esa-sceva/satcom-chunk-collection huggingface dataset:
# A Distance-Encoded Bloom Filter for Fast NDN Name Lookup
## 2 Related Works and Background
### Hash Table-Based Name Lookup
#### 2.3.2. Binary Search Order by Length  
To reduce the hash table accesses, a binary search by prefix length is proposed [8]. This idea was originally proposed by [PERSON] in the field of IP lookup [28]. This binary search starts at the middle component level. If a match is found, the search range shifts to the longer half of the levels; otherwise, it shifts to the shorter half.  
Figure 3 illustrates the lookup process using binary search by length. Given a content name /a/b/c/d/e/vr/mov, the hash search begins at level 4, where the search key corresponds to /a/b/c/d. \(k\)[1:4] represents a key composed of the first through the fourth components. Since the search result (N\({}_{3}\)) is found in the hash table, the next search proceeds at level 6 with the key /a/b/c/d/e/vr. However, this search fails, so the next search is conducted at level 5. The final search result, N\({}_{4}\), is a non-prefix node, meaning that its result face is inherited from its ancestor prefix. Thus, the face of N\({}_{4}\) is the same as the face of P\({}_{1}\).  
Figure 2. Hash table and a name lookup example.  
Note that for the binary search to work, the hash table must contain both prefix nodes (P\({}_{1}\) to P\({}_{4}\)) and non-prefix nodes (N\({}_{1}\) to N\({}_{5}\)). Unlike CCNx, which searches sequentially from the longest prefix downward, the binary search starts at the middle level. As a result, all non-prefix nodes must be stored in the hash table to enable further searches for a longer matching prefix. This method achieves O (log (\(r\))) hash table accesses where \(r\) represents the longest prefix length in the FIB.  
[PERSON] et al. discovered that not all non-prefix nodes are required for the next search. Instead, binary search can proceed as long as only specific non-prefix nodes, known as marker nodes, are stored in the hash table [28]. Figure 4 illustrates a name prefix trie with marker nodes indicated, along with the corresponding hash table reflecting this approach. In the figure, the N\({}_{4}\) node at level 5 is reached after confirming the match of N\({}_{3}\) at level 4 and passing through level 6. Since the result has already been obtained through the match of N\({}_{3}\), the match result for N\({}_{4}\) is unnecessary. Similarly, N\({}_{1}\) and N\({}_{2}\) nodes are not required in the hash table.
# 5G-MEC Testbeds for V2X Applications
## 3 Existing Testbeds and Implementations
### 5G V2X Testbeds
#### 3.2.2 5 GINFIRE IT-Av Automotive Testbed  
The 5 GINFIRE project includes various testbeds, one of which is the \"IT-AV automotive\" environment, which was developed for experimenting with V2X applications in 5G systems. MEC-based solutions have allowed the automotive sector to facilitate V2X communications and exchange vehicle-related information between nodes via the underlying communication network. In [42; 43], the authors present a novel V2X algorithm namedVulnerable Road User Safety (VRU-safe) that runs on the considered architecture. VRU-safe provides a low-complexity system, efficiency, and scope for identifying and predicting the hazardous events between vehicles and Vulnerable Road Users (VRUs). The performance and results have been evaluated in the real-time 5G testbed of \"IT-AV automotive\".
## 1 Introduction  
The rationale of retrograde filling material in endodontic surgery is to inhibit bacterial biofilm invasion and to prevent the invasion of bacterial toxins and byproducts into the surrounding periradicular tissues, in order to treat and prevent periapical pathology [1]. Retrograde filling is also expected to entomb any remaining bacteria in a way that would prevent bacterial invasion into the dentinal tubules, and that would eventually result in bacterial death [1]. However, studies have found that following endodontic surgery, bacterial biofilms may still colonize the root canals and also penetrate deep into the dentinal tubules [2].  
As part of modern endodontic surgery protocols, a variety of retrograde filling materials are used, such as intermediate restorative material (IRM) [3], mineral trioxide aggregate (MTA) [4], and Biodentine [4].  
