esa-sceva/satcom-chunk-collection huggingface dataset:
# The Impact of Using Mobile Phones on Gait Characteristics: A Narrative Review
## 3 The Impacts of Using a Mobile Phone on Gait Characteristics  
Gait kinematics were well examined among the included studies and the results of most studies were consistent. It could be concluded that using a mobile phone can significantly decrease gait velocity, cadence and step length while significantly increasing step width, step time and double support time. It was supposed that using a mobile phone would increase cognitive load, which would in turn affect gait control while walking. It is becoming increasingly clear that cognitive resources play a crucial role in maintaining postural control when walking [4; 41] and that walking is an active movement that requires the effective integration of information from the visual, vestibular and proprioceptive systems [42; 43]. Using a mobile phone while walking is a dual-task paradigm. Participants were asked to perform not only a cognitive task, but also a walking task. It was found that using a mobile phone while walking increases the cognitive load of the walker in many aspects (e.g., attention, memory and executive control).  
[PERSON] et al. reported that texting on a mobile phone while walking can increase stride length. This was inconsistent with the other studies [13; 14; 18; 20; 24; 28; 31; 34; 37; 38], but they did not mention it in their discussion. The reason could be that [PERSON] et al. used a treadmill rather than overground walking [13; 14; 18; 20; 24; 28; 31; 34; 37; 38], which should be taken into consideration.  
[PERSON] et al. reported that using a mobile phone while walking can increase cadence [23], which seems to be inconsistent with previous studies [12; 13; 17; 18; 20; 22; 26; 30; 31; 34; 36; 37; 38]. However, cadence results in this study were actually normalized using the individualized gait velocity. The authors suggested that cadence and stride length should be normalized because a decrease in these two parameters often directly results from a reduction in gait velocity. Normalization could thus be considered more appropriate for gait speed-dependent outcomes.  
Kinetics and EMG data were rarely discussed within this field. Increased lateral plantar pressure and the co-contraction of the tibialis anterior and gastrocnemius lateralis were found when walking while using a phone [34].
## Materials and Methods
### Data Collection
#### 2.2.2 Sentinel-2 Satellite Multispectral Image
Level-1B data have been processed by a series of procedures including dark signal correction, non-uniform pixel response correction, crosstalk correction, defect pixel recognition, deconvolution and noise reduction. Level-1C data can be obtained using level-1B data through radiation correction, geometric correction based on orthophoto correction, sub-pixel precision level spatial registration and splicing. ESA makes SNAP software specifically for Sentinel satellites. Two plug-ins, Sen2 Cor and Sen2 Three, are the most important parts of the SNAP software. Sen2 Cor is used for atmospheric correction and cloud removal of the image. With SNAP, a processed standard reflectivity image of Sentinel-2A has been obtained at the spatial resolution of 10m. The image was produced at Sept. 22 th, 2017 and a subset including the UAV flight area was gotten with the size of 2000 * 2000 Sentinel-2 image pixels, shown as Figure 2.
# Spatial Assessment and Prediction of Urbanization in Maseru Using Earth Observation Data
## 3 Results
### Model Performance Validation  
We used the validation module in MOLUSCE to validate the 2019 LULC based on the simulated map derived from the 2008 and 2013 LULC maps. These two years were selected based on the high classification accuracy achieved. The validation model calculated the percentage of correctness, the overall kappa, the kappa histogram and the kappa location. Our results from the validation module are shown in Table 5. They show high values that made the model suitable for predicting LULC changes in the study area.
## 3 Validation of Effectiveness
### Ground Motion Simulation of the 1994 Northridge Earthquake
In order to measure the simulation accuracy of the improved method, the simulation misfit is defined as the average logarithm of the ratio of the simulated response spectrum to the response spectrum of the observed record over all stations in this study. The simulation misfit of the ground motion of the Northridge earthquake in the NS, EW, and UD directions is shown in Figure 10.  
