esa-sceva/satcom-chunk-collection huggingface dataset:
# QoS-Guaranteed Radio Resource Management in LTE-A Co-Channel Networks with Dual Connectivity
## 4 Evaluation  
### Simulation Assumption  
In this work, we adopted the system level simulation [34] to validate our proposed schemes. Specifically, we used Vienna LTE-A Downlink System Level Simulator version v2.0 Q3-2018 as our simulator [35]. The LTE-A downlink macro-pico HetNet with seven cell sites wrapped around and three hexagonal sectors per cell site was considered here. In each cell, two pico BSs with fixed position were deployed at the cell edge with a distance of 8/15 ISD (Inter-site Distance) from the macro BS, as shown in Figure 7. In addition, mobile UEs that were nonuniform were distributed in the network. The total number of UEs was 315 in the simulated scenario with 15 UEs deployed in each sector of a Macro BS. Two traffic types were considered among 315 UEs, 158 UEs generating GBR traffic and 157 UEs generating MBR traffic. Each simulation was run for 10,000 TTIs and 30 runs of simulations were conducted. The 95% confidence interval of each simulation case was also calculated. System parameters of the simulation are summarized in Table 5.  
Figure 7: Layout of network topology.
# Frequency-Limited Model Reduction for Linear Positive Systems: A Successive Optimization Method
## 2 Problem Statement and Fundamental Results
Therefore, we summarize the overall problem formulation as follows:  
**Frequency-Limited Model Reduction:** Given a specific frequency range \(\Omega\), explore a reduced-order model \(\Sigma_{r}\) such that  
1. The system \(\Sigma_{\tau}\) is stable, and \( \begin{bmatrix}A_{r}&B_{r}\\ C_{r}&D_{r}\end{bmatrix} \in\mathbb{P}\). 2. The approximation error system \(\Sigma_{e}\) satisfies the finite-frequency criterion in (6). Next, we introduce the generalized KYP lemma, which is essential to the analysis of finite-frequency specifications. **Lemma 3** ([22]). : _Given the state-space Equation (3) and a specific frequency range \(\Omega\), the system \(\Sigma_{e}\) has a guaranteed criterion \(\|G_{\text{ue}}(\lambda)\|_{\infty}^{\Omega}<\gamma\) if, and only if, there exist symmetric matrices \(P,Q\in\mathbb{R}^{n_{x}+n_{r}}\) such that \(Q>\mathbf{0}\) and_  
\[\Psi^{T}\Phi\Psi<\mathbf{0} \tag{7}\]  
_where \(\Psi= \begin{bmatrix}A_{e}^{T}&\mathbf{I}&C_{e}^{T}&\mathbf{0}\\ B_{e}^{T}&\mathbf{0}&D_{e}^{T}&\mathbf{I}\end{bmatrix} ^{T},\Phi=\text{diag}\{ \Xi,\mathbf{I},-\gamma^{2}\mathbf{I}\}\), and \(\Xi\) concerning different frequency ranges are listed in Table 1._  
**Remark 1**. : _Lemma 3 provides an exact characterization for (6), which differs from the bounded real lemma and has the potential to improve the approximation capability with less conservatism. Notice that the condition for the solvability of limited-frequency performance is expressed as a BMI condition, which is difficult to solve due to the non-convexity, and it becomes even more arduous when an extra constraint \(G_{r}\in\mathbb{P}\) is imposed._
## 2 Theoretical Models of Light Propagation and Light Scattering
### Dependent Scattering Theory (DST)  
The DST can calculate the scattering properties (\(\mu_{s}\), \(g\), \(\mu_{s}^{r}\), \(p(\theta)\)) for dense colloidal suspensions [10; 19] on a length scale comparable to the optical wavelength. On the length scale, we considered an aqueous alumina suspension as a system consisting of multi-sized spherical particles in the background medium (water). The system corresponds to the infinitesimal volume of the scattering medium in Figure 1a. The DST is based on the first-order solution of the Foldy-Lax equation [46; 47], which is equivalent to the Maxwell equation [11]. The DST describes well the experimental results of the scattering properties [13; 14; 17].  
