esa-sceva/satcom-chunk-collection huggingface dataset:
# LMI Pole Regions for a Robust Discrete-Time Pole Placement Controller Design
## 5 Discussion and Conclusions  
The paper provides the thorough study of discrete-time pole regions appropriate for a robust pole placement controller design. The main problem is finding adequate and computationally simple inner convex approximation for the nonconvex discrete-time system pole region corresponding to the prescribed damping. Previously published inner approximations for circle and ellipse are computationally simple, but they are too restrictive in cases where the realistic closed loop pole position close to the right-hand side pole region border stems from the real plant dynamics. The proposed ellipse-cone approximation much better approximates the original heart-shape region in the right-hand side part than the elliptic one (as shown in Figures 8 and 9). This feature is important since the poles can be better tuned to receive the response, which is damped as required (contrary to the unit circle-based design). In comparison with elliptic approximation, the proposed ellipse-cone one provides wider possibilities to shape the response so that it is not too fast, which is important to obtain a less aggressive control action. This real plant feature is also inherent in the presented case study, a magnetic levitation laboratory system. Discrete-time pole placement results for magnetic levitation for various choices of the \(D_{R}\) region are compared and illustrated in Figure 10. Though the discrete-time controller can be recalculated from the one designed in the continuous time domain, in general, the performance of the resulting closed loop system is usually worse than the continuous time original (in the best case, almost the same). This fact motivates the discrete-time controller design directly in the discrete-time domain.  
The presented results provide the simple convex approximations to the originally nonconvex domain, with all the computational details. The authors believe this can contribute to solving the robust pole placement controller design problem for discrete-time systems with required resulting closed loop system damping (possibly combined with other performance requirements formulated by LMI) as simply as possible.  
Development of \(D_{R}\) Region Mathematical Description, D.R.; Software, D.R. and M.H.; Validation, M.H., D.R.; Experiments, M.H.; Writing--Original Draft Preparation, D.R. and M.H.; Writing--Review and Editing, M.H. and D.R.  
This research received no external funding.  
The work has been supported by Slovak Scientific Grant Agency, grant No 1/0733/16.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 5 Calculation Results and Analysis  
According to the machine layout, the Benchmark problems is divided into two groups: (1) 47 a and b problems; and (2) 30 c and d problems. The ISP-MCTS algorithm was programmed in MATLAB 2016a and run on a central processing unit (CPU)-i5-3470(3.20 GHZ) with 4.0 GB Main Memory. Six algorithms HVNS [20], IDABC [21], particle swarm optimization (PSO) [17], AIS [25], genetic algorithm (GA) [16] and B&B [8] are selected as comparison algorithms. The calculation results of the above comparison algorithm are obtained from the source literature. The HVNS algorithm sets the maximum running time to 100 s and takes the minimum completion time of 20 independent results under the same conditions. The IDABC algorithm also limits their runtime to 1600 s and runs 20 times independently. The maximum running time of the algorithms B&B, AIS, GA and PSO in the literature is limited to 1600 s. The minimum C\({}_{\max}\) is obtained as the final solution by independently operating 20 times under the same conditions, and thus the CPU time corresponding to C\({}_{\max}\) is recorded for each problem. The performance of each algorithm is compared by \"%Deviation\", and the deviation between the lower bound LB and each algorithm C\({}_{\max}\) is obtained by using Equation (16), as shown in Tables 4 and 5. The statistical analysis results are shown in Table 6:  
\[\%\text{deviation}=\left(\frac{C_{\max}-LB}{LB}\right)\times 100\% \tag{16}\]  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**(C,D)** & **(0.1, 32)** & **(0.5, 10,000)** & **(1, 20,000)** \\ \hline
