esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Analysis of Factors Influencing the Digital Service Trade Network of RCEP Member Countries
### QAP Regression Analysis
#### 5.1.2 Variable Selection Instructions
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variable Options** & **Index** & **Indicator Description** & **Expected Symbol** & **Data Sources** \\ \hline \multirow{2}{*}{dependent variable} & DSTcj & The digital service trade value between country c & & OECD database \\  & & and country j & & \\ \hline \multirow{6}{*}{Independent variables} & GDPcj & Absolute value of per capita GDP difference & & World Bank \\  & & between countries c and j & & database \\ \cline{2-5}  & & Absolute value of the difference in digital & & \\  & & infrastructure levels between country c & - & World Bank \\  & & and country j & & database \\ \cline{2-5}  & & & Institutional distance between country c & & World Bank \\  & & and country j & & database \\ \cline{2-5}  & & & & CEPII \\ \cline{2-5}  & & & & database \\ \hline \multirow{2}{*}{DIS} & \multirow{2}{*}{Weighted geographical distance between country c} & \multirow{2}{*}{-} & CEPII \\  & & and country j & & database \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Explanation of Indicator System and Data Sources. the governance index value of country j in the t-th year. Due to the negative value of the governance index value, in order to make the institutional distance non-negative, this study adopts absolute value processing for the institutional distance. Common language (LAN\({}_{\text{G}}\)): Language is often closely linked to culture, and common language helps to better understand cultural differences. If there are language barriers between two countries, it may lead to cultural misunderstandings and affect cooperative relationships. Cultural similarities are beneficial for reducing trade costs and promoting trade cooperation. Therefore, in this study, we represent whether there is common language between the two countries using a matrix. If there is common language between the two countries, it is denoted as 1; otherwise, it is denoted as 0. The data are sourced from the CEPII database. Geographical distance (DIS\({}_{\text{G}}\)): When conducting traditional trade, geographical distance usually reflects the transportation costs during the trade process. Although digital service trade has strong cross-border delivery capabilities and, to some extent, surpasses the constraints of geographical distance, geographical distance may lead to data being affected by different laws and regulations during cross-border transmission, requiring compliance with different regulations and standards and increasing the complexity of management and compliance. Therefore, geographical distance is still a factor to consider, and the farther the weighted geographical distance between two countries, the less likely it is to engage in bilateral digital service trade. This study represents the weighted geographical distance between the two countries using a matrix with data sourced from the CEPII database.
# A Novel Method for Constructing the S-Box Based on Spatiotemporal Chaotic Dynamics
## 4 Randomness Tests of the Constructed S-Box  
The obtained S-box is listed in Table 1. NIST-800-22 [32] statistical tests were used to test the randomness of the constructed S-box. NIST-800-22 statistical tests consist of 15 different tests. These tests focus on a variety of different types of non-randomness that could exist in a sequence. In the NIST-800-22 statistical tests, the results were evaluated according to the defined \(p\)-value. If the predefined \(p\)-value is 0.001, the resultant \(p\)-values must be greater than or equal to the predefined value 0.001 to pass the test successfully.  
Figure 4: The flowchart of the construction process of the obtained S-box.  
Tested files should contain binary sequences stored as either ASCII characters consisting of zeroes and ones or as binary data where each byte contains eight bits worth of zeroes and ones. We transform all the values of the constructed S-box into a binary sequence, which consists of 2048 bits stored in ASCII format. The tests are performed by using the NIST sts-2.1.2 on Red Hat Enterprise Linux 5. Without loss of generality, the parameters \(\mu=3.87\), \(\alpha=0.2\), \(b=12\), and \(d=7\) for the tests.  
The NIST-800-22 test results are listed in Table 2. We find that the 12 tests successfully passed. Moreover, the random excursions test, random excursions variant test, and universal statistical test were not applicable for the proposed S-box. This is because the sequence generated by an S-box only consists of 2048 bits. However, the random excursions test and random excursions variant test require a long sequence consisting of a minimum of 1,000,000 bits [32], and the universal statistical test also requires a long sequence consisting of a minimum of 387,840 bits [32].
