esa-sceva/satcom-chunk-collection huggingface dataset:
# Path Optimization Using Metaheuristic Techniques for a Surveillance Robot
###### Abstract  
This paper presents an innovative approach to optimize the trajectories of a robotic surveillance system, employing three different optimization methods: genetic algorithm (GA), particle swarm optimization (PSO), and pattern search (PS). The research addresses the challenge of efficiently planning routes for a LiDAR-equipped mobile robot to effectively cover target areas taking into account the capabilities and limitations of sensors and robots. The findings demonstrate the effectiveness of these trajectory optimization approaches, significantly improving detection efficiency and coverage of critical areas. Furthermore, it is observed that, among the three techniques, pattern search quickly obtains feasible solutions in environments with good initial trajectories. On the contrary, in cases where the initial trajectory is suboptimal or the environment is complex, PSO works better. For example, in the high complexity map evaluated, PSO achieves 86.7% spatial coverage, compared to 85% and 84% for PS and GA, respectively. On low- and medium-complexity maps, PS is 15.7 and 18 s faster in trajectory optimization than the second fastest algorithm, which is PSO in both cases. Furthermore, the fitness function of this proposal has been compared with that of previous works, obtaining better results.  
robotics; surveillance; inspection; optimization; genetic algorithm; particle swarm; pattern search +
Footnote †: journal: Applied  
ArticlePath Optimization Using Metaheuristic Techniques for a Surveillance Robot  
1
# Antioxidant Production in _Dunaliella_
## 2 Antioxidants
### Generation and Detoxification of ROS
Different isozymes of SOD exist (Mn-SOD in mitochondria and peroxisome, Fe-SOD in the chloroplast, and Cu/Zn-SOD isozyme in cytosol) but they all participate in scavenging of O2\({}^{\bullet-}\). In addition to SOD, some antioxidants molecules (Vitamin C, glutathione, etc.) also eliminate O2\({}^{\bullet-}\)[45]. Further, the individual or cumulative catalytic activity of catalase or peroxidases decompose H2O2 into H2O and O2. CAT, peroxidases (GPX, APX) and SOD show a synergistic effect in the scavenging of O2\({}^{\bullet-}\). In addition to eliminating H2O2, GPX  
Figure 2: Generation of ROS by energy transfer and during intracellular metabolic pathways in microalgae (FD; ferredoxin, FNR; ferredoxin-NADP\({}^{+}\) oxidoreductase; PSI-Photosystem I; PSII-Photosystem II, PC-plastocyanin [90; 95]). can protect cells by preventing intracellular lipid peroxidation [48]. APX may be more efficient compared to CAT or GPX in detoxification of H2O2 due to its higher affinity for H2O2. APX reduces H2O2 into H2O in chloroplasts, cytosol, mitochondria and peroxisomes, and in the apoplastic space using Ascorbic acid (ASc) as an electron donor [99]. Algal cells accumulate ASc with 30-40% remaining in the chloroplast. Ascorbic acid is water-soluble and acts as a potent antioxidant because of its ability to donate electrons in enzymatic and non-enzymatic reactions [100]. It protects cells by directly scavenging O2\({}^{\bullet-}\), HO2\({}^{\bullet-}\) and regenerating thetocopherol from tocopherooxyl radicals [101]. All intracellular compartments generate the reduced form of glutathione, which plays a role as an excellent scavenger of many ROS such as O2\({}^{\bullet-}\), HO\({}^{\bullet}\), O3, NO2, lipid hydroperoxides [50] due to the redox-active thiol group that becomes oxidised when GSH reduces ROS [102]. Carotenoid also protects cells from light-induced oxidative stress by quenching 1O2 or dissipating excess heat (excitation energy) or scavenging peroxy radicals [45; 48]. As the accumulation of enzymatic and non-enzymatic antioxidants in the cell depends on the external environment, manipulating cultivation conditions could enhance the intracellular antioxidant levels.
