esa-sceva/satcom-chunk-collection huggingface dataset:
# Genetic Algorithm-Based Intelligent Selection Method of Universal Shield Segment Assembly Points
## 2 Establishment of Assembly Point Selection Objective Function
### Assembly Point Selection Objective Function  
The smaller values of \(U_{h}(n+1)\), \(U_{v}(n+1)\), \(T_{h}(n+1)\) and \(T_{v}(n+1)\) indicate the better relative location of the shield machine and segments after assembling. The purpose of selecting the next segment assembly point \(i_{n+1}\) is to make the four optimization objectives as small as possible. To solve the multi-objective optimization problem of assembly point selection, the weight coefficient transformation method is used to combine the optimization objectives, transforming the multi-objective optimization problem into a single-objective optimization problem and establishing the objective function of assembly point selection (hereafter, objective function), as shown in Equation (5).  
\[\begin{split}\min G(i_{n+1})=\lambda_{h}U_{h}^{2}(n+1)+\lambda_ {v}U_{v}^{2}(n+1)+\xi_{h}T_{h}^{2}(n+1)+\xi_{v}T_{v}^{2}(n+1)\\ s.t.\left\{\begin{array}{l}-90\leq U_{h}(n+1)\leq 90\\ -90\leq U_{v}(n+1)\leq 90\\ -90\leq T_{h}(n+1)\leq 90\\ -90\leq T_{v}(n+1)\leq 90\\ \lambda_{h}+\lambda_{v}+\xi_{h}+\xi_{v}=1\\ \lambda_{h},\lambda_{v},\xi_{h},\xi_{v}\in[0,1]\end{array}\right.\end{split} \tag{5}\]  
where \(\lambda_{h}\), \(\lambda_{v}\), \(\xi_{h}\) and \(\xi_{v}\) are the corresponding weights of each optimization objective. As mentioned earlier, we have a requirement for the weights: they are adaptively taken with the WCPs. The method of selecting the next segment assembly point is as follows: first, we obtain the current construction data, including the WCPs and the assembly point of the previous segment, and the weights corresponding to the WCPs are determined. Then, all the next segment possible assembly points \(i_{n+1}\) that meet the staggered-joint assembly are obtained by Table 1. Then \(i_{n+1}\) are brought into Equations (1)-(5) one by one, and the \(i_{n+1}\) that minimizes the objective function \(G(i_{n+1})\) is selected as the best assembly point \(i_{n+1}^{*}\) of the next segment ring (Figure 5).
## 3 System Architecture
### Edge AI Model  
Each edge device runs a lightweight deep learning model for local anomaly detection. The model is designed to  
* Be trainable on-device with low computational cost;
* Handle time-series IoT data;
* Identify deviations in device behavior. We implement either of the following:
* A 1D convolutional autoencoder (CAE) suitable for compact feature learning from raw data;
* A GRU-based autoencoder, which efficiently captures sequential dependencies in device-generated logs. The choice of model is based on the computational profile of devices, with the GRU version offering better temporal sensitivity.
# Autonomous Underwater Vehicle Localization Using Sound Measurements of Passing Ships
## 1 Introduction
The Range-dependent Acoustic Model (RAM) [39; 40; 41] has been widely used to simulate how the sound signal of the ship propagates in underwater environments. Using RAM, we can derive the feasible region where the AUV can exist, in order to measure the sound of the ship. Then, the RPEKF is applied to estimate the AUV position, considering the feasible region. The contributions of this paper are summarized as follows. This paper assumes that the AUV can access the trajectory and source level of a passing ship, while identifying the ship by processing the ship's sound. To fix long-term drift in the IMU-only localization, we introduce the AUV localization method using sound measurements of passing ships that travel along known routes. Under the proposed localization method based on moving ships, we do not have to create additional infrastructure for AUV localization. Moreover, we can localize the AUV in a stealthy and power-efficient manner, since the AUV does not emit a signal during this passive localization. As far as we know, this AUV localization method is novel in using sound measurements of passing ships of which the trajectories are known a priori. This paper is novel in presenting the underwater localization method using RAM and sound measurements of ships moving along known routes. We verify the effectiveness of the proposed localization method utilizing MATLAB simulations. This paper is organized as follows. Section 2 presents the preliminary information of the paper. Section 3 presents the localization method using bearing-only measurements of passing ships. Section 4 presents MATLAB simulations to verify the effectiveness of the proposed localization method. Section 5 provides Conclusions.
# On the Delayed Scaled Consensus Problems
## 1 Introduction  
Multi-agent coordination of interconnected systems has found a diversity of applications in a number of fields, such as sensor networks, vehicle systems, social insects and cyber-physical systems. Consensus as a critical problem for multi-agent coordination aims to design appropriate protocols and strategies for reaching an agreement on a certain quantity of interest depending on the states of all agents. Different from traditional centralized controllers, the designed protocols take advantage of nearest-neighbor rules rendering the multi-agent systems in a distributed network framework governed by the graph Laplacians [1] since each agent can only interact with those within its local area due to limited communication capability. There has been an extensive literature on consensus problems using effective tools such as matrix theory, algebraic graph theory and system theory; see the recent surveys [2; 3] on this wide ranging topics.  