This invasion of the bacterial biofilm manifests in the ability of viable bacteria to penetrate deep into the tubuli [5]. Thus, the depth of bacterial invasion into the dentinal tubules and their viability reflect the extent of the invasion. In a recent study, confocal laser scanning microscopy (CLSM) was used to assess the invasion of bacteria into the root apices following retrograde filling [2]. It was demonstrated that even in the presence of retrograde fillings, viable bacteria penetrated deep into the dentinal tubules [2]. However, in that study, only the bacteria were stained and evaluated using CLSM; the filling material penetration into the tubuli and its effect on the proliferating bacteria were not evaluated and remain unknown.  
Recently, in another study, CLSM was used to evaluate fluorescently labeled filling material penetration into the dentinal tubules [6]. Thus, it seems beneficial to use CLSM to simultaneously evaluate both the retrograde filling material interface with the dentinal walls and its penetration into the tubuli, and its effects on the invasion of bacteria at the apically prepared and filled root canal and dental tubules [2; 6; 7; 8]. This study enables a better understanding of the microbiological-pathological course after endodontic surgical procedures, and our null hypothesis is that the presence and type of a retrograde filling material will not affect bacterial invasion into the tubuli.  
Therefore, the objectives of the study were to assess the invasion of bacterial biofilms into the tubuli of retrofilled extracted human teeth, by measuring their depth of penetration and viability, and to assess the influence of different fluorescently labeled root-end filling materials on bacterial invasion using an established CLSM experimental model.
# Joint Iterative Decoding Design of Cooperative Downlink SCMA Systems
###### Abstract  
Sparse code multiple access (SCMA) has been a competitive multiple access candidate for future communication networks due to its superiority in spectrum efficiency and providing massive connectivity. However, cell edge users may suffer from great performance degradations due to signal attenuation. Therefore, a cooperative downlink SCMA system is proposed to improve transmission reliability. To the best of our knowledge, multiuser detection is still an open issue for this cooperative downlink SCMA system. To this end, we propose a joint iterative decoding design of the cooperative downlink SCMA system by using the joint factor graph stemming from direct and relay transmission. The closed form bit-error rate (BER) performance of the cooperative downlink SCMA system is also derived. Simulation results verify that the proposed cooperative downlink SCMA system performs better than the non-cooperative one.  
SCMA; cooperative; multiuser detection; joint factor graph; closed form BER
# Application of Molecularly Imprinted Polymers in the Analysis of Waters and Wastewaters
## 4 Applications of Molecularly Imprinted Polymers (MIPs)
### Molecularly Imprinted Polymers-Based Sensors  
In recent years, substantial attention has been paid to the application of MIPs in the field of chemical sensors. The MIP-based sensors are designed to be used for the detection of some pollutants, such as pesticides [30], pathogens, explosives, heavy metals [31], dyes, purification of chemical and biological reagent substances [32], industrial materials, and environmental pollutants analysis [33]. MIP-based sensors for different fields, such as clinical, bioanalytical [34; 35], process control, and environmental applications, represent other possible promising applications.  
A device comprising a recognition element and a transducer converting the chemical's information into a measurable signal is defined as a sensor itself. One can find even opinions that analytical techniques, such as fluid chromatography, mass spectrometry, and spectroscopic methods, will compete in the near future with such sensors. MIP-based sensors provide advantages, such as low production costs, easy storage, extended life, and the ability to be used under critical circumstances. The imprinted polymer is connected to a transducer to transform the response of MIP-based sensors into a measurable signal for such applications.  
The sensitivity of the resulting sensors is directly affected by the affinity for the analyte shown by the imprinted polymer. Impressed particles should, therefore, be used in micro- or nanometer sizes with a high volume-to-surface ratio. The integration of the polymer with a transducer is, thus, a critical aspect in the preparation of an MIP-based sensor.  
