esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Shikonin has also been reported to be involved in miRNAs and has been reported to regulate miR-140-5p/toll-like receptor 4 in the past, leading to the healing of lung injuries [12]. Shikonin ameliorates lipopolysaccharide-inducy cytotoxicity and increases miR-489-3p expression [49]. MiR-146a, one of the miRNAs, has been implicated in inflammatory diseases and has been reported to be associated with inflammation in periodontal tissue in many cases [50]. Several reports have shown that the expression of miR-146a in periodontal tissues is affected by inflammatory responses and [22] that miR-146a levels are higher in chronic periodontitis compared to healthy gingiva [21,51]. The naturally occurring compound curcumin increases miR-146a expression in U87 MG cells [52]. However, the effect of shikonin on miR-146a expression in periodontitis has not been investigated. The expression of miR-146a in hGFs under inflammation-induced conditions decreased with shikonin treatment. These results suggest that shikonin may exert anti-inflammatory and antioxidant effects via its involvement in miR-146a expression in human gingival fibroblasts under inflammation-induced conditions. The anti-inflammatory and antioxidant properties of shikonin may play an adjunctive role in the treatment of periodontal disease by reducing oxidative damage to the periodontal tissues. Further studies should be conducted on its efficacy against periodontal disease, as it has the potential to be used in mouthwashes and toothpaste. In addition, the development of drugs and therapies that regulate miR-146a may be useful in the treatment and prevention of periodontal disease in patients whose miR-146a expression is altered compared to that in healthy individuals. Shikonin-based treatments in the future may assist in controlling inflammation through miR-146a modulation, offering potential as a natural approach for preventing and managing periodontal disease. As only in vitro experiments were conducted in this study, different miRNAs may be involved in the complex pathogenesis of periodontal diseases. Future in vivo experiments are needed to identify miRNAs involved in tissue interactions and investigate the influence of shikonin.
# Reactive Powder Concrete: Durability and Applications
###### Abstract
studied the effects of adding 10% and 15% ultra-fine slag or silica fume on the compressive strength and durability of high-strength concrete. Cement paste with ultra-fine slag showed better fluidity and dispersibility than that containing silica fume, whereas chloride ion penetration resistance of ultra-fine slag and silica fume concretes is quite similar [16]. Table 3 describes the reactive powder concrete properties, recommended values, and types of failure improved. The main objective of this mix design is the setting up of a compact granular system. Packing models and particle size distribution software are tools in this \"contest\" [12]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Components** & **Selection Parameters** & **Function** & **Particle Size** & **Types** \\ \hline \multirow{4}{*}{Cement} & C\({}_{3}\)S \(>60\%\); & Provides binding & & \multirow{2}{*}{OPC (CEM 142.5 R-SR} \\  & C\({}_{2}\)S \(\simeq 22\%\); & characteristics. & & 5–EN 197-1). \\  & C\({}_{3}\)A \(<5\) (\(\cong\)3.8\%); & Formation of primary & & Medium fineness. \\  & C\({}_{4}\)AF \(\simeq\) 7.4\%. & & Pozzolanic reaction. & & \\  & High SiO\({}_{2}\) content. & Formation of secondary & & & Source: ferrosilicon \\ Silica fume & Low amount of impurities. & hydrates. Filling the micropores. & & & industry \\  & & Improves rheology. & & (Highly refined). High \\  & & Maximum reactivity & & fineness. \\  & & during heat-treating. & & 5 \(\mu\)m to 25 \(\mu\)m & Crystalline. \\  & Good hardness. & Provides strength. & & Medium fineness. \\ Sand & Relatively available & Skeleton of the & 150 \(\mu\)m to 600 \(\mu\)m & Natural and \\  & and low cost. & concrete. & & Crushed. \\ Steel fibers & Optimized aspect ratio. & Enhances ductility. & Length: 13–25 mm. & \\  & & & & \\ Superplasticizer & Low retarding & Reduces the & & & Polyacrylate-based \\  & characteristic. & water/cement. & & additive. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters selection for reactive powder concrete constituents.
