esa-sceva/satcom-chunk-collection huggingface dataset:
# The Shared Bicycle and Its Network--Internet of Shared Bicycle (IoSB): A Review and Survey
## 2 Background
### History
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Gen.** & **Examples (Name, City or Country, Year)** & **Features** & **Defects** \\ \hline \multirow{4}{*}{1 st (1965–1994)} & White Bicycle, Amsterdam, 1965 [11]; & Low production cost; & Unlocked; \\  & Not given, La Rochelle, 1976 [11]; & Free of charge; & Low security; \\  & Not given, Cambridge, 1993 [11]; & Distinct. & No riding guideline. \\  & Fars\(\phi\) and Grena, Denmark, 1991 [20]. & & \\ \hline \multirow{4}{*}{2 nd (1995–2005)} & Bycyklen, Copenhagen, 1995 [11]; & Locked; & Non real-name verification; \\  & Velo a la Carte, Rennes, 1998 [19]; & Specific stations; & No location information; \\  & Call a Bike, Munich, 2001 [21]; & Payment system; & High production cost. \\  & Velo’v, Lyon, 2004 [22]. & Coin or Smart card access. & \\ \hline \multirow{4}{*}{3 rd (2006–2013)} & Velik’, Paris, 2007 [23]; & Record riding time; & Low accuracy; \\  & UseBike, San Paulo, 2008 [24]; & GPS track; & Limited battery life; \\ \cline{1-1}  & Smart Bike, Washington DC, 2008; [25]; & Networking; & Fixed lock password. \\ \cline{1-1}  & HZBike, Hangzhou, 2008 [26]. & Information service. & \\ \hline \multirow{4}{*}{4 th (2014-)} & OFO, Beijing, 2014 [27]; & Smart Lock; & Difficult maintenance; \\ \cline{1-1}  & Mobike, Shanghai, 2015 [28]: & APP on smart phone; & Environment constrains; \\ \cline{1-1}  & Hellobike, Xiamen, 2016 [29]; & Reshargeable battery; & Unreasonable allocation. \\ \cline{1-1}  & obkie, Singapore, 2017 [30]. & Cellular network. & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Progress of shared bicycle. to be exposed to lower levels of air pollution than cyclists riding for commuting, which could be an inspiration for policymaker to consider how to improve cycling infrastructure and road safety. Except for Strava Metro data (the data sources from [35]), OFO and Mobike companies in China have also set up their own big data platforms which data sources are based on their own shared bicycles [36; 37].
## 3 Network Model
### The Important Level Factor \(\alpha\)  
There are many types of medical sensor collection activities. Some are essential, and must always be guaranteed, such as ECGs or blood pressure; some can be experienced interruption or delay, such as body temperature; and some nodes even only have forwarding functions, without the acquisition function. According to these characteristics, the importance level factor \(\alpha\) of the node is defined, so the higher the importance level of the node, the greater the factor \(\alpha\). The maximum \(\alpha\) is 9, and the lowest is 1.  
In Figure 1[29], the WBANs has 15 various types of nodes, the node set \(V\) is \(\{v_{0},v_{1},v_{2},v_{3},v_{4},v_{5},\)\(v_{6},v_{7},v_{8},v_{9},v_{10},v_{11},v_{12},v_{13},v_{14}\}\), where \(v_{0}\) is EEG, \(v_{1}\) is hearing aid cochlear implant, \(v_{2}\) is positioning, \(v_{3}\) is motion sensor, \(v_{4}\) is blood pressure, \(v_{5}\) is Blood pump ECG, \(v_{6}\) is insulin injection, \(v_{7}\) is glucose, \(v_{8}\) is blood oxygen, \(v_{9}\) is lactic acid, \(v_{10}\) is artificial knee1, \(v_{11}\) is artificial knee2, \(v_{12}\) is pressure sensor1, \(v_{13}\) is pressure sensor2, \(v_{14}\) is sink [30]. The initial value of the residual energy of all nodes is 50, the node's important level factor \(\alpha\) varies with the sensor node, and the corresponding network topology as shown in Figure 2, where each node includes the node name, the residual energy and the importance level factor \(\alpha\). The number on the link between nodes is the transmission energy consumption.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Routing Protocol** & **Routing Mechanism** & **Advantage** & **Disadvantage** & **Energy Consumption** \\ \hline Star topology & Single Hop & Low delay & High energy consumption & High \\ \hline AnyBody [17] & Cluster-Based Multi Hop & Reliable, low load & More complex & Medium \\ \hline HIT [18; 19] & Cluster-Based Multi Hop & Reliable, low load & More complex & Medium \\ \hline WASP [20] & Cross-Layer Multi Hop & Reliable, low load & Large network delay & Medium \\ \hline CICADA [21; 22] & Cross-Layer Multi Hop & Reliable, low load & Large network delay & Medium \\ \hline
[23; 24; 25] & Collaborative & Low packet loss rate and low network delay & Unable to adapt to frequent network topology changes & Low \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparative Analysis of Different Routing Mechanisms.
