Intelligent Support Technology for Complex Environments, Ministry of Education.  
Author [PERSON] was employed by The 28 th Research Institute of China Electronic Technology Group 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 Experiment
### Statistical Analysis  
The evaluation indices for each individual were analyzed. Our previous work reported significant decreases in sEMG in the tibialis anterior when dorsiflexion was assisted with our system upon toe-off [27], referenced as the AST0 condition in this experiment. Therefore, the physiological index was analyzed to observe whether voluntary dorsiflexion was induced with delayed assistance compared to that with instant assistance. For all participants' processed sEMG results, a Kruskal-Wallis H test was used to analyze whether there were overall significant differences between conditions AST0, AST0.5y, ASTy, and AST1.5y. If significant differences were observed, a Dunn test with Bonferroni correction was used to compare pair-wise differences between all delayed-time assistance and AST0 conditions.  
The other stated goal for our identified optimal dorsiflexion assistance timing is to suppress compensatory movements. That is, a decrease in swing width and hip hike compared with those in the SCG condition was expected. Meanwhile, ankle dorsiflexion angle and limb shortening could affect the extent of compensatory movements [6; 10]. Thus, the influence of assistance timing on this is also considered. A Kruskal-Wallis H test was used to compare kinematic indices among all measured conditions. If overall significant differences were observed, a Dunn test with Bonferroni correction was used to compare differences between indices in SCG and those in each assistance condition.  
Analysis results of 0.01 \(\leq p<\) 0.05 were interpreted as statistically significant, and \(p<\) 0.01 was interpreted as highly statistically significant. Moreover, 0.05 \(\leq p<\) 0.10 was interpreted as marginally statistically significant. All analyses were conducted with SPSS 27 (IBM, Armonk, NY, USA).
## 3 Results
### MobileNet Lemon Bruising Classifier Results: Confusion Matrix and Precision-Recall Curves
Finally, some models are trying to leverage different techniques like Channel Shuffle Operation and Pointwise Group Convolution [35; 36] to provide highly efficient models which could be used on embedded environments, like ShuffleNet and MobileNet. In contrast, these models sacrifice their generalization capacity power. Although they were easier to train and less storage is required for them, they could not achieve a lower loss, not even on the training set. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model Name** & **Accuracy \%** & **F1-Score** & **AP** & **AROC** \\ \hline ResNet & 90.47 & 0.9046 & 0.95 & 0.97 \\ DenseNet & 85.71 & 0.8547 & 0.91 & 0.95 \\ ShuffleNet & 80.95 & 0.7974 & 0.73 & 0.85 \\ MobileNet & 73.80 & 0.7147 & 0.75 & 0.85 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Results of deep learning models evaluation comparison by their classification accuracy (%), F1-score, Average Precision (AP) and Area under the ROC curve (AROC): ResNet, DenseNet, ShuffleNet, and MobileNet.
# Characterization of the Aroma Profile of Commercial Prosecco Sparkling Wines
## Results and Discussion
### Odor Activity Values  
In order to assess the compounds that contribute most to Prosecco aroma, odor activity values (OAV) were calculated for each compound. Compounds with an OAV \(>\) 1 or with a concentration greater than their olfactory threshold were considered to have an impact on the aroma of the wine. Table 4 shows the compounds which showed OAV values \(>\) 1 in at least one sample. The data showed that the compounds with higher OAV values were mainly the esters. The three highest were, in descending order, ethyl octanoate, ethyl hexanoate and isoamyl acetate. Ethyl butanoate and ethyl 3-methylbutanoate also showed mean values above 1. This suggested that Prosecco wines are mainly characterized by the fruity notes contributed by fermentative esters. Among the other compounds with OAV > 1, fermentative compounds were found such as octanoic acid, hexanoic acid, 3-methylbutanoic acid, isoamyl alcohol, and \(\beta\)-damascenone, which can act as an aroma exhauster of fruity notes. Compounds responsible for aging notes such as TDN and TPB, kerosene, and tobacco, in some samples, could have contributed to the overall odor by affecting the fruity notes characterizing Prosecco. VSC compounds such as dimethyl trisulfide and dimethyl sulfide, despite low concentrations, could also have played a role in some samples, showing mean OAV values of 3.7 and 0.7, respectively.
