esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Effect of Nitrogen Starvation on Carotenoids and Astaxanthin Production by H. pluvialis
Mean differences were compared using 1-way ANOVA with Dunnet correction (\(n=6\), \"\(p<0.05\) (Unmarked); \"\(p<0.0001\)). of astaxanthin metabolism in \(H\). _phvialis_ along with proper mathematical models and software might represent a valid tool to identify the optimal operating conditions that maximize astaxanthin productivity, which is the product of biomass productivity times the astaxanthin intracellular content. During cultivation at a large scale, a further challenge would be posed by possible bacterial contamination due to the presence of organic matter in BWW. To cope with this problem, the use of closed photobioreactors and a highly concentrated inoculum would minimize this problem. Finally, some challenges could be posed by the still-high costs of astaxanthin extraction and purification from microalgal biomass. In this view, novel extraction techniques relying on supercritical fluids or liquid dimethyl ether (I-DME) or centrifugal partition might represent a viable alternative to the classical solvents.
## 2 System Modelling
### Tire Model  
The tire mechanics property plays a vital role in the vehicle's dynamics performance, handling stability and comfort. The vertical dynamics and lateral dynamics of the vehicle are coupled to each other by the tire force; hence, the accuracy of the tire model is essential. Tire models are usually divided into theoretical models and empirical or semi-empirical models according to their structural points. The empirical tire is generated based on a large number of experimental data fittings [18], and it is generally accurate, as for example, [PERSON]'s tire model. Fiala and UA tire belong to the theoretical tire model, which is inaccurate but physically meaningful [19]. [PERSON] [20] proposed that the theoretical physical model is impossible to practically apply to automobile dynamics simulations because it lacks the accuracy of quantitative description. [PERSON] [21] parameterized three existing tire models namely, Fiala, UA, and Pacejka tire models, and he drew a conclusion that the Pacejka tire model tire provided the closest fit for the side-force versus slip angle tests of all three tire models.  
The Pacejka tire model shows the relationship among the longitudinal force, the lateral force, the aligning torque and the side angle. It has a high fitting accuracy and can be used within a certain range except for extreme conditions. Therefore, the Pacejka tire model is selected in this paper to calculate the tire lateral force coupled with the vertical load. The relevant expression of the tire model can be found in Ref [19]. The Pacejka tire model is established in MATLAB/Simulink, and the correlative curves under the steering condition of Figure 2 are shown in Figure 3.  
Figure 3: Simulation results of Pacejka tires: (**a**) Slide slip angle; (**b**) Yaw velocity; (**c**) Lateral acceleration; (**d**) Lateral force.  
It can be seen from the tire simulation results in Figure 3, the values and the trend of curves are consistent with the curves in Ref [22], which illustrates the correctness of the tire model established in this article.
# A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation
## 3 Experimental Results
### Discussion  
Brain images are very complex, largely uncertain, and imprecise. The fuzzy clustering based methods are capable of handling the aforementioned challenges.In this paper, we have combined the results from four variants of FCM clustering methods. The RSKFCM and GSKCM are proven to be less sensitive to noise due to the use of kernel distance and the addition of neighborhood information. The MIFCM_S and MIFCM_Y are based on an intuitionistic fuzzy set which considers non-membership value along with membership value. Thus, in comparison to RSKFCM and GSKCM, MIFCM methods handled the uncertainty better and achieved better results. Since we combined the advantages of all four clustering methods, our proposed consensus clustering method achieved better results compared to state-of-the-art methods.  