## 2 Calculation Model and Basic Assumptions  
### Basic Assumptions of Rectangular Pipe Jacking Construction  
The main factors causing displacement and deformation of the surrounding stratum during rectangular pipe jacking construction include additional thrust at the excavation face, friction between pipe jacking machine and surrounding soil, friction between subsequent pipe and surrounding soil, additional grouting pressure, and soil loss [1; 17]. In the process of analytical calculation, the model includes five basic assumptions [31; 32]: (1) the stratum is homogeneous elastic half-space, which has been consolidated under the undrained condition; (2) the pipe jacking machine is along a straight line, regardless of the influence of rectification and tilt of the jacking machine; (3) during the construction process, the pipe jacking machine only changes position in space, without considering the time effect; (4) the supporting force of the excavation face and the friction between the pipe jacking machine,pipe, and soil are uniformly distributed; (5) the factors affecting the stratum deformation are relatively independent, without considering their interaction.  
Due to the complexity of the construction process, the superposition method was adopted to simplify the calculation. The stratum settlement caused by various factors could be calculated separately and then superimposed. The friction of jacking machine and subsequent pipes can be divided into four parts: top surface, bottom surface, left side, and right side. The thrust at the tunnel face, frictions, and grouting pressure act on an infinite body in half space, resulting in internal deformation, which can be calculated by Mindlin's solution.
## 4 Results and Analysis
### Pupil Area
#### 4.1.2 Pupil Area Analysis  
Light reflection of the pupil will cause the pupil to contract when the light levels increase and vice versa. Changes in pupil areas are the most popular physiological and psychological indexes that reflect the cognitive process of drivers [50; 51; 52; 53]. Besides, reasonable lighting conditions will keep the driver's pupil area constant, allowing the driver to be more comfortable in the driving process and to reduce workload intensity [54; 55; 56].  
Figure 5 shows the relationship between the driver's pupil area and the driver's position with respect to the tunnel entrance under different luminance levels during the daytime. As shown in this figure, the pupil area varied slightly compared to the driver's position, but the pupil area remained nearly constant. For \(L\) = 2, 2.5, and 3 cd/m\({}^{2}\), the pupil area ranges between 1400 and 1600 pixels, 1400 and 1600 pixels, and 1200 and 1400 pixels, respectively. Besides, the pupil area of the beginning and the exit sections are higher than the interior section. As can be inferred from Figure 5d, the pupil area decreases with an increase in luminance levels.  
Figure 6 illustrates the average pupil area of each driver in three luminance levels. The correlation between pupil area and luminance level was studied. The fitting comparison between the pupil area and the luminance level revealed that a linear function exhibited a better fitting result (as shown in Figure 6). The fitting equation of average pupil area versus luminance level is given in Equation (2).  
\[P_{\text{A}}=1944.39-191.8L, \tag{2}\]  
where \(P_{\text{A}}\) is the average pupil area (pixel); \(L\) is the luminance level (cd/m\({}^{2}\)). The coefficient of determination of \(R^{2}\) is 0.974, which means that the reliability of the fitting equation is acceptable. The results clearly show that the pupil area decreased significantly with the increase of the luminance level.  
Figure 5: Box plot of average pupil area of drivers for different luminance levels in the daytime: (**a**) under 2 cd/m\({}^{2}\); (**b**) under 2.5 cd/m\({}^{2}\); (**c**) under 3 cd/m\({}^{2}\); and (**d**) comparison results of average pupil area for three luminance levels.
# A Channel Measurement-Based Listen-Before-Talk Algorithm for LTE-LAA and WLAN Coexistence
## 3 Proposed CM-LBT Scheme
### System Model and Transmission Probability of LTE-LAA eNB
With \(b(k)\) and \(b(k)_{e}\) denoting the stationary probabilities of being in states \((k)\) and \((k)_{e}\), we can obtain the normalization condition as follows:  
\[\sum_{k=0}^{W-1}\bigg{(}b(k)_{e}+b(k)\bigg{)}=1. \tag{4}\]  