We denote a particle diameter class by \(\alpha\) or \(\beta\) and the total number of the diameter classes by \(N_{d}\). The scattering coefficient \(\mu_{s,D}\) for the DST is given by  
\[\mu_{s,D}=\int_{0}^{\pi}d\theta\int_{0}^{2\pi}d\phi\sin\theta\sum_{\alpha=1}^ {N_{d}}\sum_{\beta=1}^{N_{d}}\sqrt{n_{\alpha}n_{\beta}}\mathbf{F}_{\alpha}^{Mie} (\theta,\phi)\cdot\mathbf{F}_{\beta}^{Mie*}(\theta,\phi)S_{\alpha\beta}(\theta), \tag{7}\]  
where \(\theta\) is the polar angle and set to the scattering angle \(\cos^{-1}(\mathbf{\Omega}\cdot\mathbf{\Omega}^{\prime})\); \(\phi\) is the azimuthal angle; \(n_{\alpha}\) or \(n_{\beta}\) is the number density for the \(\alpha\)-class or the \(\beta\)-class (\(\{\alpha,\beta\}=\{1,2,\cdots,N_{d}\}\)); \(\mathbf{F}_{\alpha}^{Mie}(\theta,\phi)\) is the scattering amplitude vector using the Mie theory [48]; \(\mathbf{F}_{\beta}^{Mie*}(\theta,\phi)\) is the complex conjugate of \(\mathbf{F}_{\beta}^{Mie}(\theta,\phi)\); and \(S_{\alpha\beta}(\theta)\) is the partial static structure factor. See the reference [19] for the formulations of the other scattering properties and the numerical schemes.
## 6 Test Results
### Stresses of Soil Nails
As can be seen from Figure 14, the stresses of soil nails in the lower two rows decrease heavily compared to the stresses of the upper two rows (as shown in Figure 13). Based on the technical specifications, the bonded tendons can be tensioned effectively when the stress exceeds 15 MPa. However, in fact, the next layer was removed followed by the second excavation as a result of arranged rapid construction; afterwards, tensioning was performed. Consequently, the soil mass influenced by prestressing is in the lower parts instead of the upper parts of the foundation pit. A conclusion can be drawn, that is the stress magnitude and distribution of the soil nails are affected by different prestressing periods: the upper rows are influenced significantly when applying stress earlier; the lower rows will change greatly when applying stress later. As can be seen from Figure 14, the influence of prestressing on the stress of the third and fourth rows of soil nails is only manifested for some of the nails, which were close to the slope surface, compared to those nails away from the slope surface along the longitudinal axis of the nail, which were affected very little. This shows that the influencing range of prestress is very limited. As mentioned before, sections No.4 and No.5 are different retaining structures enhanced with (i) soil nails and prestressed anchors without unbonded parts and (ii) soil nails and prestressed anchors with a 2.5 m unbonded length. When comparing the measured results, the influence of the unbonded length on nail forces can be investigated. As can be seen from Figure 15, the main difference lies in the distribution of the nail forces of the first row. For section No.4, without unbonded parts, the distribution of the nail forces is consistent with the documented results, which presents an inverted saddle shape, that is \"small in the end and big in the middle\". However, for test profile No.5, with a 2.5 m unbonded length, the distribution is manifested as \"double peaks\", which shows that there may be more than one potential slip surface in loose fill materials. For section No.4, due to the anchor being fixed in the overall length, there is deformation of the steel reinforcement bar to transfer the load from the anchor head to the slope. Accordingly, an anchorage effect cannot function adequately. In other words, it amounts to a longer prestressed soil nail. For the other three rows of soil nails, the difference between the two sections is not so obvious. The effect of the unbonded length, which is considered to be the main reason for slope stability in dense materials, is negligible in loose fill materials.
## 2 Proposed Model: QPE Analytical Approximation Model  
The QPE analytical approximation model requires four groups of parameters as input, i.e., the Earth's physical parameters, the satellite platform orbit parameters, the SAR payload key parameters, and the a priori probability of the onboard orbit determination system. In this section, the coordinate systems, vector in the line-of-sight method, and QPE approximation method in the proposed model are described.
## 5 Conclusions  
The Inner Mongolia grassland is an important ecological barrier in northern China and the largest animal husbandry and dairy product base in China. It is of great importance to make a detailed analysis of the spatiotemporal change of the grassland in Inner Mongolia, to help formulate grassland management policies in the future. We applied the CASA model, combined with MODIS NDVI, the GlobeLand30 land-use type, and meteorological data based on the GEE platform, to evaluate the grassland NPP in Inner Mongolia during 2000-2020.  