## 4 CFA for EMG and HRV Feature Fusion
### Fusion Results in 5-Feature Sets  
The feature's fusion correct rate using the score combination of CFA for both of 5-feature sets (A) and (B) are illustrated in Figures 10 and 11.  
Figure 10: Performance of the combination of 5-features sets (A group) using CFA.  
Figure 11: Cont.  
With reference to Figures 10 and 11, the dotted lines show the average of 26 combined features. In this paper, the combined features that have the correct rate over an average of 26 combined features will be the better selected combined features for the automatic gender identification. In Figure 10a, the average correct rate is 95.49%, and it possesses the top-13 combined features which are OV, OA, OVA, OVF, OF, VA, OVAF, OAF, VF, VAF, AF, OVAa, and OVAFa. Next, in Figure 10b, the average correct rate is 93.53% and it possesses the top-13 combined features which are OV, OA, OVA, VA, OVAb, OVAc, OVb, OVc, OAb, OAc, VAb, VAc, and OVAbc. Then, in Figure 10c, the average correct rate is 93.73% and it possesses the top-13 combined features which are OV, OVF, OF, VF, OVFa, OVA, OVFb, OVb, OFa, OFb, VFa, Oa, and OVFab. Lastly, in Figure 10d, the average correct rate is 95.27% and it possesses the top-13 combined features which are OV, OA, OVA, OVF, OF, VA, OVAF, VAF, OVAPb, and OVAb. Thus, in short, all four 5-feature sets (A) have their own top-13 combined features that contribute to automatic gender identification during the stepping activity using the stepper.  
Moreover, in Figure 11a, the average correct rate is 78.36% and it possesses the top-12 combined features which are IP, IU, IPU, Ic, IPUc, IUc, PU, IPd, IPUd, PC, and PUc. Next, in Figure 11b, the average correct rate is 77.75% and it possesses the top-12 combined features which are HR, HRa, Ha, Ra, HRh, HER, HRah, EHRa, Hh, EH, Hah, and EHRh. Then, in Figure 11c, the average correct rate is 80.34% and it possesses the top-12 combined features which are HI. HIJ, IJ, HJ, HLc, HIJc, IJc, Ic, HJc, HIJd, Hc, and HId. Lastly, in Figure 11d, the average correct rate is 77.85% and it possesses the top-12 combined features which are OV, IQ, IS, QS, IQi, IQSi, Ii, ISi, IQSd, IQd, ISd, and Id. Thus, all the four 5-feature sets (B) have their own top-12 combined features.  
All the figures from Figures 10 and 11, shows that the four 5-feature sets (A) have higher correct rate compared to the four 5-feature sets (B). Thus, the overall performance of the 5-feature sets (A) is considerably better than that of the 5-feature sets (B) for automatic gender identification during the stepping activity.  
Besides that, the fusion of \(t\)-feature sets where \(t=7\), 9 and 11 is also calculated. 7-feature sets have 120 combined features, 9-feature sets have 502 combined features and 11-feature sets have 2036 combined features in total. Since the total combination is large, the results were only listed in Table 5 in Section 4.2.