On the OASIS dataset, the proposed method outperforms other methods in comparison. The OASIS dataset contains skull stripped T1 weighted MRI images. The main challenge in the OASIS dataset is the presence of WM lesions. The presence of WM lesions affects the overall segmentation accuracy of the proposed method. On the IBSR18 dataset, the proposed method outperforms all other methods in comparison. The images in the IBSR18 dataset are affected by acquisition artifacts which have direct impact on the WM tissue segmentation. On the other hand, lack of sulcal CSF labelling in the ground truth affects the GM and the CSF tissue segmentation results. Additionally, the proposed consensus clustering method has been evaluated on a practical autism spectrum disorder (ASD) detection problem. The proposed method outperforms other clustering algorithms. Even though the proposed consensus clustering algorithm is capable of handling noise and can exploit the spatial information in the image, it fails to capture the variations within the neighbourhood voxels. In addition, the time complexity of the proposed algorithm is more compared to individual clustering algorithms.
# Realizing Efficient Security and Privacy in IoT Networks
## 5 Numerical Analysis and Results  
In this section, MATLAB simulation results based on our proposed SCEO algorithm and the Swift privacy rate optimization algorithm is presented. Our investigations show that the magnitudes of all transmission channels are distributed in a Rayleigh form with an even unit of mean square, while the attenuation factor of the transmission self-interference \(\rho\) is set to be 0.8, except where slight changes are required. The transmission power constraints were set at \(20 db\) except where otherwise stated.
## 4 Nanostructured Materials for Uranium Removal
### Application of a Magnetic Reduced-Graphene Oxide/Tea Waste Composite for U(VI) Removal  
Recently, [PERSON] et al. (2019) [86] studied the preparation and application of relatively low-cost and highly efficient adsorptive materials for the removal of uranium from nuclear wastes, such as composites of graphene oxide (GO) and tea waste (TW). The composites GO-TW and the magnetic rGO/Fe\({}_{3}\)O\({}_{4}\)/TW exhibited higher adsorption capacities and faster adsorption kinetics than the simple materials GO and TW (\(Q_{\text{max}\text{ (TW)}}=92\) mg g\({}^{-1}\), \(Q_{\text{max}\text{ (GOTW)}}=112\) mg g\({}^{-1}\) and \(Q_{\text{max}\text{ (rGO)/Fe3O4/TW}}=105\) mg g\({}^{-1}\)), resulting to higher removal rates (\(\sim\)99%) for U(VI). As aforementioned, the solution pH substantially affects the speciation of uranium in the aqueous solutions, and hence, significantly influences the uranium adsorption process. The adsorption of U(VI) on TW, GOTW and rGO/Fe\({}_{3}\)O\({}_{4}\)/TW significantly increased with increasing the pH value from 2.0 to 5.0. At the pH 5, the removal rate of uranium by TW, GOTW and rGO/Fe\({}_{3}\)O\({}_{4}\)/TW materials reached the highest values, noting that at pH value \(<4.0\), uranium exists mainly in the form of UO\({}_{2}\)\({}^{2+}\). Furthermore, due to the advantageous magnetic properties, rGO/Fe\({}_{3}\)O\({}_{4}\)/TW can be easily separated from the treated aqueous solutions, thus enhancing the post-treatment efficiency for further practical applications.  
Table 5 shows the reviewed nanomaterials applied for U(VI) removal from waste/water sources, providing major information about their structural characteristics and their applications in water treatment.  
As revealed from Table 5, the proposed materials seem to work more efficiently for the U(VI) removal at pH values between 4-6. The composite material (GO-DTPAA) exhibits maximum absorption capacity 485 mg g\({}^{-1}\). The other proposed materials with graphene, showed an average high adsorption capacity of 200-300 mg g\({}^{-1}\).  
Table 6 provides the comparison of sorption capacity between different adsorbents, when applied for the removal of uranium. As can be observed by comparing the relevant data of Tables 5 and 6, the sorption ability of the previously described nanostructured materials was generally substantially higher.