In many practical applications, the states of all agents may achieve consensus on a common quantity, but of their own scales due to the constraints of physical environments. Examples include water distribution systems, compartmental mass-action systems [4] and multiscale coordination control between spacecraft and their simulating vehicles on the ground [5]. As an extension to standard consensus, [PERSON] [6] recently introduced a novel notion of scaled consensus, which permits prescribed ratios among the final convergent values of all of the agents. The scaled consensus offers a less conservative framework, which can be specialized to achieve standard consensus (with all ratios being one), cluster consensus [7], where agents in a subnetwork share a common value while there is no agreement between different subnetworks, and bipartite consensus [8] or signed consensus [9] by adopting appropriate scales.  
Scaled consensus has been studied for a fixed strongly-connected topology in [6; 10] and switching topologies in [11], where the agents are modeled by continuous-time single integrators. Scaled consensus can also be achieved through linear iterations [12; 13]. However, time delay (especially distributed delay) has not been considered. Inspired by the stability analysis for delay systems in [14], we try to investigate the delayed scaled problems and distinguish between two main sources of timedelays, to wit, signal transmission delays and signal processing delays. The contribution of this paper is two-fold. First, new scaled consensus protocols are proposed to accommodate discrete and distributed delays in networks containing spanning trees by extending the delayed complete consensus analysis in [14]. Second, for the undelayed scaled consensus process, we generalize some existing results on scaled consensus in [6; 10; 11]. In particular, we find that the ubiquitous spanning tree condition is both sufficient and necessary for scaled consensus, as well as for the related tracking formation problems on the scaled consensus manifold.
## 2 Previous Work
The whole 3D UASN is divided into mulitpe 3D geographic zones that are also called zone of reference (ZOR). The AUV collects data from the sensor within the ZOR and moves through the user-defined path. The sensors within the ZOR conserve their energy by only waking up at the AUV's visit time. In [29], the authors proposed the ESDR (Event Segregation-based Delay sensitive Routing) and the forwarding process depends upon the criticality level of the sensing event. The data related to the very critical and the critical events is forwarded directly to the base station due to their delay sensitive requirements. However, the normal nodes that generate normal event data with less priority and not delay bound, forward their data packets towards the mobile sinks, which are AUVs and referred as courier nodes (CNs). The delay bound data is forwarded using the forwarding functions that consider the cross-layer parameters including the Localization Free SNR (LFSNR), Energy Cost Function (ECF), Depth-Dependent function (DDF), and Signal Quality Index(SQI). The estimation of those functions is quite complex as well as the end-to-end delay for general category data is very high in the ESDR. In addition to that, the author used the constant depth threshold to restrict the CN's mobility, which is quite difficult to achieve in generic underwater acoustic network scenario. The holding time to guarantee the packet suppression considers the constant value and the estimation of that constant value is impractical in the unpredictable aquatic environment. The sink mobility based schemes are best summarized in the survey in [30]. [PERSON] et al. in [31] proposed Energy-efficient and Void Avoidance Depth Based Routing (EVA-DBR) protocol. Authors claimed that the EVA-DBR is the stateless routing protocol, however, EVA-DBR updates the neighboring node table that is used to select next hop forwarders. The neighborhood table is maintained by periodically exchanging the control packets. Based on the information in the neighboring table, the size of the forwarding zone is adopted. The authors used different thresholds and forwarding ranges, if the number of nodes with lower depth in that forwarding range are greater than the threshold, then minimum forwarding range is used in the data packet. On the contrary, the forwarding range is increased and matched with the threshold until the maximum forwarding range reaches. EVA-DBR minimizes the energy consumption, however, the control packet cost is very high in the dense network and duplicate data packet suppression holding time used does not guarantee the packet suppression. From the above mobile sink based literature review, we have observed that the sink mobility improves the network efficiency in terms of battery power, packet delivery ratio, and so on. Hence, any scheme proposed for the UASN must be tested with and without sink mobility to verify its effectiveness.
## 5 Conclusions
### Limitations and Future Research  
Firstly, the model in this article only considers information transmission defects and maintenance costs in the negative revenue section and has not addressed the security issues caused by the disconnection of connected vehicles. The article assumes that the missing vehicle will be corrected by the driver for abnormal vehicle conditions. During this correction process, abnormal vehicles will not affect surrounding vehicles. Therefore, safety issues should also be considered in future research to prevent abnormal vehicles from causing safety accidents.  
Secondly, the model is established in highway scenarios, with relatively few external influencing factors and no involvement in interference under abnormal weather conditions. Future research should consider adverse external environmental interference.  