Figure 6: Simulation results of the ATB station. (The comparisons of acceleration time histories are shown in the top row, the comparisons of acceleration response spectra are shown in the middle row, and the comparisons of displacement amplitude spectra are shown in the bottom row. The simulation results in the NS, EW, and UD directions are shown from left to right. The black line represents the observed record, the red line represents the GMPE, the yellow line represents the simulation result with the constant rise time when the subfault division number is 9 \(\times\) 10, the green line represents the simulation result with the modified rise time expression when the subfault division number is 9 \(\times\) 10, the brown line represents the simulation result with the constant rise time when the subfault division number is 36 \(\times\) 40, and the blue line represents the simulation result with the modified rise time expression when the subfault division number is 36 \(\times\) 40). The results show that when the subfault division number is 9 \(\times\) 10, the simulation accuracy is improved in the period range longer than 0.4 s after using the improved method. In the period range of 0.01 s to 6 s, the misfit values of the NS, EW, and UD components using the improved method are within \(\pm\)0.35, \(\pm\)0.3, and \(\pm\)0.25, respectively. When the subfault division number is 36 \(\times\) 40, the simulation accuracy is improved in the period range longer than 0.2 s after using the improved method. In the period range of 0.01 s to 6 s, the misfit values of the NS, EW, and UD components using the improved method are within \(\pm\)0.5, \(\pm\)0.35, and \(\pm\)0.45, respectively. Overall, the simulation accuracy is higher when the subfault division number is 9 \(\times\) 10 than when the subfault division number is 36 \(\times\) 40.
## 7 Conclusions  
This paper introduces the problem of unreachable nodes communicating with each other arising from the transition from the centralized to the decentralized network phase. The proposed solution mentioned in the related work for the centralized network is incompatible with the decentralized network due to the need for additional trusted third-party servers. We propose a communication scheme for unreachable nodes in decentralized networks to solve this problem. The solution does not rely on third-party trusted institutions such as CA institutes and centralized cloud platforms, and does not rely on the IP addresses of nodes when finding nodes, and can choose to establish secure direct or relay transmission channels between any two nodes depending on the network conditions. We experimentally verify the feasibility of address generation, virtual networking, and communication channel establishment of the solution. Compared with existing solutions, our solution enables users to have device democracy, improves on data privacy and security, and also avoids single point of failure. Moreover, the solution solves the routing problem of unreachable nodes using structured DHT, and can establish direct or relayed transmission channels to unreachable nodes, improving in communication methods and efficiency.  
Conceptualization, G.L.; Methodology, G.L.; Supervision, C.W. and H.W.; Validation, C.W. and H.W.; Writing--original draft, G.L.; Writing--review & editing, C.W. and H.W. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
All data were presented in main text.  
The authors declare no conflict of interest.
# CT-RPL: Cluster Tree Based Routing Protocol to Maximize the Lifetime of Internet of Things
## 4 Results and Discussion
### Number of Parent Node Changes  
It indicates the number of times RPL routers change its parent during the simulation. Additionally, the parent changes denote the route stability among the network nodes. Figure 4 exhibits the number of parent changes for various RPL protocols. It is observed that the parent changes of RPL, E2 HRC-RPL, and CT-RPL are 30%, 18%, and 10%, respectively. It is also noted that the parent change in the CT-RPL protocol is low when compared to RPL and E2 HRC-RPL. It is due to the efficient rotation of cluster heads between cluster nodes and prevents redundant data transmission in the network nodes.  
Figure 4: Number of parent node changes vs. various routing protocols (RPL). E2 HRC-RPL: energy-efficient heterogeneous ring clustering routing protocol and CT-RPL: cluster tree-based routing protocol.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline OS & Contiki 3.0 \\ Routing Protocol & RPL \\ Node Type & Sky mote \\ Simulation Duration & 1 h \\ MAC Layer & Contiki MAC/6 LowPAN \\ Number of Nodes & 100 RPL Router + DODAG root \\ Transmission Range & 200 m \(\times\) 200 m \\ Data Packet Timer & 60 sec \\ Full Battery & 3000 mJ \\ RPL Parameter & Minimum Hop Rank Increase = 256 \\ Queue Size & 8 packets \\ Data rate & 1 pk per min \\ Aggregation ratio \(\rho\) & 0.8 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Simulation parameters.
## 4 Measurement Results and Analysis
### The Impact of Different Terrains
Figure 7: Least squares fitting of measurement results in two derived scenarios: (**a**) undulating grass, \(H_{t}=H_{r}=5\) cm; and (**b**) flat grass with obstacles, \(H_{t}=H_{r}=5\) cm.