###### Abstract  
Currently, it is still a challenge to study the degradation mechanisms of the space traveling wave tube amplifier (TWTA) with no failure and small sample tests. Given that the Copula functions are used to describe the correlation of multiple performance characteristics, this paper develops a bivariate hybrid stochastic degradation model to evaluate the in-orbit reliability of TWTA. Firstly, based on the impact analysis of the life of TWTA, helix current and anode voltage are selected as the performance degradation parameters. Secondly, stochastic processes with random effects based on the one-dimensional Wiener process and Gamma process are applied to describe the degradation of TWTA's helix current and anode voltage, respectively, and the corresponding marginal distribution function is obtained. Then, the Copula function is utilized to describe the correlation between two different performance parameters of TWTA. Meanwhile, this paper also proposed a two-step method to estimate the reliability level of TWTA based on its in-orbit telemetry data through a two-step method, which contains a Markov Chain Monte Carlo (MCMC) algorithm and a maximum likelihood estimation (MLE) algorithm. Besides, the Bayes-Bootstrap sampling method is also used to improve the evaluation accuracy to overcome the defect of an in-orbit small sample of TWTA. Finally, a TWTA degradation case with a set of telemetry data is carried out, and the results show that the method proposed in this paper is more applicable and more accurate than other methods.  
in-orbit reliability; space TWTA; Wiener process; Gamma process; random effects; Copula function 2022  
[PERSON]  
1 Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100049, China; [EMAIL_ADDRESS] (X-B.S.); [EMAIL_ADDRESS] (G.-X.M.); [EMAIL_ADDRESS] (W.-L.W.)  
2
# Tracking of Moving Targets Through Asynchronous Measures
## 4 Numerical Results
### Time Evolution of Accuracy  
In this section we will illustrate and discuss the evolution of the positioning error over time during the tracking process. The scenario is simulated according to the following assumptions:  
1. The altitude of the target is \(h=100\,\mathrm{m}\);
2. The velocity of the target is \(v=10\,\mathrm{m}/\mathrm{s}\);
3. The radius of the orbit is \(r=1000\,\mathrm{m}\);
4. The RMSE of range measurements is \(\sigma_{p}=0.1\,\mathrm{m}\).
5. For all the anchors the LoS probability is \(p=100\%\)  
We can clearly notice in Figure 2 that the proposed algorithm outperforms both the EKF and the PF for both the horizontal and the vertical components. Furthermore, the accuracy achieved by the algorithm does not vary over time, differently from the PF and even more from the EKF, which are sensitive to the geometry of the scenario. Finally, we can see that on the horizontal plane, the PF and the EKF perform very similarly, while in the vertical direction, there is a significant advantage for the EKF, despite its greater simplicity from a computational point of view. For this reason, in the sequel, we will only illustrate and compare the results achieved through the proposed algorithm and the EKF since we have not found any advantages in the application of PF in the considered scenarios.
# Ultra-Small Fiber Bragg Grating Accelerometer
## 4 Conclusions and Discussion  
Theoretically, we have proved that a short vibration arm improves the resonant frequency without reducing the sensitivity, and demonstrated a method to find the pre-stretch in order to find the theoretical sensitivity and resonant frequency. The pre-stretch of the FBG in terms of the resonant wavelength change 1.13 nm is calculated based on the mass of the inertial object 4.41 g and the stretch at the equilibrium 1.38 nm. By using the pre-stretch and mass, the theoretical sensitivity and resonant frequencies are found, 633 pm/g and 67 Hz, respectively, based on the modified spring-mass theory [1; 15].  
Experimentally, an ultra-small FBG accelerometer with a 7 mm vibration arm has been demonstrated here. Its experimental crest-to-trough sensitivity and resonant frequency (244 pm/g and  
Figure 4: Crest-to-trough sensitivity at 5 Hz.  
Figure 5: Frequency response.  
90 Hz) disagree with the theoretical predictions (633 pm/g and 67 Hz), perhaps due to the friction between the inertial object and shell. The theoretical and experimental results agreed well when there were no frictions but only air resistances [13; 15].  
The vibration arm may be further shortened by using a shorter FBG; however, the friction between the inertial object and the shell must be well managed. Otherwise, the friction may significantly influence its performance, because the mass of the inertial object could be too light to overcome the friction to vibrate sinusoidally.  
