esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparative Transcriptomics for Pepper (_Capsicum annuum_ L.) under Cold Stress and after Rewarming
## 4 Discussion
### Response of Defence Mechanism to Cold and Rewarming Conditions  
Maintaining genome integrity is essential for an organism to reach its full life span. In order to maintain genome integrity and prevent DNA lesion transmission to daughter cells, DNA damage is recognized by a variety of sensors, including MutS, the RPA complex and the MRE11-RAD50-NBS1 complex [62]. These sensors activate DDR mechanisms, specifically evolved by plants, including direct repair, nucleotide excision repair, base excision repair, nonhomologous end joining, MMR, and HR [63]. This study focused on MMR- and HR-related genes; most DEGs in MMR and HR were significantly upregulated in T2 and T3 groups of CT compared with CS, suggesting that cold tolerance cultivars may have a strong DNA damage repair ability when suffering cold stress, while cold sensitive cultivars have a weak DNA repair ability. Mismatch repair corrects mismatches caused by misincorporation of nucleotides during DNA replication and recombination. After identifying the lesion, MutS recruits MutL [64], and PCNA loaded by replication factor C interacts with MutLa to enable PMS1 to exert its endonuclease activity. The endonuclease activity of MutLa generates new entry sites for the 5'-3' Exol, which removes the nicked strand [65; 66]. Finally, POL 8 and DNA ligase I complete the repair process [67]; HR is an important repair mechanism used to eliminate DNA double-strand breaks. The MRE11-RAD50-NBS1 complex recognizes DNA damage. Following resection by MRE11, the resulting single stranded DNA is bound by RPA and then replaced by RAD51 [68].  
The formed RAD51 nucleoprotein filament facilitates DNA strand invasion and exchange, resulting in the formation of a D-loop [69]. Then, DNA synthesis is conducted by three mechanisms, including non-crossover double-strand break repair, synthesis-dependent strand annealing, and break-induced replication. The DRR mechanism of plants was significantly enriched in this study and showed great differences between the two cultivars, but few studies have been conducted on it at cold stress, so the specific mechanism of action in DDR remains to be further studied.
## 4 Simulation and Water Tank Experiment Results
### Results of Water Tank Experiment
#### 4.2.1 Parameter Settings for Training Data Production  
In order to use the trained network in our water tank experiment system, we produced a large amount of training data through the method in Chapter 3, and then used these training data to continuously train CPD-Net and CPR-Net. It is especially important that the parameters in the process of making training data are completely consistent with the parameters of the actual water tank experimental system. In order to count the background light and dark count noise in the experimental system, this section makes a statistical analysis of the noise photon pulse output by the SPAD when the LED at the sending end is off. Figure 12 gives the statistical distribution of the number of noise photons within 1000 time slots, where the time slot frequency is 1 Hz. It can be seen from the figure that  
Figure 11: Diagram of the water tank experimental system.  
Figure 10: The influence of different time slot synchronous clock recovery methods on system communication BER.  
the average number of noise photons in the experimental system in 1 s is only four. When the communication baud rate is 1 Mbps, the number of noise photons within each bit is basically negligible, so the background light noise and dark count noise are not considered when making the training data set in this section. The detailed parameters of the water tank experimental system are given in Table 3.
## 5 Conclusions  
This study designed, fabricated, and verified the performance of a multi-functional transmitarray using only a PIN diode having ON/OFF switching characteristics. The transmitarray was designed based on a minimized level of quantization while reducing the design complexity and cost to be used as a low SWaP-C radar for UAV or air or ground surveillance system. The proposed configuration offers beam steering (1-bit phase resolution) and switchable linear-to-linear polarization characteristics through four PIN diodes in a unit cell. The calculation results confirmed the ability of the 8 \(\times\) 8 transmitarray to 2D beam scan on a 90\({}^{\circ}\)\(\times\) 90\({}^{\circ}\) area, polarization converting loss of below 1.28 dB, and polarization isolation of over 10 dB. The far-field pattern was measured through near-field antenna measurement system to verify the fabricated transmitarray and maximum gain of 14.6 dBi (Bore-sight), and an aperture efficiency of 16.4% were observed through the measured data showing an improvement in performance compared to previous studies despite demonstrating multi-functionality.  
