esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Inlet and Outlet Effects
The effect of velocity profile formation in the inlet region of CC is clearly visualized in Figure 10c. The inlet/outlet regions are less than 10 mm long, and are marked with red dashed lines in Figure 10a. Within the working space of CC, the velocity magnitude along the axis placed in the middle of the height of CC changes by only about 10%, tending asymptotically to the value of 0.0086 m/s (dashed blue line in Figure 10a). Figure 9: Dynamic dye profiles experimentally determined during the flow of fluid from the reservoirs to the culture chambers: (**a**) photo from a stereoscopic microscope at the inlet, (**b**) normalized inlet profiles determined from the photo, (**c**) photo from a stereoscopic microscope taken in the middle of the CC length, and (**d**) normalized middle-length profiles determined from the photo. X, Y—dimensionless distances.
###### Abstract  
This paper presents the results of testing the insulation performance of geopolymers based on fly ashes with the addition of waste broken glass. The waste glass was dried and ground to a maximum of 1 mm grain size. The proportions of broken glass in the total binder's mass were 0%, 10%, 20%, and 30%. Sodium hydroxide and sodium silicate were the activators of the alkaline reaction. The obtained geopolymer materials were characterised by determining the basic physico-mechanical properties. The chemical composition, density, and thermal conductivity coefficient were determined. The mechanical performance, including compressive and flexural strength, was investigated after 28 days of curing. The morphological analysis was also carried out using microphotographs obtained from optical and scanning microscopes. A significant effect of the waste glass on the tested geopolymers' mechanical performance was observed. Proportions of 10% and 20% broken glass in the binder led to more than a four-fold increase in the compressive strength and a two-fold increase in the flexural strength compared to the geopolymer without the waste glass. All tested geopolymers had excellent insulation ability compared to the reference mortar (more than 80% higher than cement mortar). However, the problem is potential alkali-silica reaction, which can occur when the waste glass content is high.  
geopolymers; durability; recycling; waste broken glass Article]Physico-Mechanical Properties of Geopolymers Based on Fly Ashes and Waste Broken Glass][PERSON], [PERSON] [] and [PERSON] []  
Faculty of Civil and Environmental Engineering, West Pomeranian University of Technology in Szczecin, al. Pistatow 50a, 70-311 Szczecin, Poland, [EMAIL_ADDRESS] (K.C.); [EMAIL_ADDRESS] (S.)
# Extended Spatial-Index LED Modulation for Optical MIMO-OFDM Wireless Communication
## 4 Conclusions  
The extended spatial-index LED (ESI-LED) modulation scheme for the optical MIMO-OFDM was proposed in this paper. In the proposed ESI, there are no restrictions on the number of LEDs (i.e., any number of LEDs greater than or equal three can be used). Moreover, the proposed ESI is spectrally efficient optical wireless modulation scheme, where its obtainable data rates are semi-nonlinearly increased with \(n_{t}\) (LEDs number). The main ESI connotation is to use variable power allocations with a changeable LED indices to convey information, whereas the LED number that is used for data conveyance is changed from the state where only two LED indices are selected to the state where multiple LED indices are selected. At the same time, a variable power allocation of the OFDM real competent is exploited over the same active LED indices. This gives an extra degree of freedom to expand the LED indices spatial domain, which improves the SE of the ESI over GLIM and the FGIS. Moreover, a simple and efficient MAP estimator was proposed for the ESI to cope with the variation on the channel paths (LEDs) number and the real part power allocation. Furthermore, the proposed ESI computational complexity is much better than the GLIM computational complexity especially at  
Figure 7: Computational complexity of the proposed ESI compared with the CC of the FGIS [33] and the GLIM [31] at different achievable data rates: (**a**) \(log_{2}(M)\) (zero spatial bits); (**b**) \(log_{2}(M)+2\) (two spatial bits); (**c**) \(log_{2}(M)+4\) (four spatial bits) and (**d**) \(log_{2}(M)+6\) (six spatial bits).  
the high value of spatial bits. Finally, the simulation results illustrate the ESI efficiency, as it achieves up to 5.2 and 3.7 dB SNR saving compared to the GLIM and the FGIS systems, respectively.  