The results showed that the average grassland NPP was 278.63 g C/m\({}^{2}\) and the growth trend was 2.43 g C/(m\({}^{2}\)-yr) by the OLS method. Especially, the NPP of grassland in east Ordos and the south side of the Greater Khingan Range showed sustained and significant growth. Moreover, the grassland area increased during 2000-2010 and then decreased during 2010-2020. Although the total area of grassland increased during the whole study period, the NPP loss caused by LUCC was greater than the NPP growth caused by LUCC. Precipitation is the most important meteorological factor affecting the grassland NPP, followed by sunshine duration and temperature, and there is a positive relationship between NPP and precipitation in most grassland.  
Our result shows the grassland ecosystem in Inner Mongolia improved, overall, during 2000-2020, but more attention should be paid to the reclamation of grassland and preventing new grassland from desertification again. Moreover, for future studies on grassland NPP, the periodic variation of precipitation could be taken into account. For other land-cover types, both long time series study and short time series change analysis should be considered for the spatio-temporal study of the NPP. The specific time series change should refer to its main impact factors. The remote sensing cloud computing platform like GEE could help with long time series monitoring of ecosystems.  
Conceptualization, K.T.; data curation, R.J.; formal analysis, R.J.; methodology, R.J.; software, R.J., C.P. and L.X.; supervision, K.T.; validation, C.P.; visualization, X.W. and L.X.; writing--original draft, R.J.; writing--review and editing, R.J., K.T. and X.W. All authors have read and agreed to the published version of the manuscript.  
This research was supported in part by the National Natural Science Foundation of China (No. 41871337 and No. 42171335).  
Not applicable.  
The data used in this study are openly available on the websites.  
We would like to sincerely thank Google for providing the free Google Earth Engine platform for scientific research. We would also like to thank NASA LP DAAC for providing the MODIS NDVI data, the China Meteorological Data Service Center for providing the monthly climate data, the China National Geomatics Center for providing the GlobeLand30 data, the Resource and Environment Science and Data Center for providing the vector map of the study area, and the FLUXNET (CN-Du2, CN-Du3, and CN-Sw2) and ChinaFLUX (NMG) flux tower sites for sharing their observed datasets.  
The authors declare no conflict of interest.
# Comparative Analysis of Marine Alternative Fuels for Offshore Supply Vessels
###### Abstract
One of the previous studies applying MCDM to alternative marine fuels, this paper compares LNG and biodiesel, focusing on emissions, cost, and availability [15]. This study identifies key limitations in data availability and subjectivity in criteria weighting, which are still relevant today. The use of multi-criteria decision-making (MCDM) methods has proven to be a valuable tool in assessing the feasibility of alternative marine fuels. MCDM allows for the systematic evaluation of various fuel options by considering a wide range of factors, including environmental performance, economic viability, technical feasibility, and regulatory compliance. This method enables stakeholders to make informed decisions by balancing the trade-offs between different fuel types, making it especially useful in navigating the complexities of maritime fuel transition under the stringent decarbonisation targets. Many MCDM studies are limited by theoretical models and lack real-world data on fuel performance, operational costs, and safety. These evaluations often rely on projected data, expert judgment, and simplified assumptions, reducing their accuracy and applicability to actual ships and the evolving maritime industry. To overcome these limitations, more practical, field-based studies are necessary. Such studies would integrate real-world data from case ships and operating conditions, providing a more comprehensive and accurate assessment of alternative fuels. Practical trials and pilot projects could offer valuable insights into the long-term viability, economic feasibility, and environmental performance of different fuel options, thereby supporting the industry in identifying the most suitable marine fuels for the future. This shift from theoretical to more practicable studies is essential to provide the maritime sector with clear, actionable recommendations for transitioning to sustainable fuel alternatives.
## 1 Introduction
### Disruption Tolerant Networking  
Disruption Tolerant Networking (DTN) [4] addresses the intermittent network issues in unstable and stressed scenarios and exchanges data opportunistically over an infrastructure-less network. DTN thus allows IoT devices to communicate in the presence of connectivity disruption. It employs a store-carry-forward message switching paradigm, as shown in Figure 1, by introducing a new Bundle Protocol (BP) above the transport layer [5]. The source node generates a message bundle and relays the bundle to nearby nodes within transmission range. The relay node stores the bundle and carries it while moving until it meets the destination node or another potential relay node. Finally, the relay node forwards the bundle to the destination node. DTN tackles the issues of intermittent connectivity, high delivery latency, asymmetric data rates, and high error rates in such partitioned networks. DTN can be considered as a Mobile Ad hoc Network (MANET) with intermittent connectivity or a sparse MANET. DTN and MANET are similar in node mobility. Both are infrastructure-less and resource-constrained, and both may frequently experience network partitions. Nevertheless, they are different in terms of communication protocols. MANET uses TCP/IP that requires an end-to-end path for best-effort delivery, whereas DTN uses the bundle layer protocol as mentioned above. Furthermore, while network partitions cause packet losses in MANET, they increase network coverage in DTN with trade-offs in higher delivery delay [6].