Figure 2: Number of molecularly imprinted polymers publications by writing “MIP” with “heavy metals”, “dyes”, “pesticides”, “pharmaceutical products” “bisphenols”, “phthalates”, and “personal care Products”, using PubMed on 15 September 2021 [29].
## 2 Three-Dimensional Ray-Tracing Model  
### Three-Dimensional Ray-Tracing and Acceleration Algorithm  
The ray-tracing method is widely used to study the propagation characteristics of wireless signals in a confined space [23; 24]. The ray-tracing method for tracking the path of wireless signals in roadways can be divided into three parts: wireless signal transmission, solving for the intersection point of the signal path with the reflection plane, and receiver receiving. During the transmission process, the wireless signal can undergo reflection and refraction, which can cause energy loss. A signal that has undergone more than three reflections can suffer severe energy loss. When calculating the field strength at the receiving point, it is suitable to select effective paths with three or fewer reflections for the calculations [17]. A flow chart of the 3D ray-tracing method is shown in Figure 1. Y is the input signal. The signal is decomposed into n signaling components, and the transmission paths of the n signaling components are traced. Then, the field strengths of signaling components that can reach the receiving end are superimposed to obtain the wireless signal strength P at the receiving end.  
The calculation of the vertical dimension is added to the 3D ray-tracing method, the established roadway model is more complete, and the obtained wireless signal transmission characteristics are more comprehensive. However, this method incurs an exponentially increasing amount of computation for simulation and actual application. Therefore, the spatial segmentation algorithm is added to the 3D ray-tracing algorithm to overcome the large computational complexity of the 3D ray-tracing algorithm.  
In the spatial segmentation-based acceleration algorithm, the roadway model is divided into several cubes, and each transmission path of the wireless signal is distributed in some of the divided cubes. When a transmission path of wireless signals reaches a certain cube, intersection detection must be performed only on the adjacent cubes. If the ray intersects the adjacent cube, the cube is regarded as valid, the occurrence of reflection or refraction is determined, and then the algorithm continues to track the next adjacent cube. If the ray does not intersect one adjacent cube, the other adjacent cube is checked again. As shown in Figure 2, the path of the wireless signal from point M to point N contains only cubes 1, 2, and 3. Therefore, it is only necessary to trace and calculate the effects of planes 11, 12, 21, 22, 31, and 32 on the strength and path of the ray. After the roadway space is divided, the tracing of the ray path does not have to cover all the roadway planes, which greatly improves the computational efficiency of the 3D ray-tracing method.
## 6 Conclusions  
This study shows the land subsidence monitoring results from April 2016 to April 2017 from Sentinel-1A InSAR, compared with GPS and leveling. The initial InSAR quality was improved by calibration using GPS measurements. Our monthly InSAR results indicated that land subsidence in the dry season contributed 60%-74% of the annual subsidence. This implies that more surface water should be supplied in the dry season than in the wet season to reduce groundwater pumping and land subsidence. Furthermore, InSAR identified two spots of severe subsidence not detected by leveling, highlighting the advantage of InSAR in showing detailed displacement information and in guiding government agencies to impose regulations to slow down newly developed subsidence.  
Both InSAR and leveling identified almost the same areal extent of significant subsidence (rate \(>\) 30 mm/a) from April 2016 to April 2017 in Yunlin (the two differ by only 2.6% and the resulting rates were consistent at 10 mm/a). This suggests that InSAR is a reliable tool for detecting the occurrence of significant subsidence, which is an indicator of the effectiveness of a subsidence-mitigation measure. The variations in the area of significant subsidence in the past seven years indicate that rainfall in dry seasons is the deciding factor for severe subsidence. Our analysis suggests that the newly opened Hushan Reservoir may potentially reduce land subsidence by supplying surface water to counter the shortage of rain and to reduce groundwater pumping during dry seasons and droughts.  
[PERSON] and [PERSON] initiated the idea in this study and wrote the manuscript, [PERSON], [PERSON], [PERSON] and [PERSON] provided data analyses and contributed with comments and suggestions to the writing of the manuscript.  
