esa-sceva/satcom-chunk-collection huggingface dataset:
# A Survey on Efforts to Evolve the Control Plane of Inter-Domain Routing
## 4 Issues in the Evolution of the Inter-Domain Routing Control Plane
### Ossification  
The Internet architecture is no longer a coherent whole. It has various components such as transport protocols, router mechanism, firewalls, load balancers, security mechanisms and other middle-boxes. Furthermore, the BGP is one of the most successful protocols on the Internet, and although many researchers have indicated issues related to the BGP since its inception (e.g., lack of end-to-end service guarantees, long convergence time, security issues [17]), practical deployments for new network architecture and protocols in the inter-domain environment are difficult to achieve.  
The major problem for evolving the inter-domain routing system is called \"ossification\", where the architecture becomes very dependent on the protocol and new features are inherently difficult to introduce into the network [9; 32; 33]. For the BGP, the ossification is due to economic reasons and the fact that backward compatibility has to be assured since there is no flag day to switch to a new architecture. Thus, all BGP appliances have to execute the same version of the protocol to operate appropriately, or anomalies in the network may occur (e.g., BGP black holes).  
In other words, the BGP is an inflexible protocol as a consequence of the control and data plane being embedded into the network hardware, and hence, whether the protocol is operational depends on the network equipment used. The dependency between a specific infrastructure and the hardware required creates a barrier to architectural innovation in the inter-domain routing. Hence, a new feature for the BGP has to have a minimum integration within heterogeneous networks and interoperate through different administrative domains (e.g., the Internet). Those requirements frustrated new proposals to evolve the BGP and the ecosystem of inter-domain routing [34].
## 9 Quickest Spectrum Sensing
### Performance Analysis
#### Collaborative Quickest Spectrum Sensing  
When multiple secondary users collaborate for spectrum sensing, they can exchange their observations to enhance the reliability and agility. One difficulty is to tackle the delay incurred by communications since the quickest detection is real-time. We consider a two-node (denoted by \(A\) and \(B\)) case and assume that the transmission of an observation needs \(D\) time slots. In [153], a two-thread CUSUM test is proposed to tackle the communication delay, in which the stopping time claiming the change is the earlier one of two stopping times:  
\[T_{A}^{*}=\min\left(T_{A}^{\alpha},T_{A}^{\beta}\right) \tag{67}\]  
where the stopping times \(T_{A}^{\alpha}\) and \(T_{A}^{\beta}\) are defined as follows (note that we use subscript \(A\) and \(B\) to distinguish the two nodes):  
* Stopping Time \(T_{A}^{\alpha}\): \(T_{A}^{\alpha}\) can be obtained similarly to CUSUM test, namely \[T_{A}^{\alpha}=\inf\left\{t|m_{A}^{\alpha}(t-D)+\sum_{r=t-D+1}^{t}L_{A}(r)\geq \gamma_{A}\right\}\] (68) where \[m_{A}^{\alpha}(t)=\max\left\{m_{A}^{\alpha}(t-1)+L_{A}(t)+L_{B}(t),0\right\}\] (69)
* Stopping Time \(T_{A}^{\beta}\): For \(T_{A}^{\beta}\), only observations at node A during time slots \(t-D+1\) to \(t\) can be used. Then \(T_{A}^{\beta}\) can be written as \[T_{A}^{\beta}=\inf\left\{t\Big{|}\max_{t-D+1\leq k\leq t}\sum_{r=k}^{t}L_{A}(r )\geq\gamma_{A}\right\}\] (70)  
The detailed explanation for the two stopping times and the extension to multiple nodes can be found in [153, 154].