Temperature affects such FBG accelerometers in two ways, but the effects can be controlled. Temperature affects the length of the shell. As the FBG is fixed on the shell by its two ends, the pre-strain of the FBG will change along with the length of the shell. The sensitivity will change along with the pre-strain. However, it has been demonstrated that a 0.66 nm change in the pre-strain with a 5.71 g inertial object only changed the sensitivity by less than 10% [15]. The shell can be made by temperature insensitive material, such as 4j32 or 4j36, to reduce this temperature effect. Temperature also affects the effective refractive index of the optical fiber. However, the frequency of temperature change is so low that this temperature effect can be eliminated by using a high pass filter.  
The calculations are available online at [[http://www.mdpi.com/2076-3417/9/13/2707/s1](http://www.mdpi.com/2076-3417/9/13/2707/s1)]([http://www.mdpi.com/2076-3417/9/13/2707/s1](http://www.mdpi.com/2076-3417/9/13/2707/s1)).  
Conceptualization, methodology, FFT program, writing K.L.; validation, investigation, formal analysis, K.L., G.L., Y.L.; sensor shell and inertial object manufacturing, J.Y. and W.M.; visualization, Y.L. and J.Y.; project administration and funding acquisition, K.L., G.L., Y.L.  
This research was funded by Bengbu University, grant number BBXY2018 KYQD02, 2019 ZR04 zd, 2017 ZR06 and 2017 ZR10, and Anhui Province Education Department KJ2019A0853 and KJ2017A565.  
The authors declare no conflict of interest.
# Blockchain-Based Cloud-Enabled Security Monitoring Using Internet of Things in Smart Agriculture
## 2 Background
### Cloud Solutions in Smart Agriculture  
Cloud-computing integration with smart agriculture is needed to perform the IoT sensing data storage and analytics, including big-data applications. Researchers proposed solutions to address the issues in IoT-based smart agriculture using cloud computing. [PERSON] et al. [2] proposed a fog-computing-based network architecture for smart farming and agriculture to monitor farms and control agriculture operations. The authors introduced a cross-layer-based channel access and routing solution to optimize the network communication connected to smart-farming endpoints. This improved the network latency of the IoT farming devices connected to the cloud. However, the paper did not discuss the security and privacy aspects of IoT-based smart agriculture. [PERSON] et al. [27] presented an IoT platform to cultivate turmeric outdoors for precision agriculture. The author's application enables the farmers to control the turmeric farm with GUI, improving the quality and productivity of the turmeric while maintaining the network latency that approximately matches real-time communication. However, this work is specific to smart-agriculture turmeric-cultivation application implementation. Ref. [28] proposed an intelligent security system to monitor devices in the agriculture field. The authors implemented the system on Rasberry pi 2. The system can communicate data remotely and send SMS alerts to a remote user. However, the work did not consider blockchain technology to create smart contracts and securely store the data when monitoring the devices in agriculture. [PERSON] et al. [11] discussed the limitations of using big-data solutions in IoT-based smart agriculture. The authors use the K-means algorithm to perform the agriculture data analytics and highlighted that data is insufficient to apply big-data solutions. [PERSON] et al. [29] proposed a method for detecting link failures between local nodes and master nodes and identifying local nodes from the network packets. The MLP hosted in remote nodes is used to test the identification of the nodes. Overall, the literature indicates that cloud solutions benefit the agriculture industry by remotely monitoring and improving productivity in agriculture. However, the cloud-based solutions are prone to data exposures and may lead to security breaches on the cloud service provider if security controls are not properly implemented.