Conceptualization, I.-G.L. and I.-P.H.; methodology, I.-G.L. and I.-P.H.; investigation, I.-G.L.; validation, I.-G.L. and J.-Y.K.; writing--original draft preparation, I.-G.L.; writing--review and editing, I.-P.H.; supervision, J.-Y.K. and I.-P.H.; project administration, I.-P.H. All authors have read and agreed to the published version of the manuscript.  
This research has been supported by a grant-in-aid of HANWHA SYSTEMS based on the Challenging Future Defense Technology Research and Development Program (9127786) of Agency for Defense Development in 2019.  
Not applicable.  
The authors declare no conflict of interest.
## 3 The Proposed Scheme
### Intra-Distribution Measure (IDM)  
The intra-distribution of a word is important in reflecting its dependency on a category. Inverse Document Frequency (IDF) is commonly adopted, which measures how much information a word  
Figure 2: An example of _DisVector_.  
offers in representing the category. It measures the degree of occurrence of a word across all the documents, and is expressed as:  
\[idf(w,D)=\log\frac{N}{|\{d\in D:w\in d\}|} \tag{15}\]  
Here, \(N\) is the number of documents in the training dataset, and \(|\{d\in D:w\in d\}|\) denotes the number of documents containing word_w. IDF has been incorporated into various schemes including TF-IDF to decrease the weight of frequently appearing words and increase the weight of rare words. This is a coarse-grained approach because it supposes that rare words are more important than common ones. In this paper a fine-grained Intra-Distribution Measure called IDM is introduced to analyze the words, which incorporates the dependency derived from Chi-square statistics and the occurrence of words in the document. It is expressed as:  
\[IDM(w_{i},c_{j})=\chi^{2}(w_{i},c_{j})\cdot\log\frac{|\{d\in D:w_{i}\in d\}|}{N} \tag{16}\]  
Here, \(\chi^{2}(w_{i}c_{j})\) is the Chi-square value measuring the dependency of word_w\({}_{i}\) on category_c\({}_{j}\). It is denoted as:  
\[\chi^{2}(w_{i},c_{j})=\frac{(A+B+C+D)*(AD-BC)^{2}}{(A+B)(A+C)(B+D)(C+D)} \tag{17}\]  
Table 2 lists the cases of the sums of the frequencies of the words. Here, \(A=\sum_{i=1}^{m}cf_{i}\), \(B=\sum_{i=1}^{n}cf_{i}\). \(C=M-\sum_{i=1}^{m}cf_{i}\), and \(D=N-\sum_{i=1}^{n}cf_{i}\). \(m\) is the number of documents word_w\({}_{i}\) appears in category_c\({}_{j}\), and \(n\) is the number of categories except class_c\({}_{j}\). \(M\) denotes the sum of \(cf\) value of all the words in category_c\({}_{j}\), and \(N\) is computed by summing the value of \(cf\) of words of categories except class_c\({}_{j}\). Note that, unlike the conventional Chi-square method, \(cf_{i}=\sum_{i=1}^{|d_{i}|}tf_{i}\) is employed as the input of the Chi-square calculation to avoid the weakness of incorrectly overestimating the role of low-frequency words. The proposed IDM is based on the intuition that the words of high document frequency are relatively more important. By incorporating the dependency of the words on the category, more accurate measurement of the intra-distribution significance of the words is obtained.
## 4 Results
### Gravity Data Analysis  
In a geothermal context, the optimal temperature for electricity generation is between 120-170 \({}^{\circ}\)C where the rock permeability is low [45]. In this case, it is important to characterize tectonic features such as faults and fractures that could act as permeable zones.  