# Solanesol Biosynthesis in Plants
## 4 Key Enzymes in Solanesol Biosynthesis  
### 1-Deoxy-D-xylulose 5-Phosphate Syntase (DXS)  
DXS is the first enzyme of the MEP metabolic pathway that catalyzes the formation of DXP by pyruvate and glycerol-3-phosphate (Figure 2) [3; 6]. _DXS_ genes have been identified in _A. thaliana_[25], _Medicago truncatula_[26], and _S. lycopenetium_[27; 28]. Overexpression or silencing of _DXS_ genes in _A. thaliana_ significantly altered the contents of terpenoids such as chlorophyll, carotenoids, tocopherools, abscisic acid, and gibberellin [25]. Two _DXS_ genes have been identified in _M. truncatula: MtDXS1_ is expressed in all plant tissues except the roots, while _MtDXS2_ is highly expressed only in roots colonized by mycorrhizal fungi [26]. In _S. lycopenetium_, the level of _DXS_ gene expression is positively correlated with the carotenoid content in fruits [27]; silencing of the tomato _SIDXS2_ gene causes decreases in the \(\beta\)-phellandrene content [28]. Recently, [PERSON] et al. [1] discovered that transient expression of potato _DXS1_ and _DXS2_ in _N. benthamiana_ significantly increases the solanesol content. Hence, _DXS_ is the first key enzymatic gene of the solanesol biosynthetic pathway, and its overexpression or inhibition induces changes in the contents of downstream metabolites.
## 5 Conclusions  
The polar code makes the simulation of CD spectra straightforward through the evaluation of the trace of the frequency-dependent electric dipole-magnetic dipole molecular polarizability, \(\mathbf{\alpha}^{em}(\omega)\). polar allows simulating both ECD and VCD spectra based on the quantum chemical outputs routinely produced by the Gaussian code [5]. These calculations allow for the validation of polar thanks to the available literature data.  
As a remarkable byproduct, our theoretical analysis of the molecular polarizabilities also allows one to easily compute the dissymmetry factor \(g(\omega)\), which compares well with the experimental counterpart of camphor, as reported in Figure 8. Finally, we have extended [PERSON]'s Intensity Carrying Modes [32; 33] to the context of VCD spectroscopy. This provides an informative approach to the understanding of the origin of VCD intensities.  
Moreover, the complex polarizabilities computed by polar are of relevance to spectroscopic applications in the presence of controlled distributions of electromagnetic fields that can be realized via nano-optical engineering in order to enhance the chiroptical response [87; 88; 89]. In this framework, the molecular calculations can serve both the purpose of introducing the chiral medium into the electromagnetic simulations via effective medium approaches and of evaluating the weight of the quadrupolar contributions in the CD spectra because of the presence of specific field gradients.  
Conceptualization, M.T., C.Z, G.P. and P.B.; Software, M.T.; Validation, G.L., S.A. and M.T.; Data curation, M.T. and C.Z.; Writing--original draft preparation, M.T.; and Writing--review and editing, C.Z., G.L., S.A., G.P., P.B. and M.T.  
This research was funded by the Italian Ministry of Education, Universities and Research (MIUR) through the PRIN 2015 program (Project No. 2015 FSHNCB \"Plasmon-enhanced vibrational circular dichroism\").  
M.T. acknowledges [PERSON] (Gaussian Inc., Wallingford, Connecticut, USA) for useful details about the formatted checkpoint produced by Gaussian09 rev D.01.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
AAT Atomic Axial Tensor  
APT Atomic Polar Tensor  
CD circular dichroism  
CPKS coupled perturbed Kohn Sham equations  
DFT density functional theory  
ECD electronic circular dichroism  
TDDFT time-dependent density functional theory  
VCD vibrational circular dichroism
# Star Identification Algorithm Based on Dynamic Distance Ratio Matching
We address this issue by using the angles between arbitrary neighboring stars and the distance ratios between neighboring stars and the observed star as the conditions for initial matching. Subsequently, a cumulative angle calculation method in the counterclockwise direction is employed to assess the matching degree with each navigation star. The star with the highest matching degree is determined to be the correct navigation star, thereby improving the robustness of the star identification algorithm against noise interference.
