esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results
### Method Comparison  
Since the primary purpose of coarse registration is to provide an appropriate initial pose of the profile, thereby improving the speed of subsequent fine registration, it is necessary to compare the computation time of the method proposed in this paper with that of conventional registration methods, as shown in Table 1, where the TrICP algorithm is used for all the fine registrations. It can be observed that if only the circle equation is used for the coarse registration of translation and rotation by the orbital arc features, the random sample consensus (RANSAC) fitting algorithm [36; 37], which requires complex iterative calculation, is more effective than the least-squares (LS) fitting method in reducing the fine registration time. However, when considering the coarse registration method proposed in this paper (No. 6 in Table 2), which combines both circle and parabola equations, using simple LS fitting alone can achieve the shortest registration time. This may be attributed to the fact that under the influence of degradation phenomena such as surface ablation, wear, and aluminum deposition, the arc shape of the rail gradually deviates from the standard circular arc. Therefore, directly using the midpoint of the line connecting the centers of the upper and lower fitted arcs as the center point of the bore profile may not be accurate.  
To verify the precision of bore profile registration under the non-axisymmetric deformation scenario, a 5 mm thick interference block was installed on the surface of the left insulator inside the bore. The profile point clouds before and after registration are shown in Figure 11, which reveals that the profile after fine registration using the classical ICP algorithm is affected by the anomalous point cloud and exhibits an overall  
Figure 10: Bone straightness detection results: (**a**) side straightness; (**b**) arch straightness.  
Figure 9: Bone surface deformation detection results: (**a**) rail surface deformation; (**b**) insulator surface deformation.  
leftward shift. However, when the TrICP algorithm is employed, the anomalous offset is effectively eliminated.
## 3 Results
### Model Evaluation and Validation  
The spatial cross-validation produced results that are similar. The AUC of the SRC for model A and model B is 0.92 and 0.89, respectively (Figure 5a). The high AUC values of these two models and the model 1 indicate good compatibility of the models derived from the 7 selected landslide conditioning factors. It also indicates a high level of inclusivity where all the parameter classes are well represented in the three models. Model 1 and model A produced similar high SRC values, which indicates excellent model fitness. Although the 0.01 difference may not be statistically significant, a possible explanation for this finding is the higher distribution of landslides within zone A subset (58%) generated a model with the closest SRC value to that of model 1.  
The PRC for model A and model B also produced AUC values of 0.90 and 0.89, respectively, indicating that both models have similarly high predictive capability (Figure 5a). The similar AUC values show that the spatial partitioning method used is suitable for model validation. The AUC of model A is marginally better than model B. In 2020, this model was selected to be formally submitted to DBKL, the local council of Kuala Lumpur, to support decision-making on land use planning and development control.  
Figure 4: (**a**) Landslide susceptibility map of model 1, where all the landslide points in the 2014 inventory were used to generate the model. (**b**) Landslide susceptibility map of model A, where landslides in zone A were used as training dataset and landslides in zone B as test dataset. (**c**) Landslide susceptibility map of model B where landslides in zone B were used as training dataset and landslides in zone A as test dataset. (**d**) Landslides occurred in 2021 that were used for retrospective validation are plotted on model A.  
The retrospective validation of all the three models using the 122 landslide events that occurred in 2021 showed a slight increase in confidence level (Figure 4d). The AUC of the PRC for model 1, model A and model B is 0.93, 0.93, and 0.92, respectively (Figure 5b). The values proved to be marginally higher than the spatial partitioning method. Comparing the PRC to that of model 1, the same AUC values could be attributed to the small sample size of the 2021 landslide events and similar landslide distribution in both models. The revalidation using the retrospective method reaffirms the high predictive ability of all three landslide susceptibility models. This indicates that the product that was submitted to the city council is reliable for decision-making purposes.
## 4 Flow Velocity Analysis
### Comparison of Velocity Displacement of Different Aperture Jets  
From Figure 14, it is observed that the post-nozzle inclination angle of 35\({}^{\circ}\) only increases the nozzle diameter and the remaining conditions remain unchanged. The volume of the vortex area in the 3.5 mm aperture flow field diagram is smaller than that in the 2 mm aperture flow field diagram. The fluent data are post-processed by CFD-POST and further analyzed by the line chart.  