## 3 System Models
### Sensing Coverage Model  
**Assumption 3**. : _Node deployment_: _incomplete or redundant sensing coverage of the network will reduce network QSC. In this paper, to avoid network over-sensing coverage redundancy, the area of cooperation sensing by three covered nodes will not be covered by the fourth node again._  
The distribution of network nodes leads to complex intersecting coverage of multiple nodes. Under different CTS, the entire sensing coverage area of the WRSN changes due to node energy exhaustion and replenishment. This paper provides an accurate real-time sensing coverage area calculation scheme. A few variables are introduced first to facilitate the introduction of this scheme. \(\triangle\)\(ij\) is the triangle formed by the intersection of \(s_{i}\) or \(s_{j}\) and two nodes. \(\triangle\)\(ijk\) is the triangle formed by the intersection of \(s_{i}\), \(s_{j}\), and \(s_{k}\) within the three intersecting sensing areas. \(h^{i}_{\triangle ijk}\) is the edge corresponding to \(s_{i}\) in \(\triangle\)\(ijk\). \(a^{i}_{\triangle ijk}\) is the triangle area enclosed by \(s_{i}\) and \(h^{i}_{\triangle ijk}\). \(\widetilde{h}^{i}_{\triangle ijk}\) is the circular arc of \(h^{i}_{\triangle ijk}\). \(a_{\triangle ij}\) and \(a_{\triangle ijk}\) are the areas of \(\triangle\)\(ij\) and \(\triangle\)\(ijk\), respectively. \(a^{i}_{\triangle ij}\) is the triangular area enclosed by \(s_{i}\) and \(h^{i}_{\triangle ijk}\). \(a_{\triangle i\triangle jk}\) is the sector area enclosed by \(s_{i}\) and \(\widetilde{h}^{-i}_{\triangle ijk}\). \(\angle S_{ij}\) is the \(s_{i}\) top angle in \(\triangle\)\(ij\) and \(\angle S_{ijk}\) is the \(s_{i}\) top angle in \(\triangle\)\(ijk\). **Definition 3**. : _Area of Cooperative Sensing, AoCS: the sensing coverage area covered by multiple nodes in the WRSN is defined as the AoCS, and the set is expressed as \(A_{c}=\left\{a^{1}_{c},a^{2}_{c},\ldots,a^{N}_{c}\right\}\)._  
_The specific calculation method of the AoCS is shown in Algorithm 1._  
**Definition 4**. : _Area of Independent Sensing, AoIS: the area independently covered by the node after removing the \(a_{c}\) is called the AoIS, and the set is \(A_{I}=\left\{a^{1}_{I},a^{2}_{I},\ldots,a^{N}_{I}\right\}\)._  
_The total AoIS of the network is expressed as \(a_{TI}=\sum\limits_{j=1}^{N}a^{j}_{I}=\sum\limits_{j=1}^{N}\left(a_{m}-a^{j}_ {c}\right)\), \(a_{m}=\pi(R_{m})^{2}\)._  
_Under the \(m\) CTS, nodes may stop working if they run out of energy, so the WRSN real-time total sensing area (TSA) changes, denoted as \(a_{TSR}(m)\).
## 2 Materials and Methods
### Determination of the Antimicrobial Effect of Plasma-Treated Liquids  
The respective liquid-physiological saline solution or tap water was treated with plasma for 10, 20, and 30 min, defined as treatment time (t\({}_{\text{treat}}\)). Afterwards, these liquids were mixed with the microorganism--_S. aureus_ or _E. coli_--and incubated for 30 or 60 min, defined as exposure time (t\({}_{\text{exp}}\)). For this purpose, 100 \(\upmu\)L of the bacteria stock suspension was added to 5 mL of the plasma-treated liquid filled in a petri dish 55 \(\times\) 14.2 mm (VWR, Darmstadt, Germany). The liquid was incubated on a multi-functional orbital shaker (PSU-20i, biosan, Riga, Latvia) for up to 30 or 60 min. Over the course of the exposure time, samples were taken in regular intervals and used to determine the total viable count as colony forming units/mL. The spiral plate method (spiral plate: Eddy Jet 2, IUL, Barcelona, Spain [29]) was used, with tryptic soy agar plates which were incubated for 24 h at 37 \({}^{\circ}\)C. The total viable count was measured by an automated colony counter (Flash & Go, IUL, Barcelona, Spain). As a control, 100 \(\upmu\)L of the microorganism suspension was added to 5 mL of untreated liquid. This mixture was also used for the determination of the total viable count. All measurements were performed 6 times (n = 6).  
The reduction of the total viable count is expressed as log\({}_{10}\)(\(N_{\text{R}}\)) which was calculated as log\({}_{10}\)(\(N_{\text{R}}\)) = log\({}_{10}\)(\(N_{0}\)) - log\({}_{10}\)(\(N_{\text{S}}\)), where \(N_{0}\) is the total viable count of the control and \(N_{\text{S}}\) is the total viable count after the respective exposure time.