In this study, the subsurface density distribution beneath the Midyan region was predicted based on gravity data modelling. As no deep wells were drilled in the study area, the density models of the granite rocks were matched as much as possible with the available analyses of several exposed granite rocks in addition to the information provided from nearby drilled wells penetrating similar granitic rocks in the Arabian shield [46].  
The resistivity curves and gravity modelling were overlapped for a clear interpretation. The inversion results of the AMT and gravity data were evaluated in terms of relatively low resistivity/density zones, which might have indicated a thermal variation. Accordingly, 15 profiles (Figure 2) were selected for inversion process (AMT and gravity).
###### Abstract  
It has recently been shown that the temporal and the orbital angular momentum (OAM) degrees of freedom in ultrafast (few-cycle) vortices are coupled. This coupling manifests itself with different effects in different parts of the vortex, as has been shown for the ring surrounding the vortex where the pulse energy is maximum, and also in the immediate vicinity of the vortex center. However, in many applications, the ring of maximum energy is not of primary interest, but the one where the peak intensity of the pulse is maximum, which is particularly true in nonlinear optics applications such as experiments with ultrafast vortices that excite high harmonics and attosecond pulses that also carry OAM. In this paper, the effects of the OAM-temporal coupling on the ring of maximum pulse peak intensity, which do not always coincide with the ring of maximum pulse energy, are described. We find that there is an upper limit to the magnitude of the topological charge that an ultrafast vortex with a prescribed pulse shape in its most intense ring can carry, and vice versa, a lower limit to the pulse duration in the most intense ring for a given magnitude of the topological charge. These limits imply that, with a given laser source spectrum, the duration of the synthesized ultrafast vortex increases with the magnitude of the topological charge. Explicit analytical expressions are given for the ultrafast vortices that contain these OAM-temporal couplings effects, which may be of interest in various applications, in particular in the study of their propagation and interaction with matter.  
ultrafast vortices; orbital angular momentum; pulses Article
## 3 Modes as Data Signatures  
As implied above, both _visible_ and _hidden_ modes play important roles in understanding dynamical signatures in data and thus the structure of systems from which they emanate. Using a possibly familiar analogy with large-scale data analysis in bioinformatics or computational statistics, finding the modes in dynamic system data is akin to finding the _principal components_ (principal component analysis--PCA) or _singular values_ (singular-value decomposition--SVD), of a large data matrix. This means visualizing a multivariate dataset--typically expressed in a high-dimensional data space, from its \"most informative\" viewpoint--its principal components--in a lower-dimensional space. Distinct _modes of chords and scales_ in music are another albeit less mathematical example, with each mode sounding different but having a different arrangement of the same notes played in particular orders.  
This is important because we can use these notions for developing dynamic system model _structure_ and establishing the _dimensionality of the model observable in data_, in terms of _modes_ associated with \(n\) exponential solutions in the data. In brief, _visible modes_, in particular I-O data, collected from a system are visibly associated or identified with visible state variables in its model. _Hidden modes_ in the data are associated with hidden state variables (hidden modes (state variables, compartments) are directly analogous to hidden states in a Markov model (_hidden Markov model_)), i.e., those that have no signature in the particular I-O data. They may be in the system, but they are not visible in that dataset.  
Different experiments (input-output port configurations) are needed to discover them in new data.  
To tie these relationships to the model _structure_, in particular multicompartmental structural models, we need some definitions.
# Automatic Feature Construction-Based Genetic Programming for Degraded Image Classification
## 3 The Proposed Approach
### Accompanying Evolution
#### 3.3.1 Storage Strategy  
In the storage strategy of the algorithm, two storage methods for accompanying individuals are introduced, aiming to store potential individuals at different evolutionary stages. The first method primarily focuses on high-fitness individuals that are eliminated during the evolutionary process, while the second method targets individuals that have been updated and enhanced their fitness within the new population.  