# On the Optimisation of Practical Wireless Indoor and Outdoor Microcells Subject to QoS Constraints
###### Abstract  
Wireless indoor and outdoor microcells (WIOMs) have emerged as a promising means to deal with a high demand of mobile users for a variety of services. Over such heterogeneous networks, the deployment of WIOMs costs mobile/telecommunications company high capital expenditures and operating expenses. This paper aims at optimising the WIOMs taking into account various network communication environments. We first develop an optimisation problem to minimise the number of cells as well as determining their optimal locations subject to the constraints of the coverage and quality-of-service (QoS) requirements. In particular, we propose a binary-search based cell positioning (BSCP) algorithm to find the optimal number of cells given a preset candidate antenna positions. The proposed BSCP algorithm is shown to not only reduce the number of cells for saving resources but also requires a low computational complexity compared to the conventional approaches with exhaustive search over all available sites. Moreover, EDX SignalPro is exploited as a simulation platform to verify the effectiveness of the proposed BSCP for the WIOMs with respect to various propagation modes and antenna parameters of different types, including isotropic, multiple-input single-output and multiple-input multiple-output.  
wireless indoor microcells; outdoor microcells; MIMO; network planning; EDX SignalPro
# ITOC: An Improved Trie-Based Algorithm for Online Packet Classification
### Technical Challenges and Proposed Approach  
Our method is aimed to solve the online packet classification problem and provide a good packet classification algorithm. In online packet classification problems, we meet these challenges.  
* Unpredictable new rule arriving time, rule contents, and arrival frequency;
* Lack of available optimization for the new work scene;
* The demand for both low update latency and high lookup speed.  
Figure 1: The two types of work scenes.  
It is worth noting that although the algorithms need a good update performance, the lookup speed of algorithms is still the most important in online packet classification problem. Considering this, we design our algorithm based on trie structures, which have a good lookup performance and optimize the update process. The contribution of our work can be summarized as follows:  
* We put forward an online packet classification algorithm which has a good lookup performance;
* We design an update time prediction using rule wildness and trie status;
* We implement a trie choosing process based on update time predictions to avoid the potential high update latency.  
The rest of this paper is organized as follows. Section 2 provides a review of the previous and related work. Section 3 presents our method in detail. Section 4 shows the experimental results to evaluate our work. Finally, this paper is concluded in Section 5.
## 3 Mathematical Formulation and Methodology
### Small-Scale Fading
#### 3.3.1 Level Crossing Rate  
From the selected fading distribution, it is possible to calculate its theoretical level crossing rate, in order to estimate the Doppler spread. The theoretical functions of the LCR for the Rayleigh, Rice, Nakagami, and Weibull are respectively [44; 45]  
\[N_{Rayleigh}(\rho)=\sqrt{2\pi}f_{d}\ \rho\ \exp(-\rho^{2}), \tag{3}\]  
\[N_{Rice}(\rho)=\sqrt{2\pi(k+1)}f_{d}\ \rho\ \exp(-K-(k+1)\rho^{2})\ I_{0}(2 \sqrt{K(K+1)})\rho, \tag{4}\]  
\[N_{Nakagami}(\rho)=\sqrt{2\pi}f_{d}\ \frac{m^{m-1/2}}{\Gamma(m)}\rho^{2m-1}\exp(-m \rho^{2}). \tag{5}\]  
and  
\[N_{Weibull}(\rho)=\sqrt{2\pi}f_{d}\left(\frac{\rho}{\sqrt{(a)}}\right)^{\beta /2}\ \exp\left[-\left(\frac{\rho}{\sqrt{(a)}}\right)^{\beta}\right], \tag{6}\]  
where \(r\) represents the fade samples, \(f_{d}\) is the Doppler frequency, \(\rho=r/\sqrt{\Omega}\), \(\Omega=E[r^{2}]\), \(I_{0}\) is the modified Bessel function of the first kind and order 0, and \(\Gamma(.)\) is the Gamma function. The Rician parameter \(K\) represents the ratio between the power of the dominant signal (in line of sight) and the power of the multipath components. The Nakagami parameter \(m\) refers to the quantity of multipath clusters, while the Weibull parameter \(\beta\) is related to the non-linearity of the channel, and \(a=1/\Gamma(1+(\beta/2))\).