We write all probabilities in terms of \(b(0)_{e}\) and use the normalization in Equation (4) to determine \(b(0)_{e}\). The keystone is the determination of \(b(W-1)_{e}\) to tackle the \(b(k)_{e}\) chain. A transition into \((W-1)_{e}\) from \((0)_{e}\) occurs if there is an arrival, the medium is sensed as idle, and no collision occurs. In addition, it occurs from \((0)\) if neither a collision nor an arrival occurs. Thus, we have the following:  
\[b(W-1)_{e}=b(0)_{e}\frac{q(1-p)P_{idle}}{W}+b(0)\frac{(1-p)(1-q)}{W}. \tag{5}\]  
We then have for \(W-1>k>0\), \(b(k)_{e}=(1-q)b(k+1)_{e}+b(W-1)_{e}\) with \(b(k)_{e}\) on the left side replaced by \(qb(0)_{e}\) if \(k=0\). Straightforward recursion leads to expressions for \(b(k)_{e}\) in terms of \(b(0)_{e}\) and \(b(0)\). Accordingly, we have the following:  
\[\frac{b(0)_{e}}{b(0)}=\frac{1-q}{q}\bigg{(}\frac{(1-p)(1-(1-q)^{W})}{qW-P_{idle }(1-p)(1-(1-q)^{W})}\bigg{)}. \tag{6}\]  
Using these equations, we determine the first sum in Equation (4) as follows:  
\[\sum_{k=0}^{W-1}b(k)_{e}=b(0)_{e}\cdot\frac{qW}{1-(1-q)^{W}}. \tag{7}\]  
The \((k)\) chain can then be tackled, starting with the following relation:  
\[b(W-1)=b(0)_{e}\frac{qP_{idle}p+q(1-P_{idle})}{W}+b(0)\frac{(1-p)q+p}{W}\;\;. \tag{8}\]  
Iteration leads to  
\[\sum_{k=0}^{W-1}b(k)=b(0)_{e}\cdot\bigg{[}\frac{q^{2}w-q+q(1-q)^{ W}}{1-(1-q)^{W}}+\frac{(1-q)^{2}\{1-(1-q)^{W-2}\}-q(1-q)(W-2)}{1-(1-q)^{W}}\] \[P[(0)_{e}|(0)_{e}]=1-q+\frac{qP_{idle}(1-p)}{W}, \tag{3}\]0 \[P[(0)_{e}|(0)_{e}]=1-q+\frac{qP_{idle}(1-p)}{W}, \tag{3}\]1The LTE-LAA eNB attempts transmission when it is in state \((0)\) or state \((0)_{e}\), a packet arrives, and the medium is sensed as idle. Thus, \(\tau=qP_{idle}b(0)_{e}+b(0)\). Then, given the contention window size, \(W\), the probability that the LTE-LAA eNB will attempt transmission is as follows:  
\[P[(0)_{e}|(0)_{e}]=1-q+\frac{qP_{idle}(1-p)}{W}, \tag{3}\]2  
where \(b(0)_{e}\) can be determined using Equations (4), (7), and (9), so that \(\tau(W)\) is solely expressed in terms of \(p\), \(P_{idle}\), \(q\), and \(W\). In Section 3.3, we discuss how to model \(p\), \(P_{idle}\), and \(q\) by determining the relation between the LTE-LAA eNB and WLAN nodes that are competing for the medium.
## 5 Simulations and Analyses
### Algorithm Simulation
#### 5.2.1 Control Robustness Simulation  
For the four control algorithms, we conducted robustness simulations in three types of perturbed environments: sudden changes in environmental stiffness, environmental position, and desired force. In the selection of abrupt parameter values, we take into consideration factors such as mathematical theory and the limitations of the simulated experimental manipulator and their impact. The parameters are randomly chosen within suitable ranges. The specific perturbation parameters and timing are presented in Table 1. During each robustness test involving a particular perturbation, the remaining parameters were kept constant. The desired force for stiffness and position perturbations was set at \(f_{r}=100\) N. The simulation results of the robustness tests are illustrated in Figure 8.  
Figure 7: Two-link manipulator.  
As shown in Figure 8a, when there is a sudden change in environmental stiffness, all four algorithms demonstrate good force tracking control. However, FOAIC performs the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Mutation Time [s]** & **0–4** & **4–8** & **8–12** \\ \hline Environmental & 4000 & 6000 & 8000 \\ stiffness [N/m] & & & \\ Environmental & 0.3 & 0.305 & 0.315 \\ location [m] & 50 & 100 & 80 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Mutation time and numerical values in robustness simulation.  
Figure 8: Robustness testing simulations of the algorithm. (**a**) Shift in environmental stiffness; (**b**) shift in desired force; (**c**) shift in environmental position.  
best in terms of overshoot and settling speed during contact with the environment and when the environmental stiffness changes. Similarly, as depicted in Figure 8b,c, during the position and desired force perturbations, CIC exhibits the slowest settling speed. AIC and VIC both exhibit overshoot during contact with the environment and when conditions change. On the other hand, FOAIC maintains the fastest response speed while significantly reducing overshoot. The simulations conducted under these three perturbation scenarios collectively illustrate the notable robustness of FOAIC in force tracking.