The left Figure 14a is the wall fluid velocity map at 20 mm from the wall, while the right image displays the velocity displacement map of the front nozzle jet outlet from the wall. Analyzing the wall velocity line chart of the two apertures in the left figure, it is evident that, apart from a brief instantaneous velocity fluctuation in the 3.5 mm aperture line chart at a horizontal distance of \(-\)150 mm from the coordinate origin, the overall velocity is higher than that of the 2 mm aperture. This fluctuation is limited in scope and has a momentary rebound effect. This phenomenon occurs because, with an increase in aperture size, the flow rate rises, leading to more jet impacts on the wall, causing a rebound effect on the forward jet. However, this effect is not significant in other areas.  
It can be observed from Figure 14b. that as the aperture size increases, the flow rate also increases. This results in the jet having greater initial kinetic energy and leads to an increase in the water volume in the tube. The increased water volume may not impede the jet ejection. The pre-jet line chart for a 3.5 mm aperture in the outlet area appears smoother compared to the pre-jet image for a 2 mm aperture. At 12 mm from the outlet, the velocity of the front jet decreases first and then increases, attributed to the velocity decrease caused by the vortex area's influence. However, the jet with a 3.5 mm aperture rebounded faster, indicating a smaller vortex area in the flow field with a 3.5 mm aperture. Similarly, there are two significant fluctuations at the outlet of the pre-jet with a 2 mm diameter, while the fluctuation at the same position for the 3.5 mm aperture is minimal. This can be explained by the fact that increasing the aperture from 2 mm to 3.5 mm reduces the volume of the vortex area in the pipeline, facilitating the flow of water-wrapped debris to the annulus for discharge outside the pipe.
# Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning
## 5 Conclusions  
In this study, traffic signal control based on a reinforcement learning algorithm was proposed to minimize traffic congestion. Early reinforcement learning-based signal control research focused on mathematical optimization, and when the model was applied to the road, excessively waiting vehicles and confused drivers could have occurred. Therefore, this study proposed a reinforcement learning-based traffic signal control model by applying the constraint that fixed the sequence of the pre-planned phases and provided a minimum green time.  
Simulations of the proposed model and the comparison model without constraints and fixed-time model were performed in two scenarios. The scenarios included multiple intersections, and the delay and the number of stops were compared. Compared with the fixed-time model, the reinforcement learning-based models showed excellent performance. Although the comparison model showed the best performance, the proposed model also showed ideal results. Unlike the comparison model, the proposed model will show the best performance when applied to real world intersections, because it calculates realistic signal patterns.  
Even if the simulation environment is based on reality, implementation will not be exactly the same. Therefore, it is necessary to test the model on real-world roads in future research. To this end, more constraints and data for safe road driving and simulations in various types of road networks will be required.  
Writing--original draft preparation, J.G.; visualization, M.L.; writing--review and editing, C.J.; methodology, Y.H. and J.K.; project administration, Y.K. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Road Traffic Authority grant funded by the Korea government [grant number 1325163906].  
Not applicable.  
The authors declare no conflict of interest.  
Figure 10: Traffic condition: (**a**) Comparison model; (**b**) Proposed model.