**0-10\({}^{5}\){j15c5d2) (-10 s** & & & \\ \hline Average completion time & 84.83 & 85.14 & 88.27 \\ Standard deviation & 0.53 & 1.27 & 2.50 \\ Average depth & 57 & 19 & 11 \\ \(10^{5}\)-10\({}^{6}\)(30c5e4) (-100 s) & & & \\ Average completion time & 570.9 & 567.3 & 581.1 \\ Standard deviation & 3.51 & 2.77 & 4.73 \\ Average depth & 207 & 73 & 14 \\ \(10^{6}\)-5 \(\times\) 10\({}^{6}\)(30c5e1) (-200 s) & & & \\ Average completion time & 482.7 & 465.3 & 480.5 \\ Standard deviation & 3.56 & 2.72 & 3.21 \\ Average depth & 289 & 98 & 27 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of improved single-player Monte-Carlo tree search (ISP-MCTS) for the different settings.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Problem**} & \multirow{2}{*}{**LB**} & \multicolumn{2}{c}{**ISP-MCTS**} & \multicolumn{2}{c}{**IDABC**} & \multicolumn{2}{c}{**HVNS**} & \multicolumn{2}{c}{**PSO**} & \multicolumn{2}{c}{**GA**} & \multicolumn{2}{c}{**AIS**} & \multicolumn{2}{c}{**B\&B**} \\ \cline{2-13}  & &
# Reliable Augmentation and Precise Identification of EPG Waveforms Based on Multi-Criteria DCGAN
## 3 Results and Discussion  
### Validity Analysis of Generated Waveforms by DCGAN  
The GAN framework functioned with its generator G, and the discriminator D continuously competed until the generated data closely resembled real data. Therefore, an effective GAN model should have exhibited fluctuating loss curves for D during training, making it increasingly difficult for D to distinguish between real and generated data. To obtain comprehensive observations, a high number of iterations was set in this study. Under all parameter settings, the MMD values were extremely small (<0.1), indicating there was a minimal difference between the generated data and the original data. Furthermore, the SVD plots under different epochs (Epoch) were compared as shown in Figure 3. For Figure 3a with Epoch = 500, the spatial distribution of the generated waveform was not limited to the first singular value component. Compared to Figure 3b with Epoch = 1000, the distribution was more concentrated in the first singular value component but still less distributed than the real waveform. As shown in Figure 3c, with Epoch = 2000, the distribution was more uniform than that with Epoch = 1000. When Epoch reached 2000, the spatial distribution of the generated waveform was similar to the real waveform, covering a broader range in the entire three-dimensional space. Finally, based on Figure 3d, it was observed that with Epoch = 4000, the spatial distribution of the generated waveform became even more extensive than the real waveform. This indicated that with the increase in training Epoch, the distribution of the generated waveform became closer to that of the real waveform. The DCGAN network completed its training in an average of 0.77 s per round, totaling 500 rounds. This training was facilitated by an i7-12700H processor and a 3060 graphics card. These results suggested that the DCGAN generation strategy was effective. However, whether the generator was overfitting or underfitting remained to be further verified.
# Minimal Collagen-Binding Epitope of Glycoprotein VI in Human and Mouse Platelets
## 1 Introduction
### Anti-Thrombotic Approaches Based on the Blockade of GPVI-Collagen Interaction  
GPVI is recognized as a safe anti-thrombotic target, based on the observations that its blockade reduces experimental thrombosis without impairing hemostasis [11]. Although initial phases of arterial thrombosis are regulated by GPVI interactions with collagen, at further steps GPVI stabilizes the growing thrombus through binding to fibrin [24; 25; 26; 27]. Therefore, several GPVI inhibitors and blocking antibodies have been developed and evaluated in preclinical models or clinical trials of patients with thrombotic diseases to target GPVI functions, thereby inhibiting thrombus formation [11; 28; 29]. However, limited studies are available to map the collagen-binding epitope of GPVI and specifically target only this clinically relevant interaction in platelets.  
In our study, using the crystal structure of the D1 and D2 domains of human GPVI and collagen, we modeled the collagen- and CRP-binding surfaces of the GPVI monomer and dimer, and compared them with other mammalian GPVI isoforms. Using computational modelling and a docking approach, we identified a minimal collagen-binding epitope of GPVI in both human and mouse platelets. Based on these results, we designed a GPVI-blocking antibody (EA-20) which selectively inhibits collagen-mediated platelet adhesion, activation, and aggregation responses, without affecting fibrin-GPVI interaction.