# A Novel Approach to Wearable Image Recognition Systems to Aid Visually Impaired People
## 2 Proposed Architecture
### System Architecture  
Elements in the system:  
* Cloud-based Server: This unit is a cloud computing platform, integrated with intelligent algorithms such as face recognition, object recognition, optical character recognition (OCR) text recognition. The server of the system uses the Baidu Cloud Server. Running the image recognition algorithm on small embedded devices brings on excessive resource usage and overlap processing time. But for a cloud server with very high hardware configurations, these algorithms can be run in parallel at high speed while ensuring accuracy and speed. It can accept processing requests from  
Figure 1: Architecture of the proposed system.  
many clients at the same time, and then return the recognition results to the client in a short time, as shown in Figure 2.
* Local Unit: it includes the control unit and the input/output unit. The structure and function of the local unit are shown in Figure 3. 1. Control unit: This unit is the brain of the whole system, which is responsible for receiving and processing visual information collected by the sensors, uploading images and analyzing the results of the server feedback. Compared to smart glasses of OrCam Myeye2, this solution has lower capability requirements for the CPU. Because the complex image recognition algorithms are run on the server instead of the local unit. 2. Input/output unit: It includes a micro camera, ultrasonic sensor, infrared sensor and headphone. The camera is the most important input part of the wearable device, serving as the \"eye\" of the user, which can capture the information of the surrounding environment. The ultrasonic sensor is used to measure the distance from the user to the front obstacle. Infrared sensor is mainly used to help users identify whether there is a person in front of them. It is an important input source of the multi-sensor fusion algorithm. In the choice of earphones, two options are provided: single-in-ear headphones, or Bluetooth-enabled bone conduction headphones (especially for hearing impaired people).
* Network unit: the most important problem of online identification is the networking problem. Visually impaired people cannot configure the network, so it is necessary to maintain a good Internet connection. The system supports WIFI and 4G mobile communication. Because the stability of outdoor WIFI is too poor, 4G communication Internet has become an alternative to outdoor networking.
###### Abstract
Compared to the previous works, the contribution of this paper could be itemized as: (1) it suggests an improved earthquake displacement estimation approach by considering the relationship between the earthquake and ionospheric disturbance. An undifferenced uncombined Single-Frequency PPP (SF-PPP) that parameterizes the ionospheric delay of each observed satellite is presented. (2) The relation between deformation and ionospheric disturbance is investigated by applying time-series analysis and spatial interpolation methods. For assessments, 1 Hz high-rate GPS data during the Lushan earthquake (Mw7.0, 2013) and Tohoku-Oki earthquake (Mw9.0, 2011) are processed and analyzed. The paper is organized as follows: the Methodology section illustrates mathematical models of proposed methods SF-PPP and ionospheric calculation. The Results and Discussion section investigates the displacement and ionospheric disturbance obtained from the proposed method. This is followed by the Conclusions section.
# A New Bloom Filter Architecture
## 5 Performance Evaluation
### Performance in Memory Requirements  
Table 3 shows the comparison of the on-chip memory requirements with the NPT-BF and NPT-BF-chaining (with pre-computation) algorithms [9] when the size factor (\(\alpha\)) of the Bloom filter is increased to 2, 4, and 8. The NPT-BF and NPT-BF-chaining algorithms include a standard Bloom filter which only provides membership information. In these algorithms, since all of the nodes of an NPT are  
\begin{table}
\begin{tabular}{l c c c} \hline \hline  & **10k** & **50k** & **100k** \\ \hline No. of names (\(N\)) & 10,000 & 50,000 & 100,000 \\ No. of valid nodes (\(T\)) & 9763 & 48,602 & 96,557 \\ Max. No. of components & 23 & 32 & 32 \\ LPT depth & 4 & 5 & 5 \\ Cell size of \(l\)-BF (\(c_{l}\)) & 5 & 6 & 6 \\ Cell size of \(p\)-BF (\(c_{p}\)) & 8 & 8 & 8 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Routing set characteristics and Bloom filter cell sizes.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Field** & **Length (Bits)** \\ \hline name prefix & 128 \\ output face & 8 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Data structure of hash entry.  
programmed to the Bloom filter, the on-chip memory requirement is equal to \(\alpha S^{\prime}\), where \(S^{\prime}=2^{\lceil log_{2}S\rceil}\) and \(S\) is the number of nodes of the NPT.  
The on-chip memory requirement for the proposed 2-phase BFs is the summation of the memory amounts for the \(l\)-BF and the \(p\)-BF. Since the search performance of the proposed algorithm is heavily dependent on the performance of the \(p\)-BF, the size factor of the \(p\)-BF is fixed at 16 in our evaluation. Hence, the memory amounts for the \(l\)-BF and the \(p\)-BF are equal to \(\alpha T^{\prime}c_{l}\) and \(16N^{\prime}c_{p}\), respectively, where \(T^{\prime}=2^{\lceil log_{2}T\rceil}\) and \(N^{\prime}=2^{\lceil log_{2}N\rceil}\).  