# Structural Methodologies for Distributed Fault Detection and Isolation
## 4 Equation-Based Distributed Fault Detection and Isolation
### Problem Formulation  
An equation-based solution approach is formulated for designing a distributed diagnoser. For the given set of subsystems \(S_{1},S_{2},\cdots S_{n}\), when there are faults that are not locally detectable or isolable in one or more subsystems, it is necessary to consider the following cases:  
1. \(f_{k}\in F_{i}\) is not locally detectable.
2. \(f_{1}\in F_{i}\) and \(f_{m}\in F_{i}\) are not locally isolable from each other.
3. \(f_{n}\in F_{i}\) is not locally isolable from \(f_{o}\in F_{j}\) and \(f_{o}\
otin F_{i}\).  
The last case represents a scenario where a subsystem fault is not locally isolable from a fault outside of the subsystem. This scenario can happen because a fault occurrence can have consequences beyond the original subsystem. Designing distributed diagnosers that account for these three scenarios is the focus in this section. After addressing each of these situations, we derive an integrated approach to distributed FDI and derive algorithms that apply to complex, dynamic systems made up of a number of subsystems.  
For each subsystem, it might be necessary to augment the subsystem model with additional equations that are typically acquired from the neighbors of the subsystem, such that all of the faults associated with the augmented model are locally detectable and isolable. A set of equations is minimal if there is no subset of equations that provides the same detectability and isolability. More formally, the problem of designing a diagnoser for a particular subsystem \(S_{i}\) can be described as follows.  
Consider \(\mathcal{N}_{Si}=\{S_{1},S_{2},\ldots,S_{l}\}\setminus S_{i}\) as the set of neighboring subsystems to subsystem \(S_{i}\). To address the three situations mentioned above, an algorithm is to be developed to find a minimal equation set \(E_{o}\) in \(\mathcal{N}_{Si}\) that guarantees maximal structural detectability and isolability for subsystems faults \(F_{i}\), i.e., that solves the optimization problem:  
\[\begin{array}{rl}\min_{E_{o}\subseteq E_{i}}&|E_{o}|\\ \text{s.t.}&D(S_{i}|E_{o})=D(S_{i}|E_{l}),\\ &I(S_{i}|E_{o})=I(S_{i}|E_{l}),\end{array} \tag{11}\]  
where \(E_{l}\) represents the set of all the equations in \(\mathcal{N}_{Si}\), \(D\) represents the set of detectable faults in \(F_{i}\), and \(I\) represents the set of isolable faults in \(F_{i}\) from the system faults \(F\).  
**Example 6**.: _Consider the first subsystem of the running example \(S_{1}\), \(e_{10}\) makes \(f_{1}\) and \(f_{2}\) detectable and isolable from all the other faults in the system. Therefore, \(A_{1}=\{e_{10}\}\) is a minimal solution to the problem._  
In this section, we present a method to make all the faults in a subsystem locally detectable (Situation (1) above). We also discuss the solution to the fault isolability problem (Situation (2) above) and prove that if we address the first situation, the third situation is automatically taken care of.
## 4 Research Challenges and Opportunities
### System Stability and Reliability  
During the past decade, the system stability and reliability problem of wireless sensor networks has been widely studied in order to measure physical parameters correctly and effectively, as well as to prolong the lifetime of the system dramatically [82, 83]. [PERSON] _et al._[84] studied the reliability and message delay for cooperative wireless distributed sensor networks subject to random failures. [PERSON] _et al._[85] analyzed the reliability and availability of wireless multi-hop networks with stochastic link failures. [PERSON] _et al._[86] presented a methodology using a topology control mechanism for the reliability evaluation of a WSN. [PERSON] _et al._[8] proposed a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of wireless sensor networks in typical industrial environments.  
Considering the aggressive and complex environment, it is very important to analyze the system reliability in a marine environmental monitoring system using wireless sensor networks. Therefore, the research on the reliability of a WSN-based marine environment monitoring system should take into account the following aspects.  
1. _Battery life issues:_ As mentioned above, marine sensor nodes (sink nodes) consume more energy than other kinds of wireless sensor nodes. Therefore, the battery life issue always affects the system reliability.
2. _Communication relay issue:_ The communication relay affects dramatically the system reliability, when some nodes fail or simply disappear.
3. _Severe environment conditions:_ The marine environment always has external interference from ships, fishes, and birds, and has severe weather conditions such as waves, marine currents, tides and typhoons. Such severe environment conditions further influence the system reliability.