This study is supported by Ministry of Science and Technology, Taiwan, under Grants 106-2221-E-009-133-MY3, 107-2611-M-009-001 and Water Resource Agency, Department of Economics, Taiwan, under Grant MOEAWRA1060345.  
We thank ESA for providing the Sentinel-1A SAR images and [PERSON] and additional developers for maintaining the tool GMTSAR. This paper is published with the permission of the CEO, Geoscience Australia.  
The authors declare no conflict of interest.
## 2 Model Description, Datasets, and Methods
### Datasets and Methods  
Following CMIP6 protocols, we conducted a 500-year piControl simulation and a 150-year abrupt-4 \(\times\) CO\({}_{2}\) simulation [21]. Both simulations were conducted at a spatial resolution of 128 \(\times\) 256, and at a monthly resolution. This research focused on an analysis of variables that included NPP, surface air temperature (TAS), and precipitation (Pre). As a comparison, we downloaded monthly GPP, Ra, TAS, and Pre from CMIP6 models, and treated NPP as the difference between GPP and Ra. On the basis of data availability, we chose 22 CMIP6 models (Table S1) and applied their last 30-year outputs of the piControl simulation, and the first 149-year outputs of the abrupt-4 \(\times\) CO\({}_{2}\) simulation. All of the outputs were interpolated into the coarsest spatial resolution of 64 \(\times\) 128 among the 22 CMIP6 models and in the CAS-ESM2. The responses of annual total NPP, and the differences in TAS and Pre, were all represented as the averaged anomalies for the last 30 years of the 150 years in the abrupt-4 \(\times\) CO\({}_{2}\) simulation, relative to the 30-year averages in piControl. To detect the role of TAS and Pre in driving NPP, we used partial correlation and assessed the significance via Student's \(t\)-test.
# Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications
## 3 Smart Meter Technological Solutions in Europe and Projects for Their Implementation
### France  
In France, the energy provider ERDF has initiated the smart metering employment with respect to the overall upgrade of the traditional network to an intelligent one. The initial project, called \"Linky\", involved the installation of over 250,000 smart meters in homes in the greater Lyon area and was completed in 2011 [42]. After the success of the pilot program, the company decided to proceed with a massive smart meter roll-out. It is expected that by the end of 2020, 35 million smart meters will be installed, with a cost of around \(\mathbf{\upxi}\)5 and \(\mathbf{\upxi}\)6 billion [43; 44]. The smart meters to be used are/will be based on G1 and G3-PLC technology, with percentages of 20% and 80% respectively, whereas the technology for transmitting data from the concentrator to the control center is mainly GPRS [43; 45].
## 4. Study Regions of Interest
### Metropolitan Area of Boston  
In the case of Boston MA, the investigated ROI includes both the cities of Boston and Providence (Figure 12). Boston MA is characterized by a much colder climate than Atlanta, and it was selected in order to understand the behavior of the SUHI in a region surrounded by the sea and to analyze if and how such proximity affects the phenomenon.  
The _Detrended Rate Matrix_ (Figure 13) reveals that the LST again increases for the LC transitions from _Cultivated_ or _Forest_ to _Urbanized_. On the contrary, when the LC changes from _Urbanized_ to _Forest_, the LST decreases. Nevertheless, a comparison with Atlanta MA highlights that in the Boston MA, the LST increase due to urbanization is significantly lower, despite the values of the Permanence/Variation Index \(I_{v}\) being quite similar (except for the LC change from _Forest_ to _Urbanized_, which is lower for Boston). This is likely due to the effect of the Atlantic Ocean.  
Figure 12: Boston MA: LC situation in 1992 (**a**) and in 2011 (**b**). In red, the _Urbanized_ class, in light green, the _Cultivated_ class, in dark green, the _Forest_ and _Shrubland_ classes.  
Figure 13: Boston MA: _Detrended Rate Matrix_.