# Fast Implementation of NIST P-256 Elliptic Curve Cryptography on 8-Bit AVR Processor
## 3 Range Shifted Representation for Modular Multiplication
### Modular Multiplication on RSR  
Let  
\[X_{A}=x_{0}+x_{1}W+\cdots+x_{15}W^{15}, \tag{6}\]  
\[X_{B}=x_{16}+x_{17}W+\cdots+x_{31}W^{15}, \tag{7}\]  
\[Y_{A}=y_{0}+y_{1}W+\cdots+y_{15}W^{15}, \tag{8}\]  
\[Y_{B}=y_{16}+y_{17}W+\cdots+y_{31}W^{15}, \tag{9}\]  
where \(x_{i},y_{i}\in[0,2^{8}-1]\). Subsequently, \(X,Y,Z\) can be represented as  
\[X=X_{A}\cdot W^{-16}+X_{B}, \tag{10}\]  
\[Y=Y_{A}\cdot W^{-16}+Y_{B}, \tag{11}\]  
registers. Thus, the reduction process is divided into two 128-bit size of _reduction parts_. In _reduction part_ 1, the left half side of intermediate result is computed for a reduction of \(L_{A}\) and \(H_{B}\), whereas _reduction part_ 2 computes the right half side, as shown in Figure 1b. We rearrange the order of computation from \(L\to H\to M\) in Algorithm 2 to \(M\to L\to H\) as in [8]. Subsequently, we can directly use \(H_{B}\) without any memory access for the computation of \(H_{A}+H_{B}\) at Step 7, because it is kept in registers after the previous computation of \(H\) at Step 5. We can find the duplicated computations of \(L_{A}+L_{B}+H_{A}+H_{B}\) in Figure 1b, which can be computed in the _accumulation part_ in Algorithm 1, as mentioned in Section 3. We can avoid unnecessary memory access that is related with these computations by reusing the result of first computation in _reduction part_ 2. After the _accumulation part_, the result \((t_{0},\ldots,t_{15},carry_{2})\) of duplicated computation is stored at Step 9 and loaded in _reduction part_ 2. This _accumulation part_ corresponds to the Step 4, 9, 10, 11, and 12 in Algorithm 2, except the subtraction with \(M_{A}\) and \(M_{B}\) in Step 9 and 11, respectively. When comparing the number of load and store instructions for manipulating \(L_{A},L_{B},H_{A},H_{B}\), and \(T\) during each accumulation part in Algorithms 1 and 2 the former requires 80 load and 48 store instructions, whereas the latter only requires 48 load and 16 store instructions even when considering additional computation for a reduction of \(L_{A}\) and \(H_{B}\).
# On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks
###### Abstract  
This paper presents cooperative routing scheme to improve data reliability. The proposed protocol achieves its objective, however, at the cost of surplus energy consumption. Thus sink mobility is introduced to minimize the energy consumption cost of nodes as it directly collects data from the network nodes at minimized communication distance. We also present delay and energy optimized versions of our proposed RE-AEDG to further enhance its performance. Simulation results prove the effectiveness of our proposed RE-AEDG in terms of the selected performance matrices.  
underwater wireless sensor networks; routing protocol; cooperative communication; diversity; reliability; throughput efficiency; energy optimization; delay optimization; mobile sink; autonomous underwater vehicle  
15 June 201619  
consequence of these mentioned features we propose a routing protocol named as RE-AEDG. It is focused on magnifying the system reliability by improvement in throughput rate and successful packets delivery ratio at the surface sink. Moreover, in order to attain the stated objectives, a strategy known as cooperative routing is applied in RE-AEDG. This scheme is appropriate because it substantially boosts the spectrum utilization without placing any extra cost liability over the system.  
In cooperative routing, each in range node plays the role of a potential relay and eventually the destination receiver hears the packets from multiple transmitters. It combine them using some predefined diversity combining techniques e.g., Maximal Ratio Combining technique (MRC), Equal Ratio Combining technique (ERC) and others [4; 5]. However, these all advantages comes at the cost of faster battery power dissipation mechanism that leads towards an ill-favored state known as energy-hole problem.  
Mobile sink appears to alleviate this problem through network load balancing. Furthermore, it cuts short the communication paths through eliminating source and destination connection. Although the mobile sinks are highly desirable due to lots of advantages they pose in terms of network lifetime and throughput, their mobility mechanism causes a-lot of challenges in system designing process, moreover, complicates the efficient distributed data routing. Controlled sink mobility restricts the path selection frequency hence, reduces the protocol overhead caused by sink mobility.  
The rest of the paper is organized as follows. Section 2 describes related work; overview of counterpart schemes is given in Section 3; Section 4 presents underwater acoustic communication models; Section 5 presents system model; Section 6 discusses the proposed scheme; Section 7 deals with possible relay selection; Section 8 describes AUV trajectory and Section 9 defines the optimization models for the proposed scheme; Section 10 elaborates the applications of the proposed model; In Section 11, performance efficiency of the proposed scheme is validated via simulations. The hierarchy of paper is also presented in Figure 1.