# Forage Biomass Estimation Using Sentinel-2 Imagery at High Latitudes
## 2 Materials and Methods
### Remote Sensing Data  
Sentinel-2 A and B level 2A images with 20 m spatial resolution obtained over the sites of interest in 2019 and 2020 were downloaded during the growing season from the European Space Agency (ESA) Copernicus website. The characteristics of the spectral bands (wavelength and bandwidth) are described on the Copernicus web portal [35].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Year** & **Locations** & **Temperature (\({}^{\circ}\)C)** & **Precipitation (mm)** & **Solar Radiation (MJ m\({}^{-2}\))** \\ \hline \multirow{4}{*}{2019} & As & 11.3 & 216.4 & 2484 \\  & Linnas & 12.6 & 156.8 & 2579 \\  & Ojebyn & 12.1 & 355.1 & 2852 \\  & Röbäcksdalen & 11.9 & 262.4 & 2144 \\  & As & 11.5 & 217.4 & 2437 \\  & Linnas & 12.8 & 204.6 & 2748 \\  & Öjebyn & 12.3 & 318.2 & 2667 \\  & Röbäcksdalen & 12.3 & 312.7 & 2203 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Meteorological conditions of the four study sites during the growing season (May–September) in 2019 and 2020. The temperature shown is daily averaged for the whole growing season, whereas precipitation and radiation are accumulated values. Data were obtained from Lantmet [34].  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Locations** & **Latitude** & **Longitude** & **Year** & **Management** & **Fields** & \(n\) \\ \hline As & 63\({}^{\circ}\)15/N & 14\({}^{\circ}\)36/E & 2019/2020 & Organic & 1 & 30 \\ Linnas & 63\({}^{\circ}\)8/N & 17\({}^{\circ}\)45/E & 2019/2020 & Organic & 1 & 42 \\ Öjebyn & 65\({}^{\circ}\)21/N & 21\({}^{\circ}\)24/E & 2019 & Conventional & 1 & 21 \\ Röbäcksdalen & 63\({}^{\circ}\)47/N & 20\({}^{\circ}\)14/E & 2019/2020 & Conventional & 5 & 87 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Locations, coordinates, working years, management and number of sample points (\(n\), 3 subsamples were averaged as 1 observation, i.e., sample point) of the study sites. Organic means no chemical fertilizer or herbicide was applied. Conventional indicates that the field was managed using chemical fertilizers and possibly herbicides.  
The scene classification map (SCL) produced using the Sen2 Cor algorithm from the European Space Agency classifies Sentinel-2 images to twelve classes, including cloud, shadow, vegetation, soil, water and snow [36], with Level 2A images at 20 m spatial resolution. This was used to mask all of the pixels, which were recognized as non-vegetation, before further processing and analysis.
# Quality Assessment of 3D Synthesized Images Based on Textural and Structural Distortion Estimation
## 4 Experiments and Results  
The performance of the proposed 3D video quality assessment metric was evaluated on the benchmark stereoscopic Media Communications Lab - MCL-3D dataset [70] and compared with other 2D and 3D-IQA metrics. We conducted multiple experiments of different types to evaluate the performance and statistical significance of our proposed method. The results were also compared with existing 2D- and 3D-IQA algorithms.
_Appl. Sci._**2012**, \(2\), 139-159; doi:10.3390/app2010139  
_applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
Real-Time PCR Data Processing Shown by the Analysis of Colorectal Specific Candidate Genes, ERCC1, RRM1 and TS in Relation to \(\beta\)2M as Endogenous Control  
**[PERSON] 1, [PERSON] 1, [PERSON] 1, [PERSON] 2,3 and [PERSON] 1,***  
1 Department of Pathology und Cytology, Dr. Horst-Schmidt-Kliniken (HSK), Wiesbaden 65199, Germany; E-Mails: [PERSON](\(\beta\))pathologie-wiesbaden.de (M.D.); [PERSON](\(\beta\))pathologie-wiesbaden.de (H.B.); [PERSON](\(\beta\))pathologie-wiesbaden.de (S.S.-B.)
2 Department of Radiotherapy, Lippe Hospital, Lemgo 32657, Germany; E-Mail: ralph.muecke(\(\beta\))klinikum-lippe.de
3 Department of Radiotherapy, St. Josefs-Hospital, Wiesbaden 65189, Germany
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +49-611-43-3419.  
_Received: 29 December 2011; in revised form: 7 February 2012 / Accepted: 8 February 2012 / Published: 24 February 2012_  
**Abstract:** Currently, quantitative real-time PCR (Q-PCR) of archival formalin-fixed, paraffin embedded (FFPE) tissue is a critical tool for research and is not well established in routine diagnostics. Therefore, continuous improvement in mathematics and statistics associated with interpreting final accurate and reproducible results are fundamental. This project describes and discusses specificity and sensitivity with respect to intra- and inter-assay variances by use of a commercial Human Reference RNA and individual RNA derived from colorectal cancer patients (n = 25). All patients were treated with 5-fluorouracilacil (5-FU) and a concomitant pelvic radiotherapy (50.4 Gy). Quality assessment of target tissue samples was evaluated by clinicopathological findings and optical density (OD) measurements. We analyzed the steady state messenger RNA (mRNA) expression level of a small panel of cancer relevant genes, excision repair cross-complementing group 1 (_ERCC1_), ribonucleoside-diphosphate reductase subunit M1 (_RRMI_), thymidylate synthase (_TYMS_) and \(\beta\)-2 microglobulin (\(\beta\)-2M_) as endogenous control. The mRNA of a Human Reference RNA, tumor and non-neoplastic material was reverse transcribed into its complementary DNA (cDNA). cDNA was amplified based on dual-labeled TaqMan real-time fluorescence measurements. The real-time efficiency and therefore the output data can be influenced through the kind of calibrator used, the amount and quality of used RNA and by the degree of individual assay variability. Each sample presents an individual amplification curve. Thus, confirmation of primer specificity, one or more invariant endogenous controls, RNA and cDNA quality, as well as real-time PCR amplification efficiencies and linearity calculations from individual slopes or R\({}^{2}\)-values must be included in each study.  