## 3 FKP-DGPS Algorithm
### Real-Time FKP-DGPS Algorithm [25, 26]  
Using the modified FKP corrections, shown in Equations (5) and (6), the PRC in message type 1 of the RTCM version 2.3 can be described as follows.  
\[\begin{split} PRC_{FKP-DGPS}=PRC_{DGPS}+PRC_{FKP}\\ PRC_{FKP}=\delta T_{FKP}\rightharpoons\Delta_{u}T_{\text{model}}- \delta I_{FKP}\end{split} \tag{8}\]  
In other words, we decoded the received message type 1 and integrated the PRC in the message with the modified FKP corrections using the FKP gradient information typically transmitted every 10-60 s. In addition, the tropospheric delays are generated using the Niell mapping function and Saastamoinen tropospheric zenith-delay model, which are recommended in the RTCM standard document. The integrated PRC of the FKP-DGPS is encoded in accordance with the format of the original message type 1.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Data Field** & **Data Type** & **Number of Bits** \\ \hline GPS Satellite ID & unsigned int6 & 6 \\ GPS Issue of data ephemeris (IDOE) & bit(8) & 8 \\ N0: Geometric gradient (North) & int12 & 12 \\ E0: Geometric gradient (East) & int12 & 12 \\ NI: Ionospheric gradient (North) & int14 & 14 \\ EI: Ionospheric gradient (East) & int14 & 14 \\ Total & & 66 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Structure of message type 1034 in RTCM version 3.1.  
Figure 4: Structure of message type 1 in RTCM version 2.3.  
Figure 5 shows the process of the real-time FKP-DGPS algorithm. First, the user and correction data are acquired such as the DGPS correction in the RTCM version 2.3 and the FKP correction data in RTCM version 3.1. Using the collected data, the tropospheric delays are generated, and the FKP corrections are calculated as explained previously using Equations (5) and (8). Finally, it is necessary to encode the generated FKP-DGPS correction in the form of message type 1 in the RTCM version 2.3 to directly apply it to the commercial low-cost L1 single-frequency GPS receiver. Thus, we can acquire the FKP-DGPS position in real-time at the output of the receiver.
## 2 Results  
### CsMIXTA Is Urregulated during Female Flower Development  
MIXTA has been reported to be involved in glandular trichome formation in various plant species, such as snapdragon and artemisinin [12; 14]. We searched the NCBI database using the known MIXTA sequences from snapdragon and artemisinin to identify a homolog in _Cannabis sativa_. We named the cannabis gene CsMIXTA. We first determined _CsMIXTA_ expression in different tissues and during female flower development in a hemy variety, Cherry Wine (CW). _CsMIXTA_ is highly expressed in flower tissues compared to the vegetative tissues (Figure 1A). _CsMIXTA_ is also expressed in stem and leaf tissues, where trichomes are also present. Interestingly, _CsMIXTA_ was detected in isolated trichomes, suggesting that _CsMIXTA_ may have distinct functions in processes other than trichome initiation. We further examined _CsMIXTA_ expression during a period of 7-week flower development. The results showed that _CsMIXTA_ was significantly upregulated in week 5 and reduced thereafter (Figure 1B). _CsMIXTA_ showed a similar expression pattern to that of the enzymes in the cannabinoid biosynthetic pathway [15]. We used a Pearson's correlation matrix test to evaluate the relationship (positive and negative) between expression of MIXTA and other genes involved in cannabinoid synthesis with expression of cannabinoids across the full seven weeks of flower development (Figure 1C). This analysis shows that _CsMIXTA_ has a significant positive correlation with the expression of the two genes (_Geranyl Pyrophosphate Synthes_ (_GPPS_) and _Olivetolic Acid Cyclase_ (_OAC_)) required to generate the substrates (GPP and OA, respectively) necessary for the synthesis of the CBG, the first cannabinoid in the biosynthetic pathway. This analysis indicated that during flower development, _CsMIXTA_ expression was also positively correlated with cannabinoid levels and expression of _Cannabichromenic Acid Synthes_ (_CBCAS_) which generates the end product cannabinoid CBCa (Figure 1C). This analysis indicates that through coordinating trichome development, _CsMIXTA_ may play an important role in cannabinoid biosynthesis.  