# A Review of Sharp-Switching Band-Modulation Devices
## Operating Principles and Models
### Band-Modulation Mechanism
Once the band modulation mechanism is restored, the turn-on voltage increases linearly with the gate voltage: \(\mathrm{V_{ON}}/\mathrm{V_{FG}}=0.8\) (see Figure 5a). As for the back gate, it controls the electron-injection barrier at the cathode, which is instrumental when the hole barrier is moderately high or the ungated region is short. Figure 8 shows a typical \(Z^{2}\)-FET, which fails to operate correctly with \(\mathrm{V_{BG}}=0\). A modest negative voltage (\(\mathrm{V_{BG}}=-1\) V) increases \(\mathrm{V_{ON}}\), recovering the sharp switching capability and low leakage [27]. With the ground-plane extending underneath the gated region (Figure 2a), a stronger negative voltage (\(\mathrm{V_{BG}}=-2\) V) is actually counterproductive, as it tends to lower the hole injection barrier set by the front-gate and reduce \(\mathrm{V_{ON}}\). This inconvenience can be eliminated with twin ground-planes (Figure 3a). This schematic description underlines the feedback between energy barriers and carrier injection, but does not capture the full complexity of the band-modulation mechanisms in a \(Z^{2}\)-FET. In the physics-based model derived by [PERSON] et al. [28], the key consideration is the current continuity at each of the three P-N junctions: at the cathode, at the anode, and in the center of the body. The model accounts for generation-recombination (GR) and diffusion currents for electrons and holes, whereas MOS equations define the concentrations of electrons \(N^{*}\) and holes \(P^{*}\) (electrostatic doping) in the gated and ungated regions, respectively. The rapid variation of the quasi-Fermi levels with bias is fully captured. Five equations are sufficient to reproduce the S-shape and hysteresis of DC characteristics. The computed curve matches the experiment of Figure 5.  
In the following, we focus on a compact model, suitable for circuit design.
# A Compact Dual-Band Microstrip Patch Antenna for C- and X- and Ku-Band Applications +
Footnote †: The paper presents a compact dual-band pentagonal-shaped patch antenna, with resonating frequencies 7.6 GHz and 12 GHz, that is used for satellite communication, 5G application, and high-speed applications. The proposed antenna is designed on an FR4 substrate with an overall dimension of 16 \(\times\) 16 mm where the height of the substrate is 0.8 mm. The proposed antenna contains a pentagonal-shaped patch with four circles at each corner of the patch that is used for the dual-band; in addition, the circular slot with the combination of the cross-shaped slot achieves better results. The proposed antenna has a partial ground configuration for better bandwidth and gain. The peak gain of the antenna is 8.07 dB at 12 GHz and has a 7.13 dB gain at 7.6 GHz. With its compact size and wide bandwidth capabilities, the antenna proves to be an ideal solution for mobile communication systems, satellite ground stations, and remote sensing applications across C-, X-, and Ku-bands. The proposed antenna also covers Ku used for satellite and high-speed communication.  