## 4 Results
### Testbed Effects of Malicious Traffic
As previously mentioned, recovery from the SYN-flood attack was significantly complicated by Modbus TCP's backoff mechanism. When the connection was abruptly terminated, the PLC would increase the time between reconnection attempts. As a result, prolonged attack traffic caused longer outages. During testing, the communication link took anywhere from 20 s to 5 min to re-establish, depending on the length of the SYN-flood attack. Furthermore, we observed adverse effects on the gateway's response time, even though the Modbus TCP communication link remained functional. As shown in Figure 8, PSH+ACK packets occasionally triggered large latency spikes of up to 100 ms. These spikes were unpredictable, which could lead to issues in systems requiring low latency. Interestingly, when these spikes were absent, the gateway responded consistently within 3 ms without having to retransmit packets during the study. Figure 6: Increasing impact of exponential backoff. Synchronization attempts are shown in gray. Figure 7: Modbus TCP effective transactions in response to SYN-flood traffic. Several optional security features were enabled on both the protocol and security gateways to gauge their effectiveness in preventing the aforementioned attacks. These features included SYN-flood protection, SYN-scan protection, and DoS protection on the protocol gateway. The security gateway acted as a physical firewall and was tested by limiting traffic to TCP and restricting specific port ranges. Finally, the software-defined switch was reintroduced with static route declarations to ensure that only the PLC and protocol gateway could communicate over Modbus TCP. A second switch was added to the DNP3 network to ensure that only the DNP3 outstation and protocol gateway could communicate with each other. The results of these tests are summarized in Table 2. From these results, it is evident that the software-defined switch effectively mitigates external attacks, as any attacks would require physical alteration of a device or access to the switch configuration. However, several security features aimed at addressing the vulnerabilities identified in the tests failed to prevent communication loss. The protocol gateway's SYN-flood protection, for instance, only triggered when the rate of SYN packets exceeded 50 packets per second. Therefore, attacks with fewer than 50 packets per second were capable of disrupting Modbus TCP communication without triggering the protection. Similarly, the DoS prevention mechanism encountered similar limitations, as the attack traffic did not meet the threshold required to activate packet blocking. The security gateway had more success mitigating SYN-flood and RST attacks by filtering traffic to specific ports. However, standard firewall features that restricted traffic to TCP alone failed to prevent SYN attacks, and port filtering only worked if the SYN-flood did not duplicate the restricted ports. Figure 8: Response time deviation in response to additional PSH-ACK packets.
# Assessment of Cardiovascular Disease in Autosomal Dominant Polycystic Kidney Disease
## 4 Echocardiography  
Echocardiography findings in ADPKD patients have been well known for a long time [12; 13; 14; 15]. Specific cardiac abnormalities related to mutations of PC1 and PC2 have not been reported, but all valvular apparatuses are involved in this condition; the most reported valvular defects are mitral valve prolapse, mitral incompetence, and tricuspid valve prolapse. Regardless of other possible causes, these abnormalities are more frequent in affected patients than in the general population [16; 17; 18; 19; 20]. According to the study by [PERSON] et al., mitral valve prolapse occurs in 26% of patients with PKD1, 14% of unaffected relatives, and 10% of control subjects [16].  
Some observations report an increased incidence of large- and small-vessel aneurysms localized on ascendent aorta and coronary arteries [21; 22]. These are specific experiences, not based on large studies; thus, is not possible to correlate ADPKD with a higher rate of aneurysms on these sites.  
A matter to explore is the mechanism which leads to these abnormalities. It seems that cardiovascular disease is not totally related to kidney disease. An interesting study  
Figure 1: Abbrev.: HRV, heart rate variability; FMD, flow-mediated dilation; CIMT, carotid intima–media thickness; PWV, pulse wave velocity; CT, computed tomography; MRI, magnetic resonance imaging.  
conducted by [PERSON] et al. on three cohorts of patients (affected individuals, non-affected familiers, and the general population) showed a higher prevalence of valvular abnormalities not only in affected people (3-fold higher than in healthy controls) but also in non-affected familiers (1.5-fold higher than in healthy controls) [23]. The mechanisms which underline these abnormalities are still unclear and probably need to be better understood to set up a specific prevention. We could suppose other pathogenetic pathway, different from the ones that cause kidney disease and cystic formation, involved in the changes in cardiac architecture.