# Small Target Radiometric Performance of Drone-Based Hyperspectral Imaging Systems
## 3 Methodology
### Field Irradiance Measurements  
The spectral radiance from a point target is dependent on two field measurements: the total downwelling irradiance (Figure 3(a)) and the sky irradiance (Figure 3(b)). The sky irradiance measurement will be used to estimate the Global-to-Diffuse Ratio as previously mentioned. Both field measurements contained a 2% uncertainty on the radiometric calibration and additional contributions from variations in illumination over the duration of the experiment. The illumination variation was estimated by assessing the deviation of both measurements during the 8 min experiment. This was a small contribution to the field measurement uncertainty compared to the assumed 2% calibration uncertainty. As can be seen in Figure 4, the black curves demonstrate a low percent variation in total downwelling irradiance and atmospheric conditions during the experiment. Any changes in atmospheric conditions, such as clouds or particulate scattering, would be captured in both measurements.  
As mentioned in Section 2.2, the sky irradiance was measured by shading the ASD cosine corrector from the solar disk. The shadowing device was a square piece of wood covered in black felt (similar to the mirror background material).  
Estimating the point targets entrance aperture-reaching spectral radiance is defined in Equation (3). The total downwelling irradiance can be used directly, whereas Equation (2) defines the Global-to-Diffuse Ratio. Figure 5 contains the two field measurements used to estimate the predicted point target spectral radiance (i.e., Equation (3)). Depending on the amount of diffuse sky reflected into the sensor's FOV, the point targets will have a similar spectral shape to the total downwelling irradiance. The convex mirrors merely act as an attenuator of the reflected energy as a function of the mirror coating and mirror geometry. Since all mirrors are in close proximity, all point target signal estimates use the same total downwelling irradiance and Global-to-Diffuse Ratio. The only difference is in the modification of the Global-to-Diffuse Ratio based on the unique mirror geometries (i.e., \(\theta_{m}\)).
## 3 Classification and Synthesis of Bimetallic Nanoparticles
### Successive Methods  
The seed-mediated growth process begins by synthesizing a seed nanoparticle followed by subsequent growth, in solution, from metal precursors and reducing agents [131]. The seed-mediated method is typically used for the synthesis of well-defined bimetallic nanoparticles of core-shell and intermetallic structures due to the ability to control their size, shape, and composition [132]. In this type of synthetic process, reducing agents play an important role in controlling the size distribution of the nanoparticles. For example, strong reducing agents can create new nuclei in solution, which can lead to the formation of metal nanoparticles having two different sizes [133; 134].  
The most common combinations of metals used for the fabrication of bimetallic particles are gold and silver, palladium, or platinum due to their desired properties for a plethora of applications [135]. [PERSON] et al. used the seeded-growth method to prepare layered core-shell bimetallic Ag-Au nanocages in the 10-16 nm size range that were suitable for use in surface enhanced Raman spectroscopy (SERS) applications [73]. [PERSON] et al. synthesized Au@Ag core-shell nanoparticles having controllable shapes from spherical gold seeds. Various shapes synthesized on the gram scale include: cubes, cuboctahedrals, and octahedrons such as those shown in Figure 9 [74].  
Figure 9: Schematic illustration of (**a**) Au@Ag core–shell nanopolyhedrons synthesized by the seed-mediated method and SEM images of (**b**) gold nanoseeds, (**c**) Au@Ag nanospheres, (**d**) Au@Ag cuboctahedrons, and (**e**) Au@Ag nanocubes. Reproduced with permission from ref. [74]. Copyright 2011 American Chemical Society.  
Bimetallic AuPd and AuPt nanoparticles have also been extensively studied in terms of their preparation, stabilization, and catalytic activity [50; 85; 136; 137]. [PERSON] et al. developed an Au-seeding method by which bimetallic core-shell nanoparticles can be readily synthesized with controllable sizes [88]. Following the method developed by [PERSON], core-shell Au@Pd nanoparticles with tunable sizes were prepared for use in practical SERS-based applications due to their high SERS activity, stability, and reversibility. In addition to synthesizing core-shell structures, a novel route for the synthesis of subclustered PtAu nanoparticles with controllable morphologies was developed by the overgrowth of Au onto Pt [94]. The size and shape of the nanoparticles were controlled by tuning the size of the Pt seeds or the solvent polarity to afford particles having clover-like, peanut-like, and pear-like shapes. Furthermore, certain morphologies proved to influence their catalytic performance, making this method a potential candidate for the rational synthesis of advanced materials for several types of catalytic applications.