C-band; Ku-band; satellite communication; compact dual-band antenna
# Decoupling Control of Multi-DOF Supporting System of MLDSB
## 4 Decoupling Control of the Multi-DOF System
### Design of the Decoupling Device
\[\dot{\mathbf{Y}}=\mathbf{C}\dot{\mathbf{X}}=\mathbf{CA}\mathbf{X}+\mathbf{C}\mathbf{Bu}\] (22) If \(\mathbf{c}_{i}\mathbf{B}\
eq 0\), set \(\alpha_{i}=1\), the following equation will be found: \[\mathbf{Y}^{(2)}=\mathbf{CA}^{2}\dot{\mathbf{X}}+\mathbf{C}\mathbf{A}\mathbf{Bu}\] (23) Similarly, if \(\mathbf{c}_{i}\mathbf{A}\mathbf{B}\
eq 0\), set \(\alpha_{i}=2\), continue to derivative until \(\mathbf{c}_{i}\mathbf{A}^{\alpha i-1}\mathbf{B}\
eq 0\). Arrange Equation (23), and the decoupling order constant can be defined as follows. \[\alpha_{i}=\min[k|c_{i}\mathbf{A}\mathbf{B}\
eq 0,(1\leq k\leq n)]\] (24)  
Respectively replace \(\mathbf{A}\), \(\mathbf{B}\), and \(\mathbf{C}\) with \(\mathbf{A}_{z}\), \(\mathbf{B}_{z}\), and \(\mathbf{C}_{z}\), and get \(\alpha_{i}=2\). Combining Equations (18) and (19), it can be shown as follows. \[\mathbf{Y}^{(2)}=\left[ \begin{array}{c}\mathbf{Y}_{1}^{(2)}\\ \mathbf{Y}_{2}^{(2)}\\ \vdots\\ \mathbf{Y}_{m}^{(2)}\end{array} \right]=\mathbf{F}\mathbf{x}+\mathbf{E}\mathbf{u} \tag{25}\]  
Thus, the following equation can be obtained. \[\mathbf{u}=\mathbf{E}^{-1}\mathbf{v}-\mathbf{E}^{-1}\mathbf{F}\mathbf{x} \tag{26}\]  
Combined with Equation (19), the control law coefficient relation can be obtained as follows. \[\left\{ \begin{array}{c}\mathbf{K}=\mathbf{E}^{-1}\mathbf{F}\\ \mathbf{H}=\mathbf{E}^{-1}\end{array} \right. \tag{27}\]  
Because \(\mathbf{E}\) is a nonsingular matrix, and its inverse is also a nonsingular matrix, therefore, the 2 nd and 3 rd of the time domain decoupling constraints are proven. With the above proof, it can be obtained that the system can be decoupled in the time domain, and the transformation matrix and state feedback control law matrix are brought in and the decoupling effect is as follows. \[\mathbf{Y}=\left[ \begin{array}{cccc}\frac{1}{s^{2}}&0&0&0\\ 0&\frac{1}{s^{2}}&0&0\\ 0&0&\frac{1}{s^{2}}&0\\ 0&0&0&\frac{1}{s^{2}}\end{array} \right] \tag{28}\]
## 2 Materials and Methods
### Evaluation of the Antioxidant Capacity of the Extract  
#### 2.6.1 Total Polyphenols Content (TPC)  
The total content of polyphenols in the methanolic extracts of submerged cultivated mycelium after irradiation treatment was determined by using the Folin-Ciocalteu method [17]. This is based on the reduction of the Folin-Ciocalteu reagent by phenolic compounds, which will form chromogens that can be detected spectrophotometrically.  
The polyphenols in _F. fomentarius_ extract or gallic acid (3,4,5-trihydroxybenzoic acid) reacted with the Folin-Ciocalteu reagent, forming a blue complex which was quantified by measuring the absorbance at \(\lambda\) = 765 nm. Gallic acid has been used as a standard antioxidant compound for spectrophotometric determination of antioxidant activity. Itsstandard curve comprised 6 dilutions: 0.05, 0.1, 0.15, 0.2, 0.25, and 0.5 mg/mL, starting from a 1 mg/mL stock solution.  
The total content of polyphenols in the 20 \(\upmu\)L sample/reference substance was determined by adding 120 \(\upmu\)L of Folin-Ciocalteu solution was diluted 1/10, followed by 1 min of incubation at room temperature. Subsequently, 120 \(\upmu\)L of 7.5% Na\({}_{2}\)CO\({}_{3}\) solution was added, and the final mixture was incubated for 60 min, at 25 \({}^{\circ}\)C. Finally, O.D. was measured at 765 nm, using 80% methanol as a blank [18; 19].  
The total polyphenol content of the methanolic extract was calculated based on the regression equation y = 0.0057\(\times\) + 0.0955 and expressed in micrograms of gallic acid equivalents per mL extract (\(\upmu\)GAE/mL methanolic extract) [19].  
Both the samples and the reference substance were worked in triplicate, and their average absorbance value was calculated.