Conceptualization, H.S.H.; Formal analysis, H.S.H. and M.F.; Funding acquisition, M.F.; Investigation, H.S.H., M.H. and M.F.; Methodology, H.S.H., M.H. and M.F.; Project administration, M.F.; Resources, H.S.H. and M.F.; Software, H.S.H. and M.H.; Supervision, H.S.H.; Validation, H.S.H. and M.F.; Visualization, H.S.H., M.H. and M.F.; Writing--original draft, M.H.; Writing--review & editing, H.S.H., M.F. All authors have read and agreed to the published version of the manuscript.  
This research is funding from the Deanship of Scientific Research at King Khalid University through General Research Project under grant number (R.G.PI/143/40).  
The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through General Research Project under grant number (R.G.PI/143/40).  
The authors declare no conflict of interest.
# Tightly-Coupled GNSS/Vision Using a Sky-Pointing Camera for Vehicle Navigation in Urban Areas
## 4 Camera-Based Non-Line-Of-Sight Effect Mitigation  
This section presents the vision-based method we used to reduce and mitigate the NLOS GNSS effects.
# Priority of Emergency Vehicle Dynamic Right-Of-Way Control Method in Networked Environment
###### Abstract
The current priority for the roadway is mainly focused on the priority of public transport vehicles, which are mainly divided into exclusive right-of-way and intermittent bus lanes, and most do not consider the impact on regular traffic. In summary, most analyses focused on priority control within EVs intersections, with equal spatial right-of-way between EVs and CVs within the spatial extent of the road section. However, there is a lack of research regarding an EV's spatial right-of-way priority control on road sections. Therefore, it is necessary to propose a priority dynamic right-of-way control method for emergency vehicles. Specifically, this paper set a movable, physical, and functional area ahead of the EVs that prohibits CVs from entering or requesting to \begin{table}
\begin{tabular}{c c c} \hline \hline
**EV Priority Control** & **Reference** & **Method** \\ \hline right-of-way time priority & [1–7; 6; 1; 2; 3; 4; 5; 6; 7] & Right-Of-Way time priority has evolved from the early days of roadside devices collecting information to the current developments in networked vehicle technology and communications technology, which realize real-time information interactions between CV and signal lights. \\ \hline right-of-way space priority & [8; 9; 10] & Right-Of-Way space priority is mostly controlled at the intersection entrance road, and involves the use of variable message signs to guide the movement of vehicles, clear lanes with variable guidance, and the use of vehicle–road collaboration technology to guide vehicle operations. \\ \hline road section priority & [11; 12; 13; 14; 15] & Most of the current roadway priority control targets are bus vehicles; special control methods are used to give priority to bus vehicles on road sections, and only a small number of methods consider the operational efficiency of regular traffic. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The different priority control methods. alter lanes and reduces the impact of CVs on EV operation, thus reflecting its priority right-of-way characteristics on the road section. Unlike traditional right-of-way priority, through our method, EVs do not fully occupy an entire lane of traffic, which minimizes the impact on CVs while giving priority to EVs.