# Cognitive Frequency-Hopping Waveform Design for Dual-Function MIMO Radar-Communications System
## 2 System Configuration and Signal Model
### Phase Modulation (PM)-Based Frequency Hopping (FH) Waveforms
\(\mathbf{H}(\mathbf{\hat{\jmath}})=\left[h_{m,n}^{i}\right]_{M\times N}\) indicates the target response matrix during the \(i\)-th radar scan. \(h_{m,n}\) stands for the channel coefficient between the \(m\)-th transmit element and the \(n\)-th receive element. \(\mathbf{x}(t,\mathbf{\hat{\jmath}})=\left[x_{1}(t,\mathbf{\hat{\jmath}}), \ldots,x_{M}(t,\mathbf{\hat{\jmath}})\right]^{T}\) represents the \(M\times 1\) vector of PM-based waveforms during the \(i\)-th radar scan. \(x_{m}(t,\mathbf{\hat{\jmath}})\) is the waveform transmitted from the \(m\)-th transmit element, and \(\mathbf{n}(t,\mathbf{\hat{\jmath}})\) is an \(N\times 1\) vector of zero-mean white Gaussian noise. Figure 1: Illustrative diagram of a dual-function multiple-input multiple-output (MIMO) transmit platform. The target-scattering signal components associated with the individual PM-based FH waveforms are achieved by using a matched filter bank. As a result, the target scattering signals observed at the output of the MIMO radar receiver (5) are matched-filtered to the proposed PM-based sequences (3), yielding the \(M\)N\(\times\)1 vector of the virtual signal. The extended vector can be expressed as:  
\[ \begin{array}{ll}\textbf{r(i)}&=vec(\int_{T_{0}}\textbf{y(}t,i\textbf{)x^{H} (t)dt})\\ &=vec(\textbf{H}^{T})+\textbf{\hat{n}(i)}\end{array}  \tag{6}\]  
In (6), \(vec(\cdot\ )\) describes the vectorization operator that stacks the columns of a matrix into one long column vector, and \(\textbf{\hat{n}(i)}\) denotes the \(M\)N\(\times\)1 zero-mean white Gaussian noise with covariance \(\delta_{z}^{2}\textbf{I}_{M\text{N}}\).
## 3 Results and Discussion
### Rheology of the Edible Coating Solution
#### 3.3.1 Steady Rheological Properties  
Figure 3a shows the flow curve of different samples: the changes observed in shear stress are a consequence of the addition of licorice root extract to chitosan control, due to the interaction between chitosan and licorice phytochemicals and complexation. All coating solutions exhibited the behavior of non-Newtonian fluid and can be adjusted to the Power Law model (Equation (1)). The model parameters (_K_ and _n_) are given in Table 4, and high fitting degree (R\({}^{2}\) > 0.994) was achieved. The \(K\) (consistency coefficient) values decrease significantly and \(n\) (flux index) values increase with the addition of LE. Chitosan solution presents a consistency coefficient of 0.469 \(\pm\) 0.015 and flux index of 0.795 \(\pm\) 0.005. Moreover, the samples Ch + LE-1 and Ch + LE-5 present \(K\) values of 3.72: 10\({}^{-4}\)\(\pm\) 0.001 and 1.76\(\cdot\)10\({}^{-4}\)\(\pm\) 0.001 and \(n\) values of 1.436 \(\pm\) 0.018 and 1.503 \(\pm\) 0.012, respectively. \(n\) values equal to 1 indicate the Newtonian fluids, lower than 1 indicate shear thinning fluids, while \(n\) values higher than 1 indicate a shear thickening behavior [54]. Then, the chitosan coating solution presents a shear thinning behavior due to alignment of molecules in the direction of flow, and a decrease of viscosity with the increase of shear rate. Similar results were obtain by [PERSON] [55] in a coating solution of chitosan/zein with the addition of alpha-tocopherol.  
Figure 3: Rheological properties of edible coating solutions produced with chitosan and chitosan-licorice: (**a**) flow curve, (**b**) frequency sweep and (**c**) temperature sweep.  