## 3 Results and Discussion
### Proteolytic Changes and Biogenic Amines Content  
The ready-to-eat Pul and ZS dry-cured products differed significantly in the content of amino acids released by proteolysis, especially alanine (47.4 and 30.4 mg/kg), glutamine (44.8 and 23.2 mg/kg), threonine (43.7 and 31.8 mg/kg), and leucine (40.9 and 32.8 mg/kg) (Table 2). The amount of free amino groups dissolved in water determined the majority of typical proteolysis products (0.6 and 0.7 g/100 g (\(p<0.05\)), respectively). Amino groups dissolved in PTA (0.06 g/100 g) in Pul and ZS products proved the presence of the low-molecular-weight fraction of singular amino acids, as well as di- and tripeptides [25; 31]. Similar changes in the proteolysis activity and the accumulation of free amino acids during ripening were described in fermented sausages [38], dry-cured ham [39], and Chinese traditional dry-cured loin [40]. Changes in the profiles of metabolites originating from protein degradation affect the sensory quality and safety of dry-cured products during ripening and are still the focus of science [15]. The high proportion of putrescine, cadaverine, and tyramine in ZS (23.7, 54.3, and 57.2 mg/kg) compared to Pul products  
Figure 1: The microbiological characteristics during ripening (mean, standard deviation, \(n=3\)) of Pul (**a**) and ZS (**b**) products. (4.0, 28.5, and 11.1 mg/kg) confirmed the differences in proteolysis and decarboxylation of ornithine, lysine, and tyrosine, respectively (_p_ < 0.05) (Table 3). A nearly twofold greater share of histamine and tryptamine (163.2 and 9.1 mg/kg, respectively (_p_ < 0.05)) was determined in the ZS products as the result of decarboxylation of histidine and tryptophan. The production of biogenic amines confirmed the metabolic activity of the microflora [41]. The ratio of protein to fat and a slightly different water content could create an environment more or less conducive to the decarboxylation of amino acids by bacteria. The contents of cadaverine, histamine, and tyramine in dry-cured pork shoulder ripened for 3 months remained at a lower level of 7.5, 6.5, and 21.9 mg/kg, respectively [36]. Manufacturing of dry-cured ham is a safe process, although this meat product can occasionally support the accumulation of amino-acid decarboxylation products. In fact, a high proteolytic activity during maturing favors the decarboxylate activity of many microorganisms. So far, no cases of poisoning with biogenic amines after ingestion of dry-cured ham have been confirmed in the literature. The level of amines is not limited by food safety criteria for maturing meat products. The study of [PERSON] et al. [42] revealed that the production of biogenic amines was not a widely distributed property among staphylococci. Only 3.6% strains of coagulase-negative staphylococci isolated during industrial Spanish dry-cured ham processes could produce some biogenic amines, including histamine, putrescine, cadaverine, and tyramine.
# Managing Emergency Situations in VANET Through Heterogeneous Technologies Cooperation
## 3 Architecture and Communication Protocol
### Protocol Communications
#### 3.2.1 Message Definition  
In order to implement the proposed idea in a real system, some additional messages need to be introduced. The most important messages are those to manage neighbor list of each vehicle and those concerning the warning messages in order to inform other nodes of something that is happening in the roads. A WAVE specific protocol called WSMP has been developed to carry messages through nodes. The WSMP allows the applications to directly control the lower-layer parameters such as transmit power, data rate, channel number and receiver MAC addresses. The primary motivation for using the WSMP is to reduce the overload. A WSMP packet is shown in Figure 5.  
Figure 4: Collision management by sub-layers. Here vehicles and LRTM disseminate messages.  
Figure 5: The Format of a WSMP Packet.  
Figure 3: Protocol timing of _RoadSide Unit_ (RSU) and E-OBU during the registering phase.  
Its overhead is 11 bytes, compared to a minimum of 52 bytes of a UDP/IPv6 packet. If a device receives a WSMP packet that has a _WAVE Short Message_ (WSM) Version number not supported by the device, the received WSMP packet will be discarded. The Security Type identifies if the packet is Unsecure, Signed or Encrypted. The Channel Number, Data Rate and TX Power allow the WSMP to directly control the radio parameters. The purpose of the _Provider Service ID_ (PSID) field consists in the similar role as the port number of the UDP/TCP packet, i.e., to identify the application that will process the WSM Data. The Length field indicates the number of bytes in the WSM Date, which might have been security-protected as specified in IEEE1609.2 [40].
###### Abstract  
We have set up a Computational Fluid Dynamics (CFD) modeling, and performed a user evacuation model, for evaluating the risk level in one-way road tunnel tube when used for bi-directional traffic in particular circumstances. The simulations were carried out by considering both peak-hour traffic volumes during the day and off-peak hours overnight. The investigated one-way tube is ventilated by natural ventilation only, and has a length of less than 1000 m. With reference to the worst environmental conditions, which are downstream of the fire due to the direction of natural ventilation, the consequences on escaping users, caused by different types of burning vehicles located in various longitudinal positions along the tube, are shown. The results prove the positive effects on environmental conditions (in terms of temperature, visibility distance, CO and CO\({}_{2}\) concentration) along the user evacuation path when the tube is used for bi-directional traffic at night rather than daytime. Only for the case of 100 MW fire and in the proximity of the exit portal, the last escaping user might be affected by a visibility distance and CO concentration exceeding the threshold values. In this special case, countermeasures for reducing smoke concentration or emergency services at the portals should be provided. However, the quantitative risk analysis, based on a probabilistic approach, showed that the F-N curve of the tube when used for bi-directional traffic with reference to the night always lies below that of the daytime, and the reduction in the risk level is between 80 and 100% for the night traffic compared to daytime one. It is to be focused on the fact that our modeling may represent a reference in investigating the effects of hourly traffic volumes on the risk level in tunnels and may help decisionmakers in understanding when to temporarily close a tube for maintenance, repair, or rehabilitation activities and use the adjacent tube for bi-directional traffic.  