## 2 Methodology
### Pre-Processing of Elemental Images
#### 2.1.1 Noise Reduction through Bilateral Filtering  
Applying image blurring is a conventional technique for diminishing image noise. Particularly with images that have minimal texture, such as the background, there may be instances where a stepping effect occurs. This effect is caused by discontinuous disparity levels, resulting in noticeable \"steps\" in areas with reduced changes in depth, as seen in the textured map in Figure 4. The limited resolution, subtle variations in lighting, limited bit depth, and lack of texture can cause seamless transitions to look like sudden shifts. However, using image blurring will inevitably cause a loss of fine information such as edges, hence reducing the accuracy of disparity estimation. To address this issue, bilateral filtering [13] is employed. This technique, known for its ability to preserve edges, is considered as an advanced way of blurring.  
Figure 3: The disparity estimation from the EI pipeline. (**a**) Input raw Holoscopic image. (**b**) Disparity map using multi-resolution content-aware SGBM matching. (**c**) Background correction using background/foreground masks. (**d**) Output disparity image after SGBM and background correction. (**e**) Output: two optimisation results. Top: extracted central VPI. Bottom: fusing depth from multiple EIs.  
Bilateral blurring is applied to each EI to reduce the noise:  
\[I_{\text{filtered}}\left(p\right)=\frac{1}{W_{p}}\sum_{q\in S}I(q)\cdot f_{r}(\|I( p)-I(q)\|)\cdot f_{s}(\|p-q\|) \tag{1}\]  
Let \(I_{\text{filtered}}\left(p\right)\) represent the filtered intensity of pixel \(p\), \(I(q)\) denote the intensity of the next pixel, \(S\) be the set of pixels surrounding \(p\), and \(W\) be the normalised factor. The variable \(f_{r}\) represents the spatial range of the kernel, which corresponds to the dimensions of the neighbouring region. On the other hand, \(f_{s}\) denotes the minimum magnitude required for an edge to be detected. This procedure ensures that only pixels with similar intensity levels to the core pixel are considered for blurring while maintaining distinct intensity fluctuations. A lower value of \(f_{r}\) leads to a more distinct edge. As the value of \(f_{s}\) tends towards infinity, the equation approaches convergence to a Gaussian blur.
# Ocean-Current-Motion-Model-Based Routing Protocol for Void-Avoided UASNs
## 5 Performance Simulation and Analysis
### Performance Comparison
#### 5.2.3 Influence of the Node Initial Energy  
In this section, we discuss the influence of the node initial energy on the performance of these protocols. The number of moving nodes in the network is set to 1200, the maximum node velocity is 3 m/s, the minimum node velocity is 0.2 m/s, and the initial node energy ranges between 40 J and 160 J. The simulation results can be visualized in Figures 14-16.  
Figure 14 depicts the comparison of PDR with different initial node energies. It shows that the PDR of the OCMR, QELAR, and HH-VBF protocols first increases and then plateaus with the increase in node initial energy. The VBF protocol performance is basically stable. This is because the nodes can send more packets and use algorithms to find the relay nodes as the initial energy increases. The OCMR and QELAR protocols perform better than other two protocols as the initial energy component of the node is added to the fitness function and the reward function, respectively, which can better balance the energy of the network and improve the forwarding efficiency of the relay node. However, the OCMR protocol performs better than the QELAR protocol, as it profits from the candidate forwarding set  
Figure 14: Comparison of PDR with different initial node energies.  
Figure 15: Comparison of average end-to-end delay with different node initial energies.  
based on the protection radius and the voidavoided strategy to increase the efficiency of data forwarding.  
Figure 15 represents a comparison of the average end-to-end delay with different initial node energies. It shows that the performance metrics of the four protocols do not change significantly as the node initial energy increases. The performance of the OCMR protocol is the best among them. The reason for this is that the OCMR protocol can suppress the problem of a routing void using the voidavoided strategy, which reduces unnecessary data retransmissions.  
Figure 16 illustrates the comparison of the average energy consumption with different node initial energies. It shows that with the increase in the initial energy, the average energy consumption of the QCMR, HH-VBF and QELAR protocols remains stable, and the performance of the VBF protocol experiences a jitter. However, the OCMR protocol is slightly inferior to the QLEAR protocol. This is due to the fact that the OCMR protocol exchanges information with nodes in the search coverage by broadcasting to search for an alternative relay node, which results in additional energy consumption.