# Recent Advances of Exciplex-Based White Organic Light-Emitting Diodes
## 2 Fundamental Concepts of Exciplex
### The Recognition of Exciplex  
Before 2012, the efficiency of exciplex-based OLEDs is usually poor and the generation of exciplexes is considered as a negative factor to the performance. For exciplexes used in WOLEDs, the broad emission band of exciplexes are generally exploited to achieve high CRIs [122; 123; 124]. After the work demonstrated by [PERSON] et al. in 2012 [111], the performance of exciplex-based OLEDs has been accelerated, since it is recognized that exciplexes intrinsically possess small singlet-triplet energy gap (\(\Delta_{\text{EST}}\approx\) 0-0.1 eV) and also allow high reverse intersystem crossing (RISC) efficiency [125; 126; 127].  
In OLEDs, when holes meet electrons, singlets and triplets will be formed with a ratio of 1: 3 due to the effect of spin statistics [128; 129; 130]. In the case of fluorescent emitters, singlets decay rapidly with the prompt nanoseconds fluorescence, whereas the radiative decay of triplets is spin forbidden [131; 132; 133]. In contrast, TADF emitters can also harvest triplets, because triplet excitons will be harnessed to produce the delayed fluorescence via an effective T\({}_{1}\)\(\rightarrow\)S\({}_{1}\) RISC process [134; 135; 136]. In general, the \(\Delta_{\text{EST}}\) < 0.2 eV is required for TADF molecular design, which can prohibit the nonradiative decay channels and improve the up-conversion [137]. Therefore, same as phosphors, the theoretical unity IQE could be achieved [138; 139; 140]. Aside from pure TADF materials, exciplexes allow TADF emission via RISC due to the intrinsically small \(\Delta_{\text{EST}}\), resulting in 100% IQE in exciplex-based OLEDs.  
To attain efficient exciplexes, there are some predictions or guidelines have been reported: (i) the exciplex system and its resulting photon energy are predictable by using the solution redox potentials of the constituting molecules; (ii) a fundamental issue for high-efficiency exciplex-based OLEDs is achieving the high RISC efficiency; (iii) donor as well as acceptor molecules should possess high T\({}_{1}\), which can not only be preferable for getting exciplex emitters with high fluorescence quantum yields, but also prohibit triplets quenching by confining the triplets of exciplexes from back energy transfer to donors and acceptors; (iv) high HOMO of donors and low LUMO of acceptors are significant; (v) an n-type material consisting of strong electron-withdrawing units and with low-lying LUMO energy is important; (vi) the balanced holes and electrons in the donor/acceptor heterojunction is desirable; (vii) the enhancement of the intermolecular contact can improve the light-emitting efficiency; and (viii) a broad exciton recombination zone can enhance the exciton utilization efficiency [111; 125; 126; 127; 141; 142; 143; 144; 145].
# Changes of Gait Patterns after Correction of Refractive Error in the Elderly with Cataracts
## 1 Introduction
We reported that astigmatic blur had negative effects on postural control [15], and that when the hyperopic refractive error condition was induced, despite maintaining visual acuity without glasses of power 1.0 or higher, the participants reported a decrease in postural stability compared to when their condition was fully corrected [16]. Moreover, in an earlier study, we had found that postural stability was significantly improved compared to before wearing correction glasses [17]. Based on our previous research results, we considered that postural stability studies analyzed in a static state should be further expanded to gait analysis studies in order to analyze whether the correction of refractive errors can be used as an effective optical intervention for fall prevention. We previously studied changes in gait patterns under experimental conditions wherein different types of refractive errors were induced in young adult subjects [18]. Although our recent research yielded meaningful results, the results were obtained under limited experimental conditions. In addition, the results of a study that included healthy young adult subjects with low risk of falls were limited to application to the elderly population. Therefore, in the present study, we attempted to determine whether wearing glasses for the correction of distance visual acuity can have a positive effect on gait patterns among elderly subjects who have not worn correction glasses during the past year.
