esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Submillimeter-Level Microwave Ranging
### MWR Payload Development  
The MWR system payload has been carefully designed and developed, with the diagram of one spacecraft shown in Figure 2. Several things have to be determined during the design phase, including detailed system composition, frequency planning, link budget analysis, system measurement error analysis, antenna polarization mode and optimization, high-precision time synchronization, on-ground test and verification, etc.  
Currently, MWR system payload prototypes have been developed that consist of two sets of identical equipment, mainly including (a) a K/Ka-band transceiving antenna: a single corrugated horn antenna that transmits-receives K/Ka-band dual-frequency microwave signals; (b) a frequency reference unit: an ultra-stable oscillator (USO) is used as the frequency reference source of the whole system; (c) a K/Ka-band microwave channel: up-converts the reference frequency to transmission carrier frequency (TCF) and down-converts the TCF received from another satellite to a single-carrier signal that completes the amplification process and reception mixing; and (d) a digital signal processing unit: conducts sampling and digital processing of the down-converted K/Ka-band carrier phase signal and BeiDou signal to complete the high-precision carrier phase extraction. Here, we provide a brief introduction of these four components, as:
# Metallurgical Aspects in the Welding of Clad Pipelines--A Global Outlook
## 1 Introduction
To retain the corrosion resistance of the clad pipe, the root and hot pass should be deposited with a wire compatible with the clad material. This limits the freedom in the selection of welding consumables. In recognition of this situation, the development of hyperbaric butt-welding technology was initiated with the aim to develop a fully remotely controlled dry welding technology for deep waters (below about 200 m depth). In addition to the welding technology challenges, there are metallurgical aspects that need to be considered. Therefore, the present paper addresses the metallurgical aspects in the welding of clad pipes, involving clad materials such as AISI 316L SS and Inconel 625 (typically of 3 mm thickness) and the typical pipeline API X60/X65 high-strength carbon steels. With the addition of the specific welding wire--Ni-based superalloys such as Inconel 625 and Alloy 59--a complex multi-material system is formed that needs more comprehensive understanding. Inconel 625 filler wire has been proven (high toughness at -30 \({}^{\circ}\)C) for hot-tap welding operating in subsea conditions [13] in joining X65 high-strength steel pipelines. Examples from an ongoing research project will be used to illustrate various microstructure observations, concentrating on the clad, the heat-affected zone (HAZ) of the pipe and the weld metal, or the fusion zone. Possibly, for onshore operations, a relatively new method of friction drilling and form tapping can be used to reduce the harmful effect of heat on welded joints [14]. Under hyperbaric conditions for pipe repair, from a practical standpoint, the use of multiple wires will be very difficult, such as is frequently employed in conventional clad pipeline welding; i.e., a CRA alloy for the root and hot pass, followed by a buffer layer of either Fe or Ni, and finally, filler passes by a matching ferritic wire. In a fully remotely controlled hyperbaric operation, a much simpler solution with one wire only will be employed throughout the weld. The use of backing gas is applicable since it is purged into the chamber prior to welding to remove the seawater. The moisture and oxygen content of the chamber gas must be carefully controlled continuously during welding. Moreover, the use of one welding process for the root pass and another for the fillers will not be suitable. Although GTAW is frequently used in the root pass welding of clad pipes due to the smooth surfaces, it is not applicable in remotely controlled conditions. GMAW is therefore under development for future dry subsea pipe welding, including the use of an inner clad. The manuscript is organized as follows: description of the clad pipes and their production is followed by an explanation of microstructure evolution principles (applicable for both clad pipe production and welding), applied to the weld metal and HAZ microstructure evolution with different material combinations, a description of hyperbaric (repair in subsea level) welding conditions, and an outline of the potential numerical simulation of the arc physics.
# Digital Shearing Speckle Pattern Interferometry Based on Rochon Prism and Its Application
## 1 Introduction  
It has been nearly 40 years since [PERSON] and [PERSON] introduced shearography [1; 2]. As an important optical measurement method, shearography has been widely used in the fields of shape measurement [3], vibration analysis [4; 5], and strain detection [6; 7; 8]. Generally, a basic shearographic measurement system uses a shearing device, such as a Michelson interferometer, a Wollaston Prism (WP), or an optical wedge [9]. By passing through a shearing device, two identical but slightly misaligned images are generated and interfere with each other.  