# Nonlinear Model Predictive Control with Terminal Cost for Autonomous Vehicles Trajectory Follow
## 1 Introduction
[16] used the method of adding constraints in the terminal area instead of adding contraction constraints at the terminal point to improve the MPC, and gave the open-loop control results and closed-loop control results of model predictive control, which verifies the stability of tail-end constraints. [PERSON], [PERSON] et al. [17] proposed a nonlinear model predictive control with parametric tail-end contraction constraints; in addition, experiments showed that the control effect of model predictive controller with tail-end contraction constraints is significantly better than that of model predictive controller without tail-end contraction constraints. [PERSON], [PERSON] et al. [18] provided a stability and performance analysis for nonlinear model predictive control schemes subject to input constraints. According to previous research, we can find that the theoretical research on NMPC with terminal cost has been perfected, and this method contributes to the stability of the MPC controller [19]. The paper [19] has proved that suitable terminal cost will make the controller more stable. What's more, traditional NMPC has been widely used in path tracking, but the accuracy of traditional NMPC-based path tracking method is a problem that the industry needs to solve urgently. Aiming at the existing problems, the main contributions of this study are summarized as follows: (1) A nonlinear model predictive control with terminal cost (NMPC-WTC) path tracking method is proposed, in order to make the vehicle converge to the planned trajectory more quickly and smoothly. The proposed path tracking method can improve the stability of controller, and the error of path tracking is below 0.02 m in our simulation. (2) The effectiveness of the algorithm through numerical simulation is proved. The closed-loop and open-loop simulation can validate that the proposed NMPC-WTC path tracking method is better than traditional NMPC path tracking method. (3) The application scenarios of NMPC with terminal cost are analyzed, and the commonly used terminal cost coefficient in engineering is given. The remainder of this paper is organized as follows: In Section 2, the control block diagram of the trajectory tracking of the self-driving vehicles is proposed, and the kinematic model of the vehicle is given. In Section 3, the penalty function with terminal cost is built, and the MPC problem is transformed into a nonlinear program (NLP) problem, and finally the effectiveness of the algorithm is verified in different scenarios. The paper ends with conclusions in Section 4.
## 4 Algorithm for Energy and Fuel Consumption Minimization
### Optimization Data Set  
Our proposed approach for fuel consumption optimization is a chain-form solution generated by DP technique. The implemented DP algorithm concatenates speed transitions to form the optimal speed profile that minimizes fuel consumption. Speed transitions can describe changes on vehicle behaviour if the driving states are defined using the vehicle speed and the gear engaged. In this way, the speed transitions can represent acceleration, deceleration or a constant speed stage. The acceleration and deceleration curves of the vehicles can be defined in different ways [44; 45]. For simplicity, constant acceleration, depending on the gear engaged, is considered for speed transitions of the vehicle, according to [39].  
In the speed transitions, speed and distance are discretized. Speed discretization is performed according to the desired resolution of the optimal speed profile. The distance Dg indicates the speedtransition length. Dg can be made up of one or more minimum discrete steps of distance. In acceleration and deceleration cases, the gears have a different assigned distance Dg because high gears need a longer distance to change the car speed among discrete speed values than low ones. In the constant speed cases, the minimum discrete step for distance is assigned whichever gear is used in the speed transition because the speed does not change.  
The DP algorithm evaluates the speed transition to find the optimal speed profile, therefore the speed transition must be tagged with a quantitative feature. In this method, the speed transitions are tagged using their spent fuel and elapsed time. A fuel consumption model must be used to estimate these variables. The numerical data of initial speed, final speed, initial gear, final gear, simulated road slope, spent fuel and elapsed time for each speed transition are stored into a look-up table. This data set describing the associated features of an individual speed transition is called \"atomic case\". Each atomic case is an entry for the look-up table. This look-up table feeds to the DP algorithm and contains the necessary data to perform the optimization process.  
In the DP algorithm, two sequences only can be compared if the following conditions are fulfilled: they have the same initial and final speed and the same initial and final gear, and they are limited by the same distance points. When two or more sequences of states are compared, only the sequence with the lowest cost is preserved. DP takes into account the road vertical profile and legal and safe speed limits contained in a digital map when it concatenates the necessary atomic cases to find the optimal speed profile.