## 1 Introduction  
Osteoarthritis (OA) is a debilitating progressive disease affecting the joints that could be divided into two types: primary and secondary. Both types involved the degeneration of cartilage in joints; primary OA is mostly caused by wear and tear on joints that becomes increasingly apparent as people age, while specific triggers resulting in cartilage breakdown cause secondary OA to manifest, such as genetics [1], obesity [2], inflammation [3], etc.  
Knee osteoarthritis (KOA) has a higher incidence rate compared to other OA types, which marks its importance [4]. A recent study in Belgium, conducted over a period of 20 years (1996-2015), showed that there was an increasing prevalence of KOA, which called for the need to prioritize improvement towards KOA care [5]. As for today, there is no disease-ameliorating agent that could cure KOA, and the current treatment would only slow down the disease progression and other inflammatory conditions [6].  
Hyaluronic acid (HA) is a compound that is naturally produced by the body and one of the main components of synovial fluid, responsible for reducing friction during synovial joints movement [7]. Intra-articular (IA) HA injections yield positive outcomes. Therefore, the administration of HA to KOA patients is recommended when other pharmacologic treatments, such as glucocorticoidoid injections, fail to show results [8].  
Mesenchymal stem cells (MSCs) therapy for KOA has been increasingly considered due to its unique properties, such as inflammation site homing, immune suppression, self-renewal and the restoration of cartilage tissue, making it a promising candidate for a gradual KOA treatment [9]. MSCs are multipotent stromal cells that could perform multiple functions due to their capacity to differentiate into specific cell types, such as the abundant secretion of soluble growth factors and cytokines. Moreover, MSCs can migrate to injury and inflammation sites plus exert beneficial effects through immunomodulatory, antifibrosis, antioxidation and anti-apoptosis effects [10; 11; 12].  
Combining MSCs with HA has been shown to result in synergistic effects that are beneficial for treating KOA. Outcomes like an increase in the osteogenic differentiation capability [13], improved inflammation site homing [14] and enhanced cartilage repair [15] have been reported.  
The aim of this paper was to investigate the effect of MSCs--particularly, human umbilical cord-derived MSCs (hUC-MSCs) and HA combinatorial treatment for KOA. Furthermore, we tried to examine whether HA affected the expression of cytokines in hUC-MSCs and if that, in turn, had beneficial impacts on the treatment function.
## 2 Methods
### Validation Procedures
#### 2.3.1 Unit and Integration Tests  
The features that we need for a unit test are:  
* Specificity, to check a defined section of the code.  
Figure 4: Development cycle diagram.  
* Orthogonality, to go through the same code only once.
* Coverage, to test all the features in the developed code.
* Independence, to have the same start and end state of the program.
* Automation, to be executed automatically.  
The unit tests translate a functional requirement to the code, adding sanity checks to small portions of the code. The integration tests consist of calling different routines of the code with a given input (e.g., mesh structure, FEM matrix...) asserting the expected output of the routine. For both, we have used pFUnit [29; 30], which allows us to add automatic tests in MPI and OpenMP (used extensively in the code [31]).  
We show an example of the application of unit and integration tests with pFUnit in Code 1. Note that the snippet contains Fortran free-format code, which is the language used to develop our code. There, we import the module of pFUnit with USE pfunit_mod, and we test the finiteGrid module, which is the part of the code devoted to managing the grid. We construct a mockup grid of \(2\times 2\), and we have designed the cell numbering in a way that the second domain should be in the second row and the first column. We test those numbers with @assertEqual and, if true, we destruct the mockup grid previously created.  
```
1 MODULEtest_finiteGrid
2 IMPLICITNONE
3 CONTAINS
4@test
5 SUBROUTINEtest_get2 DLocation
6 USEfiniteGrid
7 USEpfunit_mod
8 TYPE(GridStruct)::testGrid
9 INTEGER::row, col, cell, m, n
10m=2;n=2;cell=2
11 CALLgridConstructor(m,n,testGrid)
12 CALLget2 DLocation(testGrid,cell,row,col)
13@assertEqual(2,row)
14@assertEqual(1,col)
15 CALLgridDestructor(testGrid)
16 ENDSUBROUTINEtest_get2 DLocation
```  
Code 1: Snippet for unit and integration tests in the code.  
Figure 5: Unit test for a piece of code.