In a previous study, we introduced a shearographic measurement system based on the WP and the temporal wavelet transformation (TWT) [10]. Compared with the classical shearing devices, such as the Michelson interferometer, WP has an advantage in terms of common optical path arrangement, which improves the measurement stability and repeatability. WP also does not require the shifting structure of the Michelson interferometer. In further experiments, we proved the feasibility of combining the polarization splitting effect with the electro-optical crystal materials in temporal heterodyne shearing speckle pattern interferometry [11]. However, there are still some problems to be solved. For example, the polarization splitting effect of WP is not specially perfect under an illuminant of high intensity, and the lights emergent from the prism are not only an e-o light and an o-e light, but also a transmission light, which confuse the interference signals and reduce the signal-to-noise ratio (SNR) and the image contrast [12].  
To solve these problems, we introduced the Rochon Prism (RP) to replace the WP. RP is also a traditional optical beam splitter, but different from the WP, the o-light is transmitted without refraction angle passing through the RP. As such, only two kinds of interference light occur in the interference field generated by the RP. In this study, we analyzed the advantages of the shearography based on RP, and conducted relevant experiments to compare the errors between WP and RP. The experimentalresults show that the RP meets the shearographic requirements and improves the accuracy of the measurement system.
# Recent Advances and Insights into Bromelain Processing, Pharmacokinetics and Therapeutic Uses
## 7 Discussion and Future Perspectives  
Bromelain is one of the most thoroughly investigated proteolytic complexes that is characterized by several thiol endopeptidases [136]. As discussed in this review, bromelain is extracted predominantly from pineapple stems and fruit [53]. However, a number of studies have underlined the possibility that bromelain can be extracted from by-products, such as the peels, core or crown, which would fulfil the requirements of a zero-waste approach [3].  
Several studies have been carried out to evaluate the stability, purification and potential applications of bromelain, especially in the pharmaceutical and nutraceuticaltical sectors [5; 137]. While bromelain has been demonstrated to improve several conditions, thanks to its anti-inflammatory and anti-oedema properties, its mechanisms of action are yet to be completely understood [113].  
Extraction techniques for bromelain include both conventional and unconventional methods (Table 4), which can also be combined in some cases [1]. Alternative methods for bromelain purification can be applied to achieve improved cost-effectiveness, purity and yields. In fact, one of the most important limitations to bromelain commercialization is the high cost of the extract (about 2400 USD/Kg), which is mainly due to the required purification processes [12]. Although unconventional technologies, such as chromatography, reverse micellar systems, gel filtration, aqueous two-phase systems and others, have been thoroughly investigated and demonstrated to improve purity and yield, compared with conventional techniques, none have presented an economic assessment of the processes involved. Moreover, there is still a lack of standardized international guidelines for bromelain extraction.  
One of the most promising current strategies involves the production and purification of recombinant bromelain, which may decrease the overall process cost and improve bromelain yield and purity [50].  
Considering the great medical and industrial interest in bromelain, future studies on convenient and effective extraction and purification techniques, the drafting of new international guidelines, an extensive costs analysis and the evaluation of process scaling-up are necessary and are a challenge that may decrease production steps and costs. In the clinical setting, new pharmacodynamics and pharmacokinetics studies are needed to better understand the potential applications of this nutraceutical in terms of efficacy and safety.
# VHF Omnidirectional Range (VOR) Experimental Positioning for Stratospheric Vehicles
###### Abstract  
The usage of aeronautical radio-frequency navigational aids can support the future stratospheric aviation as back-up positioning systems. Although GNSS has been extensively redundant in the last years of space operations, radio NavAids can still be supportive of navigation and tracking for novel mission profiles. As an example, in 2016, VHF Omnidirectional Range (VOR) has been proven to work well above its standard service volume limit on a stratospheric balloon flight with the STRATONAV experiment. While VOR provides the \"radial\" measurement, i.e., the angle between the Magnetic North and the line between the receiver and the transmitting ground station, the intersection of two or more radials at a time allows to perform ground track reconstruction for the vehicle to be tracked. This paper reports the results from the data re-processing from STRATONAV: the acquired radials have been intersected in order to achieve positioning. The radials interfacing method, the position calculation methodology, and the data acquisition strategies from STRATONAV are reported together with the data analysis results.  
stratosphere; positioning: Software Defined Radio; balloon; HAPS; VOR Article  
1
## 3 Design Challenges of MAC Protocol for IBSN  
The design of an efficient MAC protocol for IBSN faces a number of challenges, such as interoperability, scalability, QoS, and energy efficient communication. There are various low-power techniques, such as the fixed duty cycling technique in SMAC [25] and adaptive wake-up slots in TDMA [26] to ensure energy efficient communication in a wireless sensor network. They are, however, not energy-efficient for heterogeneous IBSN and will not suffice. Unlike the supported scenarios by SMAC, the traffic characteristics in a IBSN vary from periodic to non-periodic and vice-versa [8]. Therefore, the concept of the fixed duty cycling technique gives limited answers when it comes to the heterogeneous behavior of autonomous sensor nodes in a IBSN. The dynamic nature of these nodes does not urge synchronized periodic wake-up periods. Data from some of the sensor nodes, for instance, electrocardiogram (ECG), may be set at a one packet per hour rate to the coordinator, while others may send data twice a week. Nodes should also have the capabilities to sense and transmit emergency information. The data traffic in IBSN is either normal, on-demand, or burst.
# Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges
## 2 Research Progress in Smart Mobility and Gap Analysis
### Summary and Research Gap Analysis
Authors in [5,6] primarily focused on describing the benefits of smart cities for the users and how smart mobility can be used as an aid to solve traffic congestion, urban planning, recommendation systems, etc. In [7], it was concluded that responsible behavior and the attitude of the inhabitants have a positive effect on smart mobility initiatives. The security aspects of smart mobility were discussed in [8,9]. Some of the key points which were found missing in the reviewed literature include:  
* User Privacy
* Data Integration issues
* Data Standardization issues
* Sensor characteristics
* Impact of external environment on sensing capabilities of sensors. In this paper, we have provided a holistic review which covers the above aspects in addition to those previously discussed. User privacy concerns and a lack of technical and operational knowhow restrict common people, especially elderly people, women and laborer workers, from using smart mobility services [45]. Several privacy preserving approaches have been developed in recent years for the effective adoption and ease of use of mobility services [46,47]. The governance issues in smart mobility services, including \begin{table}
\begin{tabular}{c c c} \hline \hline
**S. No.** & **Paper (Year)** & **Focus** \\ \hline
25. & [PERSON] et al. (2019) &
\begin{tabular}{c} Holistic methodology to model the efficiency of public transport facilities schemed as a whole in a multi-stakeholder context from end-to-end perspective. \\ \end{tabular}
\end{table} 
Table 1: \(Cont\). consent-based data capturing, manipulations and usage, data integration and standardization challenges, were covered in [48; 49; 50; 51]. The importance of sensor characteristics for sensing and capturing the data about the subject and its surroundings plays a vital role in developing effective and intelligent mobility initiatives [52; 53; 54; 55]. The impact of external environments on the performance of the sensors is an essential field of study, as discussed in [56; 57]. The materials used in the development of sensors also play an important role in deciding their usage and life [57]. Apart from these, a few open issues which are still prevalent in smart mobility include:  
* Enforcing uniform and ubiquitous mobility laws, rules and regulations
* Citizen participation in mobility initiatives
* Crowdsensing in smart mobility
* Interoperability
* Legacy Infrastructure setups
* Amicable Cooperation between public-private mobility services players. With the rapid technological transformations, these open issues will surely be addressed in years to come. As the smart city initiative is slowly becoming a reality, extensive research is being conducted to handle such open issues [58; 59].
# The Impact of Automated Vehicles on Road and Intersection Capacity
## 5 Capacity Calculation Model of Signalized Intersection in a Mixed Environment  
### Capacity Calculation Model of Signalized Intersection  
Through the analysis of the previous sections, it can be seen that the calculation of capacity at signalized intersections is mostly calculated by saturated flow rate (or saturated flow rate), and the saturated flow rate is modified on the basis of the basic saturated flow rate, which is the maximum traffic volume passing through a certain section of the road in a certain unit of time. Based on the derivation of the flow-density of road homogeneous traffic flow in this chapter, the basic saturated flow rate of a road under a man-machine hybrid driving environment, can be easily obtained.  
Therefore, this section proposes using a revised calculation model for assessing signalized intersection capacity in a mixed environment, which can essentially be used to identify the basic saturated flow rate in a mixed environment, as shown in Table 7.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**The Proportion of** & **Theoretical** & **Actual** & **Mean Absolute Error** & **Mean Relative Error** \\
**Autonomous Driving** & **Mean** & **Mean** & **(pcu)** & **(\%)** \\ \hline
0 & 1526 & 1381 & 145 & 9.5 \\
0.1 & 1574 & 1508 & 66 & 4.2 \\
0.2 & 1632 & 1529 & 103 & 6.3 \\
0.3 & 1704 & 1559 & 145 & 8.5 \\
0.4 & 1794 & 1584 & 210 & 11.7 \\
0.5 & 1905 & 1609 & 296 & 15.5 \\
0.6 & 2047 & 1756 & 291 & 14.2 \\
0.7 & 2229 & 1942 & 287 & 12.9 \\
0.8 & 2470 & 2171 & 299 & 12.1 \\
0.9 & 2806 & 2493 & 313 & 11.2 \\
1.0 & 3313 & 2988 & 325 & 9.8 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Average errors of actual and theoretical traffic volumes under different proportions of autonomous vehicles.  