## 4 Experimental Results
### Two Partially  
The third experiment in which there were two eccentric circular flat-bottomed holes in the monitored aluminum, as shown in Figure 11a, was conducted. One of the holes, whose thickness loss was 30% and diameter was 30 mm, was in the center of the plate. The center coordinate of another hole was x = 260 mm, y = 260 mm, whose thickness loss was 50% and diameter was 40 mm. The monitored area was divided into \(60\times 60\) grids. The tomographic images reconstructed using the SIRT and our Equation (12) are shown in Figure 11b,c. From Figure 11b, it can be seen that the tomographic reconstruction results using the SIRT could not distinguish the defect of different thickness loss. By contrast, Figure 10c obtained using the method in this paper clearly shows all the thickness losses on the plate.  
The cross sections of Figure 11a with the corrosion depths are shown in Figure 12a,b. It can be seen that the depth estimation results of our method were better than SIRT in most cases, especially along the vertical line marked in Figure 11a. However, the depth estimation results of the thinnest thickness were worse than SIRT.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Grid Density**} & \multicolumn{2}{c}{**The Number of Grids**} & \multicolumn{2}{c}{**The Number of Grids**} & \multicolumn{2}{c}{**The Number of Grids**} \\  & **Covered by the Actual** & **Calculated by the SIRT** & **Calculated by the Proposed Method** \\ \hline \(20\times 20\) & 8 & 42 & 8 \\ \(40\times 40\) & 24 & 104 & 24 \\ \(60\times 60\) & 64 & 220 & 64 \\ \(80\times 80\) & 104 & 492 & 98 \\ \hline \hline \end{tabular}
\end{table}
Table 2: With different grid density, the number of grids covered by the actual corrosion area were compared to ones calculated respectively by SIRT and the proposed method.  
Figure 10: Tomographic reconstruction images for a 1.5 mm thick aluminum plate with two 20 mm diameter circular flat-bottomed holes with different grid density using the proposed method. Their thickness losses were respectively of 50% and 30% within the flaws. (**a**) The number of grids was \(20\times 20\), (**b**) the number of grids was \(40\times 40\), (**c**) the number of grids was \(60\times 60\), and (**d**) the number of grids was \(80\times 80\).
# Compression of Next-Generation Sequencing Data and of DNA Digital Files +
## 1 Introduction  
Next-Generation Sequencing technologies (NGS for short) have finally enabled DNA sequencing at a surprising high speed and low costs.  
Recently, the increase in memory and in network traffic used and caused by new sequenced biological data has deeply grown. Genomic projects such as HapMap and 1000 Genomes collected and described the genomes of 2504 individuals from 26 populations, and they contributed to the very large increase in memory and in network traffic occupied and used today by genomics data (see [1,2]).  
There is an increasing attention on the new research (and on the important results already obtained) in these areas. The scientific community has been thrilled by the large-scale sequencing of samples of DNA that has been gained in the last eight years. New hardware tools, analysis software, algorithms, private databases, and infrastructures have been recently built to support genomics (see [3,4]).  
In this paper, we analyze different approaches for compressing FASTQ, Sequence Alignment/Map (SAM), and binary SAM (BAM) files generated by Next-Generation Sequencing tools containing nucleotide sequences, extending and improving the research we presented in [5].  
Moreover, we present a simple but effective technique for the lossless compression of DNA sequences and experimentally evaluate its performances.  
This paper is organized as follows:Section 2 reviews some fundamental concepts: the DNA sequencing workflow and the file formats generated by the machines that are currently used for genomic sequencing and a review of recent data compression tools targeted to genomic compression.  
In Section 3, we discuss and evaluate the compression performances of two generic data compression tools, _gzip_ and _bzip2_, by confronting them with a specific data compression system designed specifically for FASTA genomic file compression: _Quip_ (developed by [PERSON] et al. in [PERSON] et al. (2018)).  
Section 4 presents a compression algorithm designed for one-dimensional textual files, which code a DNA sequence, and it experimentally assesses its performances. Section 5 discusses our conclusions and future research.