# Fully Parallel Homological Region Adjacency Graph via Frontier Recognition
## 4 Specifying Bijective _HomRAG_ and _HomDuRAG_  
Figure 2 depicted the complete homological information of a given image. Although this is a particular and small example, it contains all possible kinds of homological representatives for a subdivided digital image. Therefore, the relations among them can be straightforwardly obtained. The description and one example of each incidence relation in Figure 5, center, includes: _(a)_ An incidence between a cross and a frontier; that is, between a 0- and 1-cell, such as edges '1a', '2c', '3e', etc. _(b)_ An incidence between a frontier hole and the frontier that contains it; that is, between a 0- and 1-cell, such as the double-edge '5g'. The description and one example of each incidence relation in Figure 5, right, includes: _(c)_ An incidence between a frontier and a region; that is, between a 1- and 2-cell, such as edges 'bH', 'cL', 'fK', etc. _(d)_ An incidence between a region hole and the region that contains it; that is, between a 1- and 2-cell, such as the double-edge 'hX'.  
Figure 4: In order to obtain the jump values of each 0-cell, the 4-adjacent 2-cells are compared, so that a 4-bit code is calculated as shown on the right side of the figure. The left side of the figure shows a table with all possible codes (codes 1, 2, 4 and 8 are not possible) and the calculation of the hopping directions for each 0-cell according to this code. \(N\epsilon=N+1\) is the number of columns.  
Figure 3: (a): Simplified \(HSF\). A 2 \(\times\) 3 image embedded in its \(ACC\) framework. There are four blue, one red and one green pixels. Circles represent 0-cells comprising three cases: black circles denote crossings between boundaries, gray denotes belonging to a boundary, and voids denote being inside an object neither belonging to a boundary nor crossings. (b): Jump distance matrix. The matrix of jump distances corresponding to the image. Each 0-cell has two distances pointing to its eastern and western neighbors, respectively.  
Hence, depending on the required application, two adjacency graphs can be calculated and managed:  
(1) The graph with the homological information for crosses and frontier holes, which can be called _HomDuRAG_ (Figure 5, center).  
(2) The graph with the homological information for regions (including adjacencies for region holes); that is, the _HomRAG_ (Figure 5, right).  
Obviously, these two graphs are planar as they come from a planar digital image. The duality among them can be established if the previously discussed particularities of the multiple and self-loop edges were taken into account. In this respect, faces (which are nodes in the dual graph) of the _HomDuRAG_ have been drawn in the center of Figure 5 (Figure 5, right, respectively). Note the special case of the frontier hole numbered as 5, which is the face among the frontier \(h\) and the hypothetical external region outside the image (not drawn here). The task of computing an application for the mutual conversions of these graphs is not developed here due to lack of space, and it is intended for future work.
# Field Pull-Out Tests of Percussion Driven Earth Anchors (PDEAs)
## 4 Field Pull-Out Test Program
### Instrumentation and Test Method  
After the PDEA was hammered to the desired depth or was terminated due to refusal, comprehensive instrumentations were carried out for the field pull-out test to measure the anchor performance during testing. Figure 10 illustrates the setup and components of the field pull-out test. Figure 11 shows the process of driving the PDEA anchors and testing them for pull-out resistance. The anchor head was hammered perpendicular to the surface using a percussion force using an attached hammering rod that would later be taken out once the desired depth had been achieved (Figure 11a). The anchor was then pulled, rotated, and tensioned by applying a tensile load against the anchor (Figure 11b,c). An aluminum hollow plunger hydraulic cylinder (ENERPAC RACH206, 229 KN Capacity, 150 mm Stroke, Enerpac, Columbus, WI, USA) was used to transfer the load from the hydraulic hand pump (ENERPAC P392, Enerpac, Columbus, WI, USA) to the soil tendon (PDEA). A plunger was used to mobilize the cable in the PDEA system. The anchor displacement during the pull-out test was obtained via a displacement transducer (GEOKON Model 1450-6, GEOKON, Lebanon, NH, USA). A donut-type load cell (Transducer Techniques THC-7.5K-V, Temecula, CA, USA) was utilized to measure the pull-out load applied to the PDEA during the test. Strain gauges (Model 4151 Miniature Strain Gauge, GEOKON, Lebanon, NH, USA) were used to measure the strain of the tendon as a secondary data source for the load cell. Finally, the anchor was load-locked by using a top termination plate and grip system at a specified working condition (Figure 11d).  