quantitative risk analysis; computational fluid dynamics; peak-hour traffic volumes; one-way road tunnel tube; bi-directional traffic; F-N curves
# Feasible Energy Density Pushes of Li-Metal vs. Li-Ion Cells
## 3 Excess Lithium and Energy Density

Table 2: Theoretical specific capacities and energy densities calculated for zero-excess LMB and LIB. Figure 2: Change of EDs with different factors of excess lithium on the anode. represents the energy density value of current lithium ion batteries with graphite anode. In order to reach to maximum values of ED and a long cycle life, it is indispensable to create a cell with high CE [7; 13; 34]. The cycling stability and \(X_{Li}\) correlation can be estimated from the following equation:  
\[X_{Li}\times CE^{n}=1 \tag{8}\]  
where \(n\) is the cycle number and 1 refers to 100% consumption of the lithium. For example if we take 2 times excess lithium and obtain 98% of CE:  
\[ \begin{array}{c}2\times 0.98^{n}=1\\ n=\frac{\ln 0.5}{\ln 0.98}=34.3\end{array} \]  
After approximately 34 cycles the lithium excess is depleted. Then we can answer how much excess would be needed to reach 80% lithium consumption after 1000 cycles at this efficiency? \[ \begin{array}{c}X_{Li}\times 0.98^{1000}=0.8\\ X_{Li}=\frac{0.8}{0.98^{1000}}=47.5\times 10^{6}\end{array} \]  
Approximately 47 million of lithium excess is obtained where we need a maximum value of \(X_{Li}=6\) to obtain an acceptable ED. If we take \(X_{Li}=6\) in the last equation, 80% of lithium will be consumed after almost 100 cycles. All these calculations prove that only increasing the excess lithium is not enough to obtain long lasting cells. The correlation between CE and \(X_{Li}\) for a cell with 1000 cycle life span is presented in Figure 3.  
When we combine the results of Figures 2 and 3, it can be assumed that an energy density of 367 Wh/kg and CE of 99.8% can achieve \(X_{Li}=6\). Nevertheless, the capacity ratio of negative to positive electrode (N/P ratio) is another parameter in order to determine the full cell performance [35; 36; 37]. For example, N/P ratio is equal to zero for an anode-free (zero excess) configuration. The recommended N/P ratio range is between 1 and 1.2 for LIBs and between 0 and 1 for LMBs [37]. Figure 3: The need of total excess lithium at different CEs (vertical axis is in logarithmic scale).
## 3 Alamouti Code (Transmitter Diversity)  
This section gives an overview of ASTBC. In ASTBC, two transmitters and two receivers are used. Consider a vehicular node i equipped with two transmitting antennas \(tx_{0}\) and \(tx_{1}\), and node j equipped with two receiving antennas \(rx_{0}\) and \(rx_{1}\). The channel between \(tx_{0}\) and \(rx_{0}\) is denoted by \(h_{0}\); that between \(tx_{1}\) and \(rx_{0}\) is denoted by \(h_{1}\). \(h_{2}\) represents the channel between \(tx_{0}\) and \(rx_{1}\) and \(h_{3}\) represents the channel between \(tx_{1}\) and \(rx_{1}\), as shown in Figure 2.  
The two received signals in two adjacent symbol intervals can be written as  
\[r_{0}=h_{0}.s_{0}+h_{1}.s_{1}+n_{0}\]  
\[r_{1}=-h_{0}.s_{1}^{*}+h_{1}.s_{o}^{*}+n_{1}\]  
\[r_{2}=h_{2}.s_{0}+h_{3}.s_{1}+n_{2}\]  
\[r_{3}=-h_{2}.s_{1}^{*}+h_{3}.s_{o}^{*}+n_{3}\]  
where \(n_{1}\), \(n_{2}\), \(n_{3}\) and \(n_{4}\) are complex thermal noise and interference. The receiver \(rx_{0}\) receives two symbols \(r_{0}\) and \(r_{1}\) in time t and the receiver \(rx_{1}\) receives two symbols \(r_{2}\) and \(r_{3}\) in time t + T.  