On the other hand, the addition of LE caused a decrease in the shear stresses and a non-Newtonian behavior. The shear thickening behavior (n \(>\) 1) observed in samples Ch + LE-1 and Ch + LE-5 are probably a consequence of particle hydro-clustering and an order-to-disorder transition. At large shear rates and stresses, convective and hydrodynamic force dominate over inter-particle force, and cause hydro-clustering of particles [56; 57]. The rheological properties of coating solutions are consistently used among the literature to provide data on films' microstructure, thickness, coating spreadability and uniformity on substrate. In general, highly viscous solutions retained air bubbles in the casting process, and low viscous solutions facilitated its spreading on the plate where the films were formed [58].
## 2 Literature Review
### Budget Constraints  
The novelty of our study is that it incorporates the friend's budget constraints into RRPs. Prior studies have focused on the friend's valuations [2; 13; 14] while disregarding budget constraints.  
In micro-economics, the budget is defined as the payment capability of a consumer. However, budgets are influenced by several factors such as time and income. The most significant application of budget in micro-economics is the theory of consumers, which posits that consumers purchase certain groups of products according to maximum utility within their budget. The budget constraint can be expressed as \(p_{1}x_{1}+\ p_{2}x_{2}+\cdots+p_{N}x_{N}\leq m\), where \(m\) is the budget affected by factors such as time and income; \(p_{N}\) denotes the price of product \(N\); and \(x_{N}\) represents the number of product \(N\). Therefore, the budget is a constant value in the theory of consumers. Consumers usually adopt value priority hypotheses in budget planning, especially when purchasing goods such as durables [15]. In value priority hypotheses, the budget is considered to be a constant value and the budget constraint is expressed as\(p_{1}g_{1}+\ p_{2}g_{2}+\cdots+p_{N}g_{N}+\gamma\leq B\), where \(B\) is a consumer's budget, \(p_{N}\) denotes the price of product \(N\), \(g_{N}=1\) or \(0\) represents whether or not the consumer purchases product \(N\), and \(\gamma\) is the summary of the consumer's allocation for other goods.  
There is another definition of budget different from ours. Budget is defined as the maximum a consumer plans to pay for a product, thus possibly varying with the consumer's valuation of the product [16]. In contrast, our study defines budget as the consumer's payment capacity, which is affected by time and income and is independent of the product valuation--the same definition as is used in the theory of consumers and value priority hypotheses [15]. There are several situations where a customer has budget constraints, especially when customers purchase durable goods such as household appliances, cars or apartments. A customer holding 30,000 dollars cannot purchase a car priced 50,000 dollars. This is a situation where the budget limits a customer's purchase decision. The budget is the current cash state of a customer, and does not have any relationship with the product. Capacity constraint problems also occur in related research disciplines such as the budget constraint in auction literature [17] and the inventory or capital constraint in operation management.  
A customer's budget is affected by time and income, which are independent of the product valuation, follow a Bernoulli distribution (e.g., the probability of a high income is \(q\), whereas the probability of a low income is \(1-q\)) [1]. Therefore, our study assumes that budget constraints are independent from customer valuations, and characterizes them with a Bernoulli distribution.
# Occlusion Vehicle Target Recognition Method Based on Component Model
## 2 Occlusion Vehicle Target Segmentation and Recognition Scheme Design
### Design of Vehicle Component Feature Mask Module Based on Swin Transformer
#### 2.2.2 Component Perception Enhancement Unit  
To deal with the problem that the weak contrast of the vehicle component area in the acquired image affects the feature extraction, the component perception enhancement unit is introduced to enhance the vehicle component features, as shown in Figure 5:  
In Figure 5, the receptive field expansion is carried out by introducing dilated convolution to improve the response performance of the component perception enhancement unit to the weak contrast of vehicle components. Due to the particularity of the output feature data of the Swim Transformer unit, the data format needs to be adjusted first. Then, \(1\times 1\) convolution is used to reduce the dimension of the feature image to reduce the amount of parameter calculation. Then put the features into the dilated convolution with different magnifications. The magnifications are 1, 2, 4, and 8, and the size of the convolution kernel is \(3\times 3\). The features on different branches are fused to generate the enhanced features, and \(1\times 1\) convolution is used to increase the dimension to obtain the feature map. Finally, the feature map is activated by the Swish function as the output feature data.  