Since the NPT-BF and NPT-BF-chaining algorithms use a standard Bloom filter while our proposed algorithm uses two functional Bloom filters, the proposed 2-phase Bloom filters require more on-chip memory. However, the 2-phase Bloom filters are small enough to be stored in on-chip memories alone because the total amount is a few mega-bytes, as shown in Table 3.  
Table 4 shows a comparison of the off-chip memory requirements. We assumed that the NPT should be implemented with an off-chip memory because of its requirement to store every node of the trie, where a node is represented by five fields: flag, child pointer, child edge, name prefix (128-bit signature), and output face. The memory requirements of the NPT are proportional to the number of nodes. The NPT-BF, the NPT-BF-chaining, and the proposed architecture make up a hash table with an off-chip memory. The hash table memory of the proposed architecture is smaller than that of the NPT-BF and the NPT-BF-chaining, since our proposed architecture only stores name prefixes, while the NPT-BF and NPT-BF-chaining need to store every node of an NPT.
Ultra-Reliable Communication for Critical Machine Type Communication via CRAN-Enabled Multi-Connectivity Diversity Schemes +
Footnote †: This paper focuses on edge-enabled cloud radio access network architecture to achieve ultra-reliable communication, a crucial enabler for supporting mission-critical machine-type communication networks. We propose coordinated multi-point transmission schemes taking advantage of diversity mechanisms in interference-limited downlink cellular networks. The network scenario comprises spatially distributed multiple remote radio heads (RRHs) that may cooperate through silencing, or by using more elaborated diversity strategies such as maximum ratio transmission or transmit antenna selection to serve user equipment in the ultra-reliable operation regime. We derive an exact closed-form expression for the outage probabilities and expected values of signal-to-interference ratio for silencing, transmit antenna selection and maximum ratio transmission schemes. We formulate rate control and energy efficiency under reliability constraints to test the performance and resource usage of the proposed schemes. Furthermore, we study the impact on average system sum throughput with throughput-reliability trade-off under cooperative communication. Extensive numerical analysis shows the feasibility of ultra-reliable communication by implementing diversity schemes with RRHs cooperation.  
Centre for Wireless Communications, Faculty of Information Technology and Electrical Engineering, University of Oulu, 90014 Oulu, Finland; [PERSON]O.L.A.L.); [PERSON]SS] (H.A.); [EMAIL_ADDRESS] (M.L.-a).  
Correspondence: [EMAIL_ADDRESS]; Tel: +35-845-106-0575  
Part of the work appears in the Proceedings of the European Conference on Networks and Communication (EuCNC), Valencia, Spain, 18-21 June 2019; pp. 320-324.
# Ultra-Low-Power FinFETs-Based TPCA-PUF Circuit for Secure IoT Devices
## 2 Adiabatic FinFET-Based PUF
### Adiabatic FinFET TCPA-PUF  
The proposed FinFET-based TPCA-PUF circuit topology is shown in Figure 4. The CMOS-based TCPA-PUF was proposed in [33], which is adiabatically operated in four phases (wait, evaluate, hold, and recover phases). It consists of a static CMOS inverter (P1 and N1), which plays a key role in charging and discharging the PUF cell semi-adiabatically using a trapezoidal power clock signal of Vpc and controlled by the Cb. Similar to the QUALPUF circuit [35], the proposed TCPA-PUF cell consists of a cross-coupled inverter (P2, P3, N2, and N3) to evaluate the response-bits (output nodes of Rb and Rb- in Figure 4). As an improvement from the QUALPUF one, the current flow from one of the output nodes is controlled to slowly flow to the ground through transistor N4, by controlling its operation speed with a ramped Vpc- signal.  
In this work, the same circuit topology is then further investigated using bulk-type FinFETs in SG mode to limit the leakage current that may flow through static inverter P1 and N1 transistors. To the best of our knowledge, this is the first work on SRAM-based FinFET PUF cells in adiabatic operation for ultra-low-power and high performance (security metrics) for secure key generation and/or other related weak PUF application.  
Figure 3: FinFET model and schematic: (**a**) three-dimensional structure, (**b**) cross-sectional top view, and (**c**) schematic symbol (modified from [42]).