## 2 Problem Description
### Limitations of Existing Tools  
In the literature, there appear different efforts and approaches addressing the performance evaluation of various wireless mesh networks. Specifically, we can find similar efforts for modeling WirelessHART. As an example, [7] extends the basic, general-purpose IEEE 802.15.4 model of the ns-2 (network simulator 2) simulator with a detailed WirelessHART stack, including accurate modeling of the network time synchronization and other network management tasks. The implementation inherits the transmission range-based physical layer performance model approach from the IEEE 802.15.4 model, _i.e._, the success of a transmission only depends on the range between the corresponding nodes. Therefore, it does not aim at accurately modeling the lower layers. The ns-3 module in [8] adopts a simple two-state Gilbert-Elliot statistical model for packet errors without considering the underlying network. A different approach is taken by [9] by connecting a detailed packet-level network simulator (ns-2) and MATLAB Simulink for the dynamics simulations by using High Level Architecture (HLA) as the means of integration. Their efforts result in a more general, packet-level CPS evaluation framework. However, significant computational complexity results from the synchronization requirements between the two simulators, and accuracy is limited by the fairly simple physical layer models present in the ns-2 simulator.
# Liquid-Crystal-on-Silicon for Augmented Reality Displays
## 3 Fringing Field Effect and Novel Solution
### Exemplary Optimization Results  
Here we use an exemplary optimized structure to demonstrate the performance of the proposed design. The basic HG LCoS parameters are set as follows: cell gap \(d\) = 1.5 \(\upmu\)m, pixel length \(l\) = 6.2 \(\upmu\)m and pixel gap \(g\) = 0.2 \(\upmu\)m, which corresponds to pitch length \(p\) = \(l+g\) = 6.4 \(\upmu\)m. The LC parameters are \(\Delta n\) = 0.16 at 550 nm, \(\Delta e\) = 3.1, \(\gamma_{1}\) = 118 mPa-s, and (splay, twist, bend) elastic constants (\(K_{11}\), \(K_{22}\), \(K_{33}\)) = (13.2, 6.5, 18.3) pN at 25 \({}^{\circ}\)C (from Merck). As illustrated in Figure 8a, by simulating the phase retardation profile with an even pretilt angle, the FFE-affected outer zone and the unaffected inner zone are differentiated with \(w\) = 1 \(\upmu\)m. Applying the second determining method, the optimized inner zone pretilt angle \(\alpha_{i}\) = 88\({}^{\circ}\) and outer zone pretilt angle \(\alpha_{o}\) = 85\({}^{\circ}\) are obtained. Figure 8b shows the results with our modified pretilt angle pattern design: the electric field distortion at pixel edge is much suppressed and the FFE is effectively reduced.  
Figure 8: The pixel location dependent phase retardation curve and equal potential curve with (**a**) even pretilt angle distribution and (**b**) specially-designed uneven pretilt angle distribution.  
Figure 7: The LCoS pixel layout and optimization parameters: pixel length \(l\), pixel gap \(g\), pixel pitch \(p\), FFE border width \(w\), inner zone pretilt angle \(\alpha_{i}\), and inner zone pretilt angle \(\alpha_{o}\).  
One potential concern of our design is the phase retardation uniformity when an equal voltage is applied to adjacent pixel electrodes. Therefore, we plot the phase retardation curves with our special pretilt angle design. From Figure 9a we can see, in the large pretilt angle region (\(\alpha>80^{\circ}\)), that neither phase retardation nor reflectance is sensitive to the pretilt angle. In Figure 9b, generally flat spatial profiles are obtained in our design. The spatial fluctuation at all-pixels-dark state is only \(\Delta\Gamma=\Gamma\) (\(\alpha=85^{\circ}\)) \(-\)\(\Gamma\) (\(\alpha=88^{\circ}\)) = 0.01\(\pi\) for phase retardation and R (\(\alpha=85^{\circ}\)) \(-\) R (\(\alpha=88^{\circ}\)) = 0.03% for reflectance, suggesting that a high contrast ratio could be maintained. At all-pixels-bright state, the reflectance fluctuation is within 0.002%. In other words, the side effect of our proposed design is negligible compared to the gain in FFE reduction.