The combiner combines signals and gives two O/P signals \(y_{0}\) and \(y_{1}\).  
\[y_{0}=h_{0}^{*}.r_{0}+h_{1}.r_{1}^{*}+h_{2}^{*}.r_{2}+h_{3}.r_{3}^{*}\]  
\[y_{1}=h_{1}^{*}.r_{0}-h_{0}.r_{1}^{*}+h_{3}^{*}.r_{2}-h_{2}.r_{3}^{*}\]  
\[y_{0}=(\alpha_{0}^{2}+\alpha_{1}^{2}+\alpha_{2}^{2}+\alpha_{3}^{2}).s_{0}+h_{ 0}^{*}.r_{0}+h_{1}.r_{1}^{*}+h_{2}^{*}.r_{2}+h_{3}.r_{3}^{*}\]  
\[y_{1}=(\alpha_{0}^{2}+\alpha_{1}^{2}+\alpha_{2}^{2}+\alpha_{3}^{2}).s_{1}+h_{ 1}^{*}.r_{0}-h_{0}.r_{1}^{*}+h_{3}^{*}.r_{2}-h_{2}.r_{3}^{*}\]  
Figure 2: Alamouti space-time coding.
## 2 Materials and Methods
### Solution Preparation  
Electrospun mats were obtained from PCL (80 kDa, Sigma Aldrich, Munich, Germany) solutions and acetic acid (AA, VWR, Darmstadt, Germany) was used as solvent. The solutions of PCL in acetic acid (20% _w/v_) were mixed overnight and then were ultrasonicated for 1 h before electrospinning. To produce the composite electrospun mats, 4555, BGMS10, and BGMS_2 Zn were homogenously dispersed (5 wt% respect to PCL) in the polymer solution and mixed for 10 min and subsequently immersed in ultrasonic bath for 1 min before electrospinning. The amount of bioactive glass was chosen at 5 wt% because previous studies demonstrated that adding only 5 wt% bioactive glass to PCL can already generate relevant in vitro and _in vivo_ outcomes with respect to PCL only [55]. In particular, the focus of this work is the development of composite fibers with suitable properties for applications in soft tissue engineering, as widely reported [47; 48; 49; 50] and it is not oriented to the osteogenic differentiation as reported in [55]. The composite electrospun mats were namely PCL, PCL, 4555, PCL_BG10, and PCL_BGZn.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**BG Label** & **SiO\({}_{\mathbf{2}}\)** & **CaO** & **Na\({}_{\mathbf{2}}\)O** & **K\({}_{\mathbf{2}}\)O** & **P\({}_{\mathbf{2}}\)O\({}_{\mathbf{5}}\)** & **MgO** & **SrO** & **ZnO** \\ \hline
**4555**[16] & 45 & 24.5 & 24.5 & - & 6 & - & - & - \\ \hline
**BGMS10**[17; 18; 19; 20; 21; 22; 23] & 44 & 22.3 & 2.2 & 3.4 & 5.7 & 6.3 & 16.1 & - \\ \hline
**BGMS\_2 Zn**[24] & 41.1 & 20.8 & 2 & 3.1 & 11 & 5 & 15 & 2 \\ \hline \end{tabular}
\end{table}
Table 1: Summary of bioactive glasses (BGs) compositions reported in wt%.  
Figure 1: SEM analysis of bioactive glass particles after milling before electrospinning: 4555 (**a**), BGMS10 (**b**), and BGMS_2 Zn (**c**).
# Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey
## 3 Background: iSDVN System
### Data Dissemination  
Vehicles may gather and disseminate data to big data repositories, such as current location, speed, and road density [98; 99]. As a result, adjacent vehicles collect data on road and surrounding conditions and reduce their speed to avoid future accidents [100]. One-hop and multi-hop communications can be used to disseminate data [29]. High latency in high-traffic areas can impact the performance of data distribution networks [101]. An SDVN has its inherent features, making it difficult to establish a secure and effective data dissemination scheme [85]. Random mobility, rapid topology changes, link partitions, or network fragmentation also occurs in the vehicular environment at nodes. Vehicles in random mobility patterns are considered for data dissemination in SDVNs. This would significantly affect data delivery, quickly contributing to severe packet failures. In addition, scalability will be increased by forwarding data packets between two-way nodes using multiple hops for the wireless radio spectrum of RSU [102]. Through SDN, VANETs can disseminate data effectively and efficiently [103].