# Dynamic Network Resource Autonomy Management and Task Scheduling Method
## 2 Related Work
can make upgrading and configuring the underlying foundation more accessible, and the architecture's performance is verified in practical cases. The results show that this architecture can effectively reduce the control time overhead of configuration updates and decisions [8; 40]. However, although the cross-domain SDN architecture is excellent in many aspects, it ignores the development of interface protocols for the interconnection between logical planes. Currently, there is no specification for reference in this regard, so how to formulate a suitable interface protocol according to different links is still a problem to be explored [41]. To solve the dynamic management problem among multiple resources in the satellite information network, [PERSON] et al. considered the random observation and transmission channel conditions in the satellite information network during the research process and established a comprehensive optimization framework. To ensure the effectiveness of the network, they formulated a traffic optimization problem based on time-expanded graphs. They proposed an online algorithm using the Lyapunov optimization technique theory to solve the traffic optimization problem on time-expanded graphs in a slot-by-slot manner [1; 42]. However, this approach performs well in solving the problem of multiple resource management in satellite information networks. However, it does not effectively consider the latency problem of switching between multiple observation targets when observing satellites. It also fails to integrate the different effectively adaptable quality of service parameters required. These issues are the critical points that the method needs to pay attention to in future development. Therefore, in response to the above-unresolved issues, we design an adaptive management architecture for resource unification and allocation and propose an improved dynamic scheduling algorithm adapted to dynamic satellite network changes to solve these problems.
## 2 Materials and Methods
### Methods
The \"stress-strain\" curves in compression \"\(\varepsilon_{b}\)-\(\sigma_{b}\)\" and in tension \"\(\varepsilon_{bt}\)-\(\sigma_{bt}\)\", constructed from the results of determining the strength and deformation characteristics of the test concrete, are shown in Figures 14 and 15. The stress-strain curves of concrete obtained by dispersed reinforcement with coconut fibers demonstrated that coconut fibers significantly affected the deformability. The maximum of the \"stress-strain\" curves of FDRC in the amount of 1.75 % _wt._ of cement is above and to the right in the diagrams of concrete with other considered dosages of coconut fiber, and the peak of the curve of concrete deformation with the amount of fiber 2.5 % _wt._ almost coincides with the peak diagrams of concrete with the amount of fiber 0.25% and 0.5%, or slightly below and to the right of them. \begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Concrete Characteristics**} & \multicolumn{8}{c}{\(\Delta\) **(\%), Depending on the Content of Coconut Fibers (\%)**} \\ \cline{2-10}  & **0** & **0.25** & **0.50** & **0.75** & **1.00** & **1.25** & **1.50** & **1.75** & **2** & **2.25** & **2.5** \\ \hline \(R_{b.cib}\) (MPa) & 0 & 3.4 & 8.7 & 15.8 & 17.8 & 20.5 & 22.4 & 25.8 & 20.8 & 10.7 & 3.0 \\ \hline \(R_{b}\) (MPa) & 0 & 3.9 & 8.9 & 13.7 & 16.4 & 19.6 & 20.8 & 24.1 & 18.2 & 5.4 & \(-\)3.3 \\ \hline \(R_{btb}\) (MPa) & 0 & 9.4 & 17.0 & 20.8 & 26.4 & 32.1 & 35.8 & 41.5 & 30.2 & 15.1 & 1.9 \\ \hline \(R_{bt}\) (MPa) & 0 & 13.3 & 20.0 & 23.3 & 26.7 & 30.0 & 33.3 & 43.3 & 33.3 & 13.3 & 3.3 \\ \hline \(\varepsilon_{bR}\) (mm/m \(\times\) 10\({}^{-3}\)) & 0 & 9.3 & 16.4 & 20.1 & 23.4 & 27.6 & 34.1 & 45.8 & 39.7 & 28.5 & 22.0 \\ \hline \(\varepsilon_{btR}\) (mmThe established dependencies and identified characteristic relationships between the initial factors and output parameters proved the high efficiency of dispersed coconut fibers in the composition of concrete. The next task was to analyze the microstructure of the hardened cement paste of concrete, dispersedly reinforced with coconut fibers, to analyze it at the micro level after evaluating the effectiveness of such reinforcement at the macro level.