keywords: _\(\beta\)2M; ERCC1; Q-PCR-Efficiency; RRM1; TYMS_+
Footnote †: journal: Journal of Experimental Biology
# Green IoT: A Review and Future Research Directions
## 4 Energy-Efficient M2M Communications
### Power-Aware Scheduling  
Power-aware scheduling is an important aspect of energy-efficient data transmission in M2M communications. By carefully managing the energy consumption of M2M devices, it is possible to extend the longevity of battery life of these devices and improve their overall performance and reliability. There are several approaches to power-aware scheduling in M2M communications, which can be summarized into two points: (i) downsize the energy consumption of M2M devices while still satisfying the required performance objectives. These algorithms can consider various factors, such as the remaining battery life of the M2M device, the importance of the data being transmitted, and the energy efficiency of the transmission technology [36]; (ii) use power-saving modes in M2M devices to reduce energy consumption during periods of low activity. These modes can include sleep modes, in which the device shuts down non-essential components to save power, and idle modes, in which the device reduces its operating frequency to conserve energy.
# Prediction Models for Mechanical Properties of Cement-Bound Aggregate with Waste Rubber
## 1 Introduction
The testing of the moisture sensitivity of asphalt mixtures using the UPV in [21] resulted in a linear equation between the seismic modulus and the UPV with a good coefficient of determination. Using this model, the moisture susceptibility of asphalt specimens can be predicted. In addition to the desire for non-destructive testing methods, the trend of the circular economy has also been expressed in recent times. There are increasing numbers of applications of different waste materials in composite materials used in construction. Some of these are used as aggregates, while those with pronounced pozzolanic properties are used as binders. For example, [PERSON] et al. [22] investigated the possibility of using different additives to cement and different fibers in the production of concrete bricks, while [PERSON] et al. [23] investigated the possibility of using glass powder in combination with waste rubber in concrete. Rubber has also showed potential in increasing the resistance of concrete structures to the impact of earthquakes [24]. Guided by the desire to preserve the environment, rubber was used as a waste material in this work, since, due to its pronounced elastic properties, it can affect the reduction in the high stiffness of cement-stabilized aggregates and, as a waste material, it is very easily available on the market, considering the large consumption of tires. In addition, in most countries in Europe, the collection and processing of tires is very well organized [25]. Furthermore, the possibilities of using waste rubber in road construction is highlighted [24; 26]. However, prior to waste rubber's incorporation in pavement materials, it has to pass through a certain separation process, in which steel fibers are separated from the rubber. These steel fibers are applied as reinforcements in concrete [27]. The aim of this research is to develop reliable prediction models for \(\mathrm{f_{c}}\) and \(\mathrm{E_{st}}\) estimation based on the measured UPV of CBA modified with waste rubber. Such a model would ensure a simple, fast, non-destructive approach to characterizing CBA by adding waste rubber. Furthermore, based on the literature review, it is concluded that none of the prediction models developed to date consider both the UPV and the length of the curing regimes of specimens for the prediction of mechanical properties, which would greatly facilitate the application of such models. Furthermore, a complete lack of prediction models for estimating the static modulus of elasticity was observed. Considering the difficulty of precisely determining this parameter, such a model would contribute significantly to this field.
## 3 Results and Discussion
### Assessment of Recovery of Tocopherol in Food Matrices  
All foods were spiked with a mix of the four tocopherol standards at two concentrations: one at the same concentration level of the main tocopherol isoform (\(\alpha\)-tocopherol) found in unspiked analyzed samples and the other at twice that concentration. After calculating the concentration of each tocopherol isoform in each spiked sample using the calibration curves shown in Table 1, the recoveries were estimated in each case and the results are reported in Table 3.  