_CsMIXTA_ belongs to the R2R3-MYB TF family and showed homology with the known R2R3-MYB and MIXTA-like TFs from other plant species. Using a yeast activation assay, we demonstrated that _CsMIXTA_ is capable of transcriptional activation (Figure 2A). Transient expression of _CsMIXTA_ in _N. benthamiana_ leaves showed nuclear localization (Figure 2B). In some cases, we also observed plasma membrane localization of _CsMIXTA_ (Figure S2).
# Freeform Wide Field-of-View Spaceborne Imaging Telescope: From Design to Demonstrator
## 3 Telescope Proof-of-Concept Demonstrator
### Manufacturing and Alignment Process
As a last step during the manufacturing process, the aperture stop and a flat fold mirror are added. The additional mirror enables the mounting of the Xenics Bobcat 320 GigE 100 Hz camera, and is mounted on a movable structure, ensuring coverage of the full FOV.
# Interference Alignment in Multi-Hop Cognitive Radio Networks under Interference Leakage
## 2 Signal and System Model
### End-to-End SNRs in the Presence of Interference Leakage  
In the presence of interference leakage, in other words, when the interference is not perfectly aligned, i.e., \(\alpha\
eq 0\), leakages occur, and the instantaneous SNRs can be expressed as:  
\[\Gamma_{S\to R_{1}}=\frac{\mathcal{P}_{S}\frac{||\mathbf{H}_{S \to R_{1}}||^{2}}{\sigma_{N}^{2}}}{1+\frac{a\sum_{j=1}^{\sum_{j}=1}^{\sum_{j} }P||\mathbf{H}_{j\to R_{1}}||^{2}}{\sigma_{N}^{2}}},\] \[\Gamma_{R_{i}\to R_{i+1}}=\frac{\mathcal{P}_{R_{i}}\frac{|| \mathbf{H}_{R_{i}\to R_{i+1}}||^{2}}{\sigma_{N}^{2}}}{1+\frac{a\sum_{j=1}^{ \sum_{j}}P||\mathbf{H}_{j\to R_{i+1}}||^{2}}{\sigma_{N}^{2}}}\text{ and}\] \[\Gamma_{R_{K-1}\to D}=\frac{\mathcal{P}_{R_{K-1}}\frac{|| \mathbf{H}_{R_{K-1}\to D}||^{2}}{\sigma_{N}^{2}}}{1+\frac{a\sum_{j=1}^{\sum_{ j}}P||\mathbf{H}_{j\to D}||^{2}}{\sigma_{N}^{2}}}, \tag{8}\]  
where \(||\cdot||\) denotes the Frobenius norm.
# A Review of Ku-Band GaN HEMT Power Amplifiers Development
## 3 Conclusions  
This article reviews the current state of Ku-band GaN HEMT high-power amplifiers for satellite communications, which are actively being developed and researched. Recent MMIC designs focus on GaN HEMT processes with gate lengths less than 0.2 \(\upmu\)m on SiC substrates, achieving PAEs exceeding 30% and output powers nearing 100 W. Utilizing advanced heat dissipation packaging from MIC design, Ku-band GaN HEMT amplifiers are anticipated to expand into both GaN-on-SiC and cost-effective GaN-on-Si MMICs. Future developments will focus on enhancing linearity, backoff efficiency, and bandwidth to support applications in military and civilian satellite and UAV communications. Additionally, advancements in power efficiency, thermal management, and miniaturization will enable broader adoption across mobile and satellite platforms, with new markets like 5G/6G expected to drive commercial and defense applications. These trends underscore the ongoing importance of research in Ku-band GaN HEMT HPA technology.  
Figure 10: Comparison of output power and PAE of GaN HEMT MMICs according to thermal interface material and heat spreader combinations.  
**Funding:** The EDA tool was supported by the IC Design Education Center (IDEC), Korea.  
**Acknowledgments:** I would like to express my gratitude to Electronic Device Solution Inc. for the industry-university connection with this research. I would like to express my sincere gratitude to [PERSON] and [PERSON] of Hanyang University for their invaluable assistance with my research and experiments. I also would like to express my sincere gratitude to [PERSON], Wireless Protocol Engineer at Amarisoft and the author of the Sharetechnote website, for his permission to cite useful illustrations about satellite communication. I would also like to thank the authors of the many references cited in this paper for their figures, data, and expertise.  
**Conflicts of Interest:** The author declares no conflicts of interest.