## 2 Materials and Methods  
### Reagents and Materials  
Methacrylic acid (MAA), divinylbenzene (technical grade 80%, DVB-80), ethylene glycol dimethacrylate (EGDMA), 2-hydroxyethyl methacrylate (HEMA) and 2,2-azobisisobutyronitrile (AlBN) were obtained from Sigma Aldrich (Madrid, Spain). MAA was purified by reduced pressure distillation. DVB-80 was freed from impurities using a self-made column of neutral alumina (Sigma Aldrich). The stabilizers of EGDMA were eliminated by an inhibitor remover column from Sigma Aldrich. AIBN was purified by recrystallization in MeOH. HPLC grade reagents including acetonitrile (ACN), formic acid (FA) and MeOH were supplied by Scharlab (Barcelona, Spain). Analytical grade reagents including ammonia (25%) (AM), acetic acid (HOAc) and dimethyl sulfoxide (DMSO) were obtained from Panreac (Barcelona, Spain). Ultrapure water was produced by a Milli-Q water system (Molsheim, France). C\({}_{18}\) SPE cartridge (500 mg, 6 mL) was supplied by Supelco Analytical (Bellefonte, PA, USA).  
Reference standards of colistin (62.9% purity) containing two major components of colistin A (CSA with the CAS number of 7722-44-3) and colistin B (CSB with the CAS number of 7239-48-7) was purchased from USP reference standards (Twinbrook Pkwy, Rockville, MD, USA) and polymyxin B (84.7% purity) was obtained from Toronto Research Chemicals (Toronto, Canada). Figure 1 presents their chemical structures. A 1 g L\({}^{-1}\) concentration level of individual stock solution was prepared by weighing appropriate standard based on purity into a 10 mL of brown volumetric flask and dissolving with water, and then stored at -20 \({}^{\circ}\)C for no more than 3 months. Stock solutions were mixed and then diluted by fresh water daily to prepare working mixed standard solutions (100 mg L\({}^{-1}\) and 10 mg L\({}^{-1}\)).
## 1 Introduction
Especially, sensor nodes located far away from the query point require largebattery consumption because they must transmit messages to the query node through several intermediate sensor nodes. In this paper, we propose a greedy approach for _l-k_NN query processing in mobile sensor networks. The key idea of the proposed approach is to divide the search space into subspaces whose sides are all \(l\). By selecting \(k\) sensor nodes from the other subspaces near the query point, we can obtain accurate query results for _l-k_NN. The proposed approach has several challenging issues, including estimating the search space, dividing the search space with the \(l\) constraint, and traversing between the subspaces. We present efficient solutions for each of these challenges. In our experiments, we show that the proposed method exhibits superior performance compared with a post-processing based method using the kNN query in terms of energy efficiency, query latency, and accuracy. The rest of the paper is organized as follows: Section 2 reviews the existing _k_NN query processing techniques. Section 3 presents the proposed _l-k_NN query in detail. Section 4 reports the performance evaluation through various experiments. Finally, Section 5 provides the conclusions for the paper.
# From Patient to Musician: A Multi-Sensory Virtual Reality Rehabilitation Tool for Spatial Neglect
## 8 Discussion
### Findings
#### 8.1.1 Assessment Task  
The data of the _Assessment_ show a clear and interesting phenomenon. During the first 11 s of the _Assessment_, all patients are biased on the average head direction towards their non-neglected side. The assumption is that this is their natural behaviour, i.e., the patients tend to look and explore their non-neglected side when no stimuli are presented. However, after approximately 11 s, when, on average, the first key is played, the average head direction shifts towards the centre and sometimes even towards the neglected side. It is assumed that this is taught behaviour of the patients, i.e., whenever external stimuli are presented, they shift their attention to the neglected side. Patients 1 and 3 corrected their head direction more severely compared to Patients 2 and 4. This is most likely related to  
Figure 18: (**Left**) The average head direction for the _Memory_ task for each patient during all 6 sessions indicates a gradually increasing correction towards their neglected side. (**Right**) The average head direction for the _Free-to-Play_ task for each patient during all 6 sessions indicates a gradually increasing correction towards their neglected side.  
the significantly higher CBS scores of Patients 1 and 3. As they had more severe neglect, a more significant correction to their head direction is warranted, to observe the entire environment successfully. This correlation is evident in Figure 14 for the available data. Ultimately, the _Assessment_ task should result in a metric that accurately predicts the degree of USN in a patient. Additional data points of more patients would be needed to further investigate this behaviour and the correlation with the CBS score.