The first storage method focuses on preserving individuals that, although eliminated during the evolutionary process, exhibit high fitness. This approach avoids introducing lower-quality individuals that might degrade the overall population quality, without adding extra computational resource consumption. At the end of the selection process for each generation, the eliminated individuals are ranked based on their health conditions. They are then stored as accompanying individuals according to the ratio \(\alpha\) and subsequently incorporated into \(A_{1}\). This ratio \(\alpha\) is defined in Equation (2),  
\[\alpha=\begin{cases}0.15&\text{if }1\leq g\leq 10\\ 0.10&\text{if }11\leq g\leq 30\\ 0.05&\text{otherwise}\end{cases} \tag{2}\]  
where \(\alpha\) takes on different values depending on \(g\), which represents the evolutionary generation. In the initial stages of the algorithm, the population diversity is typically high. As evolution progresses, the population might begin to converge, potentially leading to a decrease in diversity. To adapt to this transition, the algorithm reduces the number of accompanying individuals it retains.  
The second type of storage method: The second storage method focuses on preserving individuals that have successfully updated. Specifically, the first type of accompanying individuals successfully replace some redundant individuals in the population, generating a new population through crossover and mutation. Within this new population, if any individual successfully updates (improves its fitness), this indicates that these new individuals have potential for development. Individuals that have updated successfully are stored in \(A2\) as the second type of accompanying individuals.
## 5 Experimental Results
### Tests in Ideal Static Scenarios  
As aforementioned, in the second phase of our experimental campaign, we perform a number of field tests in ideal scenarios, where the nodes are static and positioned in an environment not affected by phenomena like shadowing and fading. In the considered experimental conditions, the wireless medium access problem cannot be extensively analyzed, and the IF protocol does not perform at its best. The number of retransmission choices is, in a probabilistic sense, very small. Although a larger number of nodes should be considered (e.g., at least 15-20 devices) in order to have higher node spatial density, the obtained results shed light on the performance of the proposed information dissemination system.
# Optimization of Submodularity and BBO-Based Routing Protocol for Wireless Sensor Deployment
###### Abstract  
Wireless sensors are limited by node costs, communication efficiency, and energy consumption when wireless sensors are deployed on a large scale. The use of submodular optimization can reduce the deployment cost. This paper proposes a sensor deployment method based on the Improved Heuristic Ant Colony Algorithm-Chaos Optimization of Padded Sensor Placements at Informative and cost-Effective Locations (IHACA-COpSPIEL) algorithm and a routing protocol based on an improved Biogeography-Based Optimization (BBO) algorithm. First, a mathematical model with submodularity is established. Second, the IHACA is combined with pSPIEL-based on chaos optimization to determine the shortest path. Finally, the selected sensors are used in the biogeography of the improved BBO routing protocols to transmit data. The experimental results show that the IHACA-COpSPIEL algorithm can go beyond the local optimal solutions, and the communication cost of IHACA-COpSPIEL is 38.42%, 24.19% and 8.31%, respectively, lower than that of the greedy algorithm, the pSPIEL algorithm and the IHACA algorithm. It uses fewer sensors and has a longer life cycle. Compared with the LEACH protocol, the routing protocol based on the improved BBO extends the life cycle by 30.74% and has lower energy consumption.  