## 4 Promising Neuropeptides Inhibitors for the Development of Effective Cancer Therapy
### Neuropeptides Inhibitors: A Promising Approach also for Other Cancers
#### 4.2.4 Lung Cancer  
Lung cancer remains the top cause of cancer-related fatalities in both men and women worldwide [160]. BBR is a class of GPCR consisting of the neuromedin B receptor (NMBR), the gastrin-releasing peptide receptor (GRPR), and the orphan bombesin-receptor subtype-3 (BRS-3). These receptors are frequently overexpressed in various cancers, including non-small cell lung cancer (NSCLC) [161]. Research investigations showed that VIP receptors (VPAC1/2) are overexpressed in various cancers (e.g., breast, prostate, and neuroblastoma cancers), gaining attention as targets for potential therapy. Moreover, VPAC1 receptors were found in high amounts in 58% of biopsy samples from patients with lung cancer, indicating their high pathogenicity in vitro [162; 163]. VPAC1/2 are GPCR receptors on which VIP and PACAP-27 bind with high affinity, increasing the activity of adenylyl cyclase and cAMP in small cell lung cancer (SCLC) cells through stimulatory (Gs) subunits, subsequently increasing the secretion rate of BB-like peptides. In numerous cases, VPAC1 antagonists, in combination with chemotherapeutic drugs, inhibited lung cancer growth in many SCLC and NSCLC cells, representing a promising antitumor approach. BB-like peptides have been observed in the dense core neurosecretory vesicles of SCLC cells. With the addition of VIP, the secretion of BB-like peptides from SCLC cells increases, which then bind to the BB2 receptor [163, 164, 165, 166]. Due to the overexpression of BB2 in tumors, various radiolabeled BB analogs have been developed to target tumors with cytotoxic drugs for therapy [121]. NTS is highly expressed in SCLC cells [166]. NTS increases cancer cell survival by activating the PI3K/Akt/mTOR pathway [167]. NTS also induces overexpression of the EGFR, HER2, and HER3 genes in lung cancers [168]. However, addition of 2-([1-[7-chloro-4-quinolinyl])-5-[2,6-dimethoxyyl]pyrazole-3-yl]carboxylamino)tricyclo(3.3.1.1.[3.7]) decan-2-carboxylic acid (SR48692) reversed the signal transduction driven by NTS and reduced clonal growth and xenograft proliferation in SCLC cells [163]. In this context, inhibitors targeting various neuropeptides in different cancer types, especially CRC, have been discussed below and are summarized in Table 3.
## 1 Introduction
### Organization of the Article  
Related work is presented in Section 2, whereas a detailed network framework appears in Section 3. Section 4 illustrates routing in SD-EAR along with proposed sleep request--sleep grant mechanism. Section 5 presents simulation results, and Section 6 concludes the paper.
# Fire-Induced Changes in Soil and Implications on Soil Sorption Capacity and Remediation Methods
## 4 Fire-Induced Changes in Soil and Choice of Soil Remediation Technologies
### Physical Remediation Technologies That Could be Used in Fire-Affected Soils  
#### 4.1.1 Soil Replacement, Isolation and Importing  
Soil replacement involves replacing contaminated soil with clean soil [135], whereas in soil importing, clean soil is added to contaminated soil and homogenized to reduce contaminant concentration per gram of soil. The cost and logistics of excavating and transporting soil could be huge, and so soil replacement can only be feasible if the area contaminated is small. The principle behind soil importing is dilution. Considering the cost involved, these remediation technologies are feasible where the contaminated area is spacious, to allow access to excavators, and where the area of the contaminant plume is small and shallow, to reduce the cost of excavation and transportation. In soil isolation, contaminant spread is prevented by isolating the contaminated site using various barriers, which could be vertically or horizontally placed depending on the nature of contamination, the characteristics of the site, and the contaminants in question [136]. In soil isolation, the contaminant is neither removed nor treated, but its mobility to other environmental receptors is restricted. Soil replacement, soil isolation and soil importing are physical processes which do not require chemical or biological reactions to clean up contaminated soils. They could therefore be used to remediate fire-affected contaminated soils if the contaminated site is spacious and the contaminant plume has not spread extensively.