The recoveries were in the ranges of 81.3-100.3% for \(\alpha\)-tocopherol, 77.8-108.2% for \(\beta\)-tocopherol, 78.3-105.8% for \(\gamma\)-tocopherol, and 79.5-106.3% for \(\delta\)-tocopherol. In all cases, recovery values were within the 70-120% range which is usually considered acceptable for most analytical method guidelines [32], although most recoveries were above 80%. This fact shows that both extraction methods are efficient in collecting tocopherols from all of the assayed food matrices.
# A Component-Based Approach to Early Warning Systems: A Theoretical Model
## 2 Materials and Methods
Nevertheless, integrating all these factors into EWSs would be highly complex and financially demanding. These factors may include cartographic data, geological information, or other contextual variables that are difficult to measure. For this reason, the identification of primary and secondary causes in this study focused solely on critical, measurable physico-chemical parameters. For the analysis of sensors, only scientific literature from Scopus and Web of Science database was used. Hundreds of articles were reviewed to identify five to ten sensors per parameter, thereby creating a framework for further study and summarising the types of sensors used. Targeted search strategy was employed to identify relevant literature on sensors used in EWSs. The search query \"name of the hazard' sensors for early warning system\" was used, and results were sorted by relevance. Each article was then reviewed to extract information on sensor types. This compiled sensor database serves as a foundation for future research and complements the sensor analysis conducted in this study. The materials used in this research included scientific studies, articles, and reports on existing EWSs and the requirements set by various global international organisations and institutions. The primary sources of relevant literature were Scopus and Web of Science, along with official reports and documents from organisations operating in the humanitarian sector, including the United Nations (UN) and legal regulations. The selected materials focus mostly on the impacts of natural disasters, with an emphasis on EWS functionality and requirements. The proposed EWS components are based on identified gaps and needs highlighted in the review of multiple studies, taking into account the perspectives of the authors referenced in the text. The identification of primary and secondary parameters, as well as the manifestations of natural disasters, is supported by the research presented in the Sections 1 and 4, ensuring a comprehensive approach to this issue. To support these analyses, a comparative study and categorisation of different EWS approaches was conducted, from which a proposed conceptual framework was developed. The theoretical conclusions were further substantiated by case studies on the implementation of EWSs, where gaps and shortcomings were identified. These gaps are reflected upon and analysed throughout the article, providing a comprehensive perspective on the current state of EWSs and potential improvements.
# Collaborative Robotics: Enhance Maintenance Procedures on Primary Flight Control Servo-Actuators
## 3 Critical Aspects Related to the Automatic Adjustments Procedures
### Mechanical-Related Challenges
#### 3.1.3 EHSA Reference Frame Definition
However, possible mounting errors could occur, leading to non-zero values  
Figure 7: (**a**) Setting of the EHSA reference frame with the camera using the checkerboard on the fixture on which the servo-actuator is mounted; (**b**) View of the checkerboard from the camera while updating the coordinates of the EHSA reference frame. of the roll (\(\psi\)), pitch (\(\varphi\)), and yaw (\(\theta\)) angles. As an example, in Figure 8 is schematized the procedure used to estimate the roll and pitch angles, exaggerated for better clarity, by measuring the distances \(y\) and \(x\) between a point on the checkerboard, detected by the camera at the working distances \(d\), and the projection of the camera reference frame on it. Several measurements, taken with a different configuration of the camera, showed a linear correlation between \(d\)-\(y\) and \(d\)-\(x\), leading to the definition of \(\psi=\arctan(\frac{y}{d})\) and \(\varphi=\arctan(\frac{x}{d})\). Once known the position of the camera with respect to the TCP currently mounted on the robot, it has been used to obtain the data necessary to build the 4x4 roto-translation matrix \({}^{\text{TCP}}\mathbf{A}_{\text{EHSA}}\). To do so, a checkerboard, similar to the one reported in Figure 7b, has been positioned on the fixture on which the faulty unit is mounted, so that the robot could take a picture of it as shown in Figure 7a. Since the EHSA fixture can be positioned, in different ways, inside the test bench, but with a fixed high with respect to the robot, one picture is enough to obtain the rotation around the \(Z\) axis and the two X and Y translations (\(\varepsilon_{z}\), \(\delta_{x}\), and \(\delta_{y}\)) of the EHSA reference frame with the respect to the one defined on the camera. The roto-translation matrix can be then simplified, leading to:  
\[\text{CAM}\mathbf{A}_{\text{EHSA}}=\left[ \begin{array}{cccc}c_{zz}&-s_{ez}& 0&\delta_{x}\\ s_{ez}&c_{ez}&0&\delta_{y}\\ 0&0&1&0\\ 0&0&0&1\end{array} \right] \tag{3}\]  
In so doing, even if the fixture or the work cart change their positions due to, for example, different models of test benches or workspace limitations, it would not be necessary to set all the coordinates of the servo-actuator waypoints again.