wireless sensor deployment; submodularity; ant colony algorithm; routing protocol; biogeography-based optimization 2020
## 3 Results
### Analysis of Variance
#### 3.2.3 Six Locking Screws  
The maximum principal stress of six locking screws results from running the FEA model at various testing conditions as shown in Table 11. All main factors were identified in importance by an ANOVA, as shown in Table 12. Furthermore, R-squared and adjusted R-squared statistics were analyzed for checking the fit of the dataset. Moreover, if the p-value of each main effect and its interaction was less than 0.05, it was considered statistically significant. According to this analysis, gap type (A), fracture gap (B), nail length (C), the interaction between variables A and B, the interaction between variables A and C, the interaction between variables B and C, and the three-way interaction A*B*C are factors that affect the maximum principal stress of the composite interlocking nail. \begin{table}
\begin{tabular}{c c c c c} \hline
**Condition** & **A** & **B** & **C** & **Principal Stress** \\ \hline
1 & Proximal & 1 & 120 & 47.23 \\ \hline
2 & Distal & 1 & 120 & 80.50 \\ \hline
3 & Proximal & 3 & 120 & 59.18 \\ \hline
4 & Distal & 3 & 120 & 148.48 \\ \hline
5 & Proximal & 1 & 160 & 36.58 \\ \hline
6 & Distal & 1 & 160 & 75.83 \\ \hline
7 & Proximal & 3 & 160 & 50.24 \\ \hline
8 & Distal & 3 & 160 & 91.14 \\ \hline
9 & Proximal & 1 & 120 & 47.23 \\ \hline \end{tabular}
\end{table} 
Table 11: FEA model of the six locking screws’ results for the testing conditions. Figure 10: Pareto chart of the effects of principal stress (four locking screws). The R\({}^{2}\) value shows that the model explains 96.58% of the variance in the maximum principal stress, which indicates that the model fits the data extremely well. The residual plot of the maximum principal stress is shown in Figure 11, representing the normal probability plot of the residuals. The residuals of the response randomly scatter around zero in the residual plots. Regarding the residuals versus the fits, the observation points (blue dots) scattered randomly in the normal probability plot show that the process parameters in this study were normal and independently distributed. The histogram of the residuals is approximately symmetric. Regarding the residuals versus the order, the residuals exhibit no clear pattern. The magnitude and significance of an effect were determined by the Pareto chart shown in Figure 12. The Pareto chart shows the absolute values from the largest to the smallest effect of the standardized effects. The standardized effects are t-statistics that test the null hypothesis that the effect is zero [31]. In this Pareto chart, the bars that represent factors A, B, C, AB, ABC, BC, and AC cross the reference line, which is at 2.20. These factors are statistically significant at the 0.05 level with the current model terms. In the selected range, the infection order of each factor is A \(>\) B \(>\) C \(>\) AB \(>\) ABC \(>\) BC \(>\) AC.
# Planning Urban Internal Transport Based on Cell Phone Data
## 4 Results
### Traffic Accessibility Analysis  
The accessibility of the urban traffic road network reflects the service scope of urban road networks and the convenience of urban residents' travel, the degree of interaction between regions within the city, and to a certain extent, it can analyze the defects of urban road networks [30], so this paper studies the accessibility of traffic road networks in Wuxue City based on travel time and travel distance [31].  
We obtain the accessibility distribution of the main crowd activity nodes in the city based on the analysis of cell phone data by constructing the OD matrix model (Figure 10). The crowd is mainly concentrated in the south of Wuxue City, and the accessibility of the main distribution points of crowd activity gradually decreases from south to north, and the accessibility is better in the areas with greater travel demand, but the traffic demand of Meichuan Town and Huaqiao Town, which are located in the east and north of Wuxue City is also greater from the above linkage analysis, their accessibility is poor, and the road network needs further improvement. The accessibility of the central part of the city, where highways and provincial roads are located, is high, while the eastern part of the town of Yuchuan and Huaqiao has fewer roads and poorer accessibility. The planning of the road network in the eastern and northern areas of Wuxue City needs to be further improved.  
Traffic intersections are generated by the intersection of more than two roads, which can lead to multiple directions. The average distance value of cell phone data points arriving at the nearest intersection is calculated to be 535.77 m; the standard deviation is 655.04 m. Furthermore, 67.64% of the distance is less than 500 m. The natural interruption point classification is used to obtain the road accessibility analysis map (Figure 11).  
Figure 9: Analysis of road network density and travel OD passenger volume distribution. (**a**) Road network density (**b**) Administrative district level. (**c**) Township district level.