The introduction of dilated convolution in this module can make the net pay more attention to the component areas with weak vehicle contrast. The formula of dilated convolution is as follows:  
\[f_{o}(m,n)=\sum_{i=1}^{m}\sum_{j=1}^{n}f_{i}(m+r\cdot i,n+r\cdot j)\cdot \omega(i,j) \tag{9}\]  
In Equation (9), \(f_{o}(m,n)\) is the element of the output feature map, \(f_{i}(m+r\cdot i,n+r\cdot j)\) is the element of the input feature map, \(\omega(i,j)\) is the element of the convolution kernel, \(m\) and \(n\) are the height and width of the convolution kernel, and \(r\) is the expansion rate.
## 4 Discussion
From our analysis, all three C sequestration indicators exhibit significant negative correlations with the temperatures in late summer (August and September), a period typically marked by intense summer heat and frequent drought events [94]. Therefore, enhancing the drought resilience of PFs is crucial for sustaining and increasing C sequestration across the study region. This requires the careful selection of tree species and genotypes with traits adapted to hot, dry summers. For example, deep-rooted species can access moisture from deeper soil layers during drought, sustaining their transpiration and photosynthesis when shallow-rooted trees (like some poplars) experience water deficit. As observed, a small proportion (~2-5.1%) of deep fine roots can supply up to ~20-40% of the tree's water use during prolonged dry periods [95]. Thus, selecting or encouraging species with deeper rooting profiles may be one strategy to enhance drought adaptation. Meanwhile, genetic selection within species can be another useful strategy to enhance drought resistance for future PF developments. Studies on hybrid poplars (widely planted in Eastern China) have found significant variation in drought tolerance among clones. For instance, one hybrid clone (_Populus deltoides_\(\times\)_P. nigra_) maintained higher growth and photosynthetic rates under drought, suffering less damage than other clones [96]. Utilizing more drought-resistant clones or species can therefore improve plantation performance during Jiangsu's drought period. In addition to single-species choices, increasing tree diversity can be another adaptation strategy to maintain the sustainability of PFs. Diverse mixed-species forests tend to be more drought-resilient than monocultures because different root depths and water-use strategies allow for more efficient use of available moisture. A recent global study indicated that converting monoculture plantations to mixed stands (e.g., four species) could raise drought resistance by a few percent on average, with even larger benefits in drier regions [97]. This diversity effect arises from complementary water uptake and stress buffering among species. In practice, managers in Jiangsu can consider blending deep-rooted native hardwoods (such as certain oaks) with a fast-growing species to confer greater ecosystem stability under summer droughts. Overall, species selection and silvicultural practices that favor deep rooting and stand diversity will potentially help Jiangsu's PFs to better withstand summer drought and low soil moisture, securing their C sequestration capacity in a changing climate.
# Quality of Experience Experimentation Prediction Framework Through Programmable Network Management
## 3 Preliminaries and Methodology
### Adaptive Streaming  
A multimedia data file is segregated into multiple parts or segments and then conveyed to the user using HTTP. A media presentation description (MPD) explains the particulars of the segment, which include aspects such as time, website and multimedia properties such as video resolution and bit rates. These segments can be arranged in a number of ways such as segment-based, segment time line, segment template and segment list, depending on the use case. A segment can be a media file of any type or format, such as the \"ISO base media file format\" and MPEG-2 transport stream; there are the two major kinds of container format. DASH can be considered as a video/audio codec specific. Media files are usually provided as a multiple number of illustrations, and the concerned choice of data is mainly related to the network status, equipment potential and client preferences that are responsible for allowing the adaptive bit rate streaming and impartiality of the quality of the experience.  
The adaptive bit rate streaming logic is not defined by an MPEG DASH standard. Therefore, DASH can be implemented on any type of protocol. PCC expressively decreases the storage quantity at the cost of multifaceted pre-processing and execution at the client. \"HTTP adaptive streaming\" (HAS) deals with dynamic setup circumstances while endeavouring transport at maximum quality possible in the given circumstances.