## 3 Materials and Methods
### Feature Transformation
#### 3.2.3 Tree Creation  
Since both used patent classifications comprise a hierarchically organized taxonomy, each can be represented by a tree. By additionally inserting a root node, the trees of all assigned class codes are unified in one tree structured graph (see Figure 3), which facilitates the computing of the distance between the structured codes of CPC/IPC taxonomy using the tree-edit-distance [33].  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Class Name** & \multicolumn{2}{c}{**\# of Patents**} & \multicolumn{2}{c}{**\# of CPC Codes**} & \multicolumn{2}{c}{**\# of IPC Codes**} \\  & **Training** & **Testing** & **Training** & **Testing** & **Training** & **Testing** \\ \hline Imaging & 205 & 30 & 1380 & 129 & 838 & 84 \\ Implants and prostheses & 205 & 15 & 1659 & 78 & 732 & 33 \\ Telemedicine & 205 & 2 & 1064 & 5 & 827 & 6 \\ Surgical intervention & 205 & 23 & 1351 & 98 & 805 & 59 \\ In-vitro diagnostics & 205 & 6 & 922 & 18 & 1175 & 18 \\ Special therapy systems & 205 & 18 & 1190 & 67 & 1024 & 50 \\ \hline Total & 1230 & 94 & 7566 & 395 & 5401 & 250 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Patent data for training and testing assigned into six classes of innovative biomedical devices.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Level** & **Symbol** & **Classification and Description** \\ \hline Section & A & Human necessities \\ Class & A61 & Medical or veterinary science; hygiene \\ Subclass & A61B & diagnosis; surgery; identification \\ Main Group & A61B 5/00 & Detecting, measuring or recording for \\  & & diagnostic purposes; identification of persons \\ Subgroup & (A61B 5/00 48) & • Detecting, measuring or recording by \\ Subgroup & A61B 5/00 55 & •  
The string representations of the IPC/CPC codes have to be parsed to build the required tree. However, a full deduction of the hierarchy as given in official CPC definition [34] solely from the code strings is not possible, because the different subgroup levels are not represented in the code strings. Thus, the resulting tree parsed from the code string is only an approximation of the actual defined structure, which is created by discarding eventually existing intermediate subgroup levels between the given code and the main group. For example, a patent is marked with code A61B5/0055. Since this is according to the official CPC definition a 2 nd-level subgroup (see Table 2), the string parser discards one intermediate subgroup. Nevertheless, the parsed tree carries as much information as possible to be extracted solely from the string representation of a CPC/IPC code.
# Machine Learning-Based 3D Soil Layer Reconstruction in Foundation Pit Engineering
## 3 Data Enhancement Algorithm of Soil Layers  
### Common Patterns of Soil Layer Distribution  
Over time, the occurrence of events such as crustal movement, weathering erosion, sedimentary discontinuities, and paleontological evolution significantly alters subsurface conditions. Based on an extensive review of geological data, we identified that soil layers can be primarily categorized into three types.  
The first type is a continuous soil layer. This type of soil layer exhibits uninterrupted distribution, with no missing or disrupted layers, as illustrated in Figure 5a.  
The second type is a hiatus soil layer. Due to the movement of the crust, the stratum lacks one or more layers of soil. It is usually in the shape of an inverted triangle. The remaining layers are still continuous. Figure 5b shows this situation.  
The third type is a fault soil layer. Part of the crustal subsidence often leads to the formation of such a soil layer. The soil layer has a significant displacement fracture at a certain position, as depicted in Figure 5c.  
Figure 4: Soil layer visualization process.  
In a continuous soil layer, the interface between the two types of soil also rarely appears in the form of a plane. Instead, they typically are curved surfaces. In addition to continuous soil layers, geological processes have also formed soil layers with hiatuses and faults. Based on this information, we simulated the formation process of real soil layers on Earth. Additionally, we designed a soil layer generation algorithm capable of generating data for the aforementioned three types of soil layers.
## 2 Literature Review
These strategies are commonly referred to as load-aware strategies (LAS). In [49], authors suggested a LAS-based adaptive strategy for reducing cumulative energy consumption, which varies over time due to non-uniform data traffic. Both complete channel state information (CSI) and incomplete CSI are used to drive switch-off strategies. In [50], researchers introduced a load-aware approach that optimizes a utility function considering interference and throughput. The model employs progressive and heuristic methodologies to dynamically deactivate unnecessary BSs, but it is worth mentioning that both [49; 50] focus on the fixed data traffic profile. Though the RSM- and LSM-based algorithms have fewer computational complexities and a comparatively low operational cost, these techniques lack adaptability to unpredictable factors such as the distance between small-cell and macro BSs relative to mobile users or traffic conditions in actual wireless networks [21; 51]. Nonetheless, RSM-based algorithms harm the overall network energy efficiency rather than benefit, as the amount of energy efficiency achieved is insufficient to compensate for the decrease in average throughput and coverage [22]. The proposed dynamic DOSS considers realistic network models; accounts for random spatial network impact, user density variation, and diverse traffic conditions; and mitigates negative QoS impacts from sleep mechanisms. It provides computationally efficient solutions for energy-efficient HetNets while adhering to QoS requirements. These solutions are derived through stochastic geometry, optimizing the balance between energy efficiency and average throughput while meeting coverage probability and average wake-up time delay constraints.