Figure 7: SUMO simulation diagram: traffic flow in a mixed environment.
# Unsupervised Feature Selection for Outlier Detection on Streaming Data to Enhance Network Security
## 4 Unsupervised Feature Selection for Streaming Outlier Detection
### Model for Scoring and Clustering Features
We have (i) increased the factor of the Log-Likelihood within the BIC (Bayesian Information Criterion) computation, relevant to finding the optimum number of clusters \(k\) in order to better cluster the feature scores by more distinct spacing between data points. To avoid the case of too few feature scores in the top cluster yielding a small \(\gamma\), we (ii) add a minimum constraint of having at least \(\gamma_{min}\) feature scores in the top cluster. Thus, \(\text{\sc{Kmeans.1d.dp}}\) is performed as long as \(|cluster_{1}|\geq\gamma_{min}\) by successively reducing \(k\) starting from the initial optimum number of clusters \(k_{opt}\). This adds a negligible constant to big \(\mathcal{O}\) notation in the worst case where \(|cluster_{1}|=1\) of \(\gamma_{min}-1\). For \(\gamma_{min}\), we are proposing a minimum number of \(\lceil\sqrt{d}\rceil\) features, which is often used as a rule of thumb for selecting features and achieved promising results in our evaluation. However, \(\gamma_{min}\) can also be freely set by the domain expert. Since \(\gamma_{min}\) only states the least requirement and the second, third, etc. best clusters might have promising feature scores as well. We are (iii) also proposing to check the distances between the cluster centers and their radii, which are defined by the utmost feature score from the cluster center as depicted with semicircles in Figure 4.  
Thus, not only the features of the cluster with the top scoring features \(cluster_{1}\) are returned, with \(|cluster_{1}|\geq\gamma_{min}\), but also those where the distance between the centers of \(cluster_{i}\) and \(cluster_{i+1}\) is less than the sum of radii of \(cluster_{i}\) and \(cluster_{i+1}\). Within the example of Figure 4 for \(d=20\), \(\lceil\sqrt{d}\rceil=5\), \(|cluster_{1}|=6\) the feature scores of \(cluster_{1}\) are returned with (ii) and \(\gamma=6\) whereas those of \(cluster_{1}+cluster_{2}\) are returned with (iii) and \(\gamma=11\). It is again noted that the cardinality has a significant impact on the classifier since some even perform well with only a few features [26; 51] whereas others operate best in high dimensions [14] or fluctuate with a varying number of relative features [52]. However, depending on the classifier used, one might adapt \(\gamma_{min}\) or not use the cluster approach at all by setting \(\gamma\) to a certain value. UFSSOD then ranks the feature scores in descending order, e.g., by the widely accepted Quick Sort or Merge Sort algorithm, and returns the top-\(\gamma\)-features. Depending on the chosen setup, in terms of complexity, we propose Merge Sort since the space and time complexity of \(d\) feature scores, even in the worst case, is \(\mathcal{O}(d)\). A summary of the clustering functionality of UFSSOD is shown in Algorithm 3.
## 3 Results
### Detection Probabilities
#### 3.2.2 Correct Detection Probability (CDP)  
CDP means the likelihood of a SU affirming the existence of a PU when there is a PU in the spectrum and the channel is not free. It is the time when the channel is occupied by PUs. If sensing time is much higher for SUs, PUs find no interference from SUs and can easily finish their transmissions during that period. After the PUs' transmissions are completed, SUs find the channel free [24].
## 3 System Overall Process
### Decoder
#### 3.3.2 Localization Decoder
During training, the network optimizes the parameters through backpropagation based on the error between the center point and top-right coordinates of the positive anchors and the ground truth boxes, ultimately producing a well-trained network. Figure 10: ECA module. In this experiment, the localization decoder generates feature maps at three different scales, with each feature map corresponding to a specific target size. These feature maps are divided into fixed grid sizes, such as 13 \(\times\) 13, 26 \(\times\) 26, and 52 \(\times\) 52, with each grid cell assigned three anchors of varying aspect ratios. The sizes of these anchors are dynamically calculated using the K-means algorithm based on the distribution of object box sizes in the dataset. Through multi-scale feature processing, the localization decoder effectively accommodates the detection requirements for both small and large objects, significantly improving the model's localization accuracy and robustness.