## 5 The Group-Aware Query Region Tree (GQR-Tree)
### Cooperative Evaluation of CM Range Monitoring Queries
#### 5.4.2 Object-Side Tasks  
Each moving object \(o\) maintains its current resident domain \(N\) and a _local query table_ (hashed on query identifiers), which stores, for each query \(q\in g\_N\), an identifier \(q.id\) and a spatial query range \(q.R\). Whenever \(o\) changes its location, it monitors its spatial relationships with \(N\) and spatial query ranges stored in the local query table. In particular, when \(o\) moves, it checks if it exits \(N\) or crosses any of the boundary of spatial query ranges stored in the local query table. If \(o\) exits \(N\), it sends the \(RequestDomain(o.id,o.loc_{new},o.Cap,N_{old})\) message to the server. On the other hand, if \(o\) crosses some spatial query range \(q.R\) stored in the local query table, it sends the \(UpdateResult(o.id,o.loc_{new},q.id)\). In addition, \(o\) expects the following broadcast messages from the server and processes them as follows:  
* \(InsertQuery(q.id,q)\): When \(o=(o.loc,o.A)\) receives the \(InsertQuery(q.id,q)\) message from the server, given the query \(q=(q.R,q.V)\), it checks if (i) \(q.R\) contains \(o.loc\) and (ii) it is matched to \(q.V=\{q.v_{1},q.v_{2},\ \cdots,q.v_{m(\leq n)}\}\), _i.e._, \(\forall o.\acute{a}_{i}\,(1_{\leq i\leq m})\in o.\acute{A}:\ o.\acute{a}_{i} =q.\acute{v_{i}}\,(1_{\leq i\leq m})\) or \(o.\acute{a}_{i}\in q.v_{i}\) (assuming a set of non-spatial attributes \(A=\{a_{1},a_{2},\ \cdots,a_{n}\}\)). If this is the case, \(o\) sends the \(UpdateResult(o.id,o.loc_{new},q.id)\) message to the server in order to let the server insert \(o\) into the result of \(q\). Next, \(o\) checks if \(q.R\) is covered by or partially intersects its current resident domain \(N\). If so, it inserts \(q.id\) and \(q.R\) into the local query table. It should be noted that if the number of query identifier and spatial query range pairs stored in the local query table becomes greater than the capability \(o.Cap\) of \(o\) due to the insertion, \(o\) sends the \(RequestDomain(o.id,o.loc_{new},o.Cap,N_{old})\) message to the server in order to receive a new resident domain (together with new query identifier and spatial query range pairs).  
* \(DeleteQuery(q.id)\): When \(o\) receives the \(DeleteQuery(q.id)\) message from the server, it just deletes the pair of \(q.id\) and \(q.R\) from the local query table if the pair is stored in the local query table.
# Correlation Analysis of Macro-Micro Parameters of Sandstone Based on PFC3D
## 4 Instance Verification
### Verification of Results  
Based on the values of the aforementioned microscopic parameters, uniaxial compression, tensile, and triaxial compression numerical simulations were conducted with the numerical model. The obtained simulation results were compared and verified against the laboratory test results, as follows: Figure 7 shows the failure mode of the rock sample under uniaxial compression. It can be observed that the crack propagation in the uniaxial compression simulation was generally consistent with the splitting pattern of the experimental rock sample. The stress-strain curve (Figure 8) obtained from the numerical simulation and the laboratory test aligned well for the elastic stage, peak strength, and residual strength, verifying the rationality of the microscopic parameters. In conclusion, after applying the mesoscopic parameters obtained through regression model inversion to PFC numerical simulations, the resulting stress-strain curves closely matched the laboratory test results for three critical mechanical properties: elastic modulus, peak strength, and residual strength. The error between the simulation values and experimental values was controlled within 5% (see Table 10), and the compressive-tensile strength ratio was significantly improved from the traditional PBM range of 5-8 to 12.7, which is close to the measured value of 12.1. The simulated failure modes also aligned with the experimental observations, showing that cracks propagated along the shear plane and exhibit tensile failure characteristics. This fully verifies the reliability and applicability of the mesoscopic parameter regression model established in this study for mechanical modeling of sandstone. This method not only enhances the scientific accuracy of parameter calibration but also provides a transferable technical pathway for the numerical simulation of similar rock materials in the future.