# Neuroimaging of Pediatric Cerebellum in Inherited Neurodegenerative Diseases
## 2 Mitochondrial Disorders  
In MRI studies of several mitochondrial disorders, the cerebellum appears involved. In many instances, however, cerebellar ataxia is not the most characterizing feature. Patients with mitochondrial disease often present a combination of abnormalities: signal abnormalities in the basal ganglia, or the brainstem, or cerebellum; the pattern of distribution, however, is fairly characteristic and may suggest a specific disorder [43].  
Isolated or predominant cerebellar volume loss due to cerebellar hypoplasia or, more frequently, progressive cerebellar atrophy are common neuroradiological features in children with various mitochondrial disorders: complex I, complex II, complex III and complex IV deficiency, isolated or combined, multiple respiratory chain defects (RCDs) and partial coenzyme Q10 deficiency [44] (Figure 8).  
Coenzyme Q10 transfers electrons along the respiratory chain; among other clinical manifestations, Coenzyme Q10 deficiency has been associated with cerebellar ataxia [45]; 13 genes encode proteins involved in its biosynthesis, but only mutations in 10 genes have been associated with diseases. One of the most well-documented is mutations in the COQ8A gene (formerly ADCK3). In these patients, cerebellar atrophy is an almost universal finding [46].  
In POLG related disorders and myoclonic epilepsy with ragged red fibers (MERRF), white matter abnormalities and changes in the dentate nucleus can be observed. The latter has also been reported in Kearns-Sayre syndrome (KSS) [43].  
Figure 7: Ataxia telangiectasia (AT). Brain MRI scan of a 10-year-old girl. MR images reveal severe atrophy of the cerebellar hemispheres, decreased thickness of the cortex of superior cerebellar hemispheres, and hypoplasia of inferior vermis.  
In other mitochondrial disorders, the cerebellum is the main target of the disease, sometimes in combination with brainstem or supratentorial abnormalities. In children, the most common mitochondrial disorder is Leigh's syndrome, characterized by cerebellar atrophy with lesions in the dentate nuclei and lesions in the brainstem (periaqueductal area, pontene) tegmentum and medulla oblongata), lesions in the basal ganglia, particularly the posterior part of the putamen. In mitochondrial neurogastrointestinal encephalopathyopathy (MNGIE), cerebral atrophy and cerebellar volume loss may be associated with leukoencephalopathy. Lesions in MELAS are extensive cortical and subcortical hyperintensities in T2-w.i. in supra and infratentorial compartments compatible with stroke-like lesions but not confined to vascular territories. They do not evolve as ischemic infarcts and may initially completely regress. Progressive cerebellar atrophy is a characterizing feature [44]. In an unsuspected adolescent with a first stroke-like episode, observation at MRI of cerebellar atrophy should suggest the possibility of MELAS.
# Review on Retrospective Procedures to Correct Retinal Motion Artefacts in OCT Imaging
## 1 Introduction
Moreover, little information was given on validation techniques, which are one of the major concerns on OCT registration due to the lack of a ground truth for the retinal structure. In this work, a broader and extensive review focused on retrospective procedures to correct retinal motion, covering 38 publications, is provided. The pre-processing, registration, and validation techniques used in these publications, whenever provided, are described and discussed. The remainder of the paper is organized as follows. In Section 2, the retinal motion that affects OCT imaging is explained. Section 3 describes the literature search methodology and summarizes the topics that are tackled in the survey, namely the motion correction approaches, pre-processing, and validation techniques. The retrospective procedures used to correct retinal motion in OCT volumes are reviewed in Section 4. Section 5 provides a discussion on the reviewed approaches, followed by the conclusions in Section 6.