Figure 10: Schematics of field anchor pull-out test.  
Figure 9: PDEA anchor driving process on west bank slope using mini-excavator: (**a**) setup of a mini excavator and (**b**) anchor driven using the excavator.
# A Survey on Recent Advanced Research of CPS Security
## 3 Reviews
### Audit Framework  
For complex CPS devices, we need to perform a comprehensive safety inspection. In some studies, the authors designed comprehensive testing frameworks with open source tools. These frameworks can cover physical interfaces, protocol security, firmware analysis, etc.  
[PERSON] et al. [57] provided a large-scale analysis of the vulnerabilities in IoT devices for smart homes. In this research, they used a WiFi inspector (a tool included by antivirus products from Avast) to scan internal IoT devices and identified the device types through a set of expert rules and a supervised classification algorithm. After testing 83 M IoT devices in 16 M homes worldwide, the results show that astronomical numbers of devices use weak or default passwords on FTP, Telnet, or HTTP administration and are still vulnerable to known attacks.  
[PERSON] et al. [145] proposed an auditing framework for vulnerabilities in IoT systems, which is based on open-source tools. This framework mainly focuses on communication,firmware, and hardware. Communication analyses check the credential management vulnerabilities in web interfaces and network services. In firmware analysis, the framework searches hardcoded credential, backdoor or compromised third-party libraries. Hardware analysis examines the security of physical interfaces, sensors and memory. As an example, the authors analyzed an IP camera with the proposed framework and found many undetected vulnerabilities.  
[PERSON] et al. [59] developed an extensible testbed to assess the vulnerabilities in IoT devices with open-source tools. The automatic testbed first gathers information on the target device and then uses all possible security tools (e.g., nmap, metasploit, binwalk, tshark, and SSLscan) to test the device. Finally, it generates a test report to show the security assessment results. The authors also tested a wireless camera and smart bulb with the testbed to prove its abilities.  
MiniCPS [92] is a simulator framework that provides a real-time network, programmable logic controllers (PLCs), and physical-layer interactions in CPS for security research. MiniCPS uses Mininet as the lightweight network emulation part and extends it to simulate important CPS components (e.g., PLCs). Furthermore, MiniCPS provides a simple API to capture physical-layer interactions. The authors used a water treatment testbed and a custom SDN controller to test the modeling capability of MiniCPS and successfully developed offenses and defenses for MitM attacks.  
Snout [80] is a pen-testing framework for various IoT protocols. It supports four simple radio protocols (ZigBee, ZWave, WiFi, and Bluetooth) for information gathering and device enumeration. Moreover, it can also assess the vulnerabilities, replay packets, and fuzz packets of specific protocols.
# On the Use of the Effective Width for Simply Supported Generally Loaded Box-Girders
## 5 Average Effective Width  
The theory developed so far explained that the effective width \(b_{en}\) is strictly related to the load shape as well as the wavelengths of its harmonic components. However, one might want to obtain an approximate formula which, still keeping the necessary dependence on the load shape, avoids the need to employ a series expansion, which entails the simple but tedious addition of a larger number of contributions. In this perspective, the idea of an _average effective width_, obtained as a medium value of the wavelength-dependent effective widths, would be desirable.
# Novel 3U Stand-Alone CubeSat Architecture for Autonomous Near Earth Asteroid Fly-By
## 4 Subsystems Analysis
### Attitude Determination and Control System
Moreover, it ensures a slew rate larger than 1.5\({}^{\circ}\)/\(s\), which allows to keep the target in the FOV for a sufficient range of fly-by altitudes and relative velocities, as it has been reported in Figure 6. The finest pointing accuracy of XACT-15 would be highly beneficial for navigation purposes, as it influences both line-of-sight direction accuracy for planets and asteroid, as reported in Reference [21]. Therefore careful analysis should be performed on that, and eventually replacing the iADCS200 with XACT-15 can be considered, reducing significantly allowable volume and mass for the payload.