## 3 Multiplication Methods over \(GF(2^{m})\) on 8-bit AVR MCUs  
Until now, many studies have been conducted for optimizing \(BF\) multiplication's performance on 8-bit AVR platforms [2, 3, 4, 5, 6, 7, 8]. They can be categorized into two main approaches: LookUp Table-based (LUT-based) approaches [2, 3, 4, 5] and Block-Comb-based (BC-based) approaches [6, 7, 8, 9]. Table 1 summarizes the existing result results, and the details will be explained in the following Sections 3.1 and 3.2. Because the count of accessible registers is constrained on 8-bit AVR, many memory accesses take place. Namely, among 32 general-purpose registers, only 26 are accessible for calculating a \(BF\) multiplication, without six registers for a memory address pointer. For instance, at least a set of 64 registers are necessary for maintaining the total part of a multiplier, a multiplicand, and a result of multiplication. However, due to the limited number of available registers, only certain parts of the operands can be kept in the registers. Thus, this limitation generates a huge number of redundant memory accesses. Therefore, on 8-bit AVR, the major goal of existing researches on binary field multiplication methods is minimizing redundant memory accesses by optimizing the use of the available registers.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Technique** & **Application** & **Fields** & **Timing (\(cc\))** & **SCA Resistance** \\ \hline [PERSON] et al. [3] & LookUp-Table (4-bit wise) & \(ECC\) & \(GF(2^{163})\) & 19,670 & SPA, TA \\ [PERSON] et al. [4] & LookUp-Table (4-bit wise) & \(ECC\) & \(GF(2^{163})\) & 4508 & SPA, TA \\ [PERSON] et al. [6] & Block-Comb & \(ECC\) & \(GF(2^{29})\) & 9511 & none \\ [PERSON] et al. [7] & Unbalanced Block-Comb & \(ECC\) & \(GF(2^{163})\) & 4346 & none \\ [PERSON] et al. [8] & Karatsuba Block-Comb & \(ECC\) & \(GF(2^{163})\) & 3274 & none \\ [PERSON] et al. [8] & Constant Karatsuba Block-Comb & \(ECC\) & \(GF(2^{163})\) & 5005 & TA \\ [PERSON] et al. [9] & Enhanced Karatsuba Block-Comb & \(ECC\) & \(GF(2^{233})\) & 6896 & none \\ [PERSON] et al. [11, 15] & Masked Block-Comb & \(GCM\) & \(GF(2^{128})\) & 14,445 & TA \\ [PERSON] et al. [10] & Block-Comb with Dummy XOR and \(ILA\) & \(GCM\) & \(GF(2^{128})\) & 5675 & SPA, TA \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of existing multiplication methods over binary fields on 8-bit AVR microcontrollers (MCUs) (\(GCM\) and \(ECC\) are mean Galois/Counter mode and elliptic curve cryptosystem, respectively).
## 3 Case Studies
### From Survivable to Resilient Topologies: A Real-World Network
With this objective function and these constraints in AGX, we were able to find the topology shown in Figure 5(b) that presents a maximum Wiener impact value of 34 (against the original 181 value of the original topology). We can also check in Table 5 that all the other analyzed invariants were improved when compared to the original topology. To better understand the effects of minimizing the node Wiener impact on the topological parameters, a worst case analysis was performed for the same topologies analyzed in Table 5. For that end, for each topology, the node maximizing the Wiener impact was removed from the topology, and the invariants were computed again. The results are presented in Table 6. Notice that, whereas the diameter of the original topology has increased from 5 to 9 after the worst case node failure, the diameter of both the improved topologies has only increased from 5 to 6. Moreover, the average distance of these improved topologies increases much less (11.68% for the topology shown in Figure 5(a) and 5.43% for the one shown in Figure 5(b)) than the average distance of the original topology (25%). These results are graphically presented in Figure 7. In addition, this figure shows that the diameter and the average distance invariants from the optimized topology of Figure 5(b) are similar to the topology of Figure 5(a), but without the need for adding two additional edges. When we optimize the original graph, the output is an improved node interconnection solution that better suits the defined constraints and objective functions. A final step to implement the solution in real networks is to map the nodes from the optimized solution into the original node geographical distribution. This is another problem that can also be tackled with the guidance of graph invariants. For example, a heuristics may sort the original geographical nodes by traffic load or population aspects and map them to the nodes in the optimized solution that have the greater values for some specific graph invariant (e.g., degree or Wiener impact). In addition, this heuristics has to ensure that neighbors in the optimized solution are close in terms of geographic distance to minimize the cabling costs. Figure 6: Optimization of topology shown in Figure 5: (**a**) addition of two edges; and (**b**) minimization of the maximum Wiener impact.