**Author Contributions:** P.W.: Conceptualization, Methodology, Software, Formal analysis, Writing--original draft. Y.L.: Conceptualization, Resources, Supervision. N.C.: Methodology, Software, Writing--review and editing. L.Z.: Methodology, Software. W.K.: Methodology, Software. Q.W.: Methodology, Software. G.Q.: Methodology, Software. G.Q.: Methodology, Software. Z.M.: Conceptualization, Resources, Supervision. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Key Science and Technology Projects in the Transportation In-dustry of the Ministry of Transportation [grant no. 2021-ZD2-047]; the Shandong Transportation Science and Technology Planning Project [grant no. 2021B49]; and the Youth Innovation Science and technology support project in Colleges and Universities of Shandong Province [grant no. 2021 KJ058].  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data will be made available on request.  
**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
# Medical Devices for Tremor Suppression: Current Status and Future Directions
## 8 Future Perspectives  
The devices currently studied have employed distinctive mechanistic approaches. The weight of evidence supporting their efficacy challenges the notion that tremors originate from a single, dominant pathway. Additional pathological insights, such as the loss of Purkinje cells in ET [148; 149] and increased central oscillator synchronization in the basal ganglia in PD tremors [150], along with several mechanistic targets of tremor suppression devices, highlight the advances in our understanding of how tremors may be generated. Perhaps the most pertinent pathway implicated in tremors is the cortico-ponto-cerebollo-thalamo-cortical loop, which serves as the basis for successful surgical interventions [21]. These findings suggest an integrative multi-pathway model for tremor pathogenesis. The relevance of these pathways necessitates a further clarification of the complexities and inter-related causes of tremors, which is central to spur the future development of safer and more effective devices for tremor suppression.  
The lack of consensus on the characterization and electrophysiology of tremor previously represented two major diagnostic pitfalls [151]. However, in 2018, the IPMDS task force reviewed the vast uncertainties to update its consensus classification criteria for tremor disorders [1]. Besides ET and PD tremors, it is important to recognize that a wide range of other tremor conditions also affect the upper limbs with varying clinical features and etiologies [1]. Future studies could investigate whether the efficacy of these devices is generalizable to other tremor conditions. As seen in the pivotal Cala ONE trial [70], tremor suppression can, in part, be attributed to the surgical placebo effect. Since the studies of most of these devices were descriptive in design, sham-controlled randomized trials are warranted to confirm their efficacy. Lastly, evaluating the concurrent use of one or more devices, along with pharmacotherapy/lifestyle interventions, may derive insightful data to explain the benefits and overall impact of a multimodal strategy in the management of tremors.
## 3 Blockchain-Enhanced Security and Operational Efficiency in VANETs
### Architecture Overview
#### 3.1.2 Blockchain Layer
These smart contracts execute autonomously, with their conditions predefined by consensus among network participants, thereby enhancing trust [78; 79] and efficiency within the network. Our blockchain platform is specifically enhanced to handle the extensive throughput demanded by real-time vehicular communication. It supports rapid transaction processing and block generation, which are crucial for the instantaneous nature of vehicular communications [12]. The preliminary performance analysis of our proposed blockchain architecture demonstrated a significant reduction in transaction validation time, thus contributing to faster data dissemination. In our simulations, this resulted in a 30% improvement in the overall network throughput compared to traditional VANET systems. Additionally, smart contracts automated many of the routine tasks, thereby further enhancing the system's responsiveness. The event and reputation chains are designed to be interoperable, thereby allowing for seamless data exchange and crossvalidation. This facilitates more comprehensive situational awareness and enhances the overall network security and efficiency. When a vehicular event is recorded in the event chain, it is validated against the reputation scores from the reputation chain. This validation process ensures that only events associated with nodes of high reputation are accepted, thereby enhancing the overall reliability and security of the VANET. Conversely, the reputation chain utilizes the data from the event chain to update the reputation scores of the nodes, thus reflecting their recent activities and behaviors [80]. By integrating these two chains, our architecture achieves a synergistic effect, thereby enhancing both the security and reliability of the VANET. The event chain ensures that all vehicular interactions are securely logged and validated, while the reputation chain provides a robust mechanism for continuously assessing the trustworthiness of network participants [81; 82]. This dual-layer approach significantly mitigates the risks of malicious activities and false data propagation within the network [26]. The dual-layer blockchain architecture presents a novel and effective approach to addressing security challenges in VANETs. By integrating the event chain with the reputation chain, a robust system is established for tracking, verifying, and managing node reputations, which is essential for maintaining the integrity and reliability of vehicular communications (see Figure 6[76]).
## 3 Results and Discussion
### Volatile Compounds
#### 3.4.4 Alcohols
Most C\({}_{6}\)-alcohols were unaffected, with the exception of _cis_-2-hexen-1-ol, which was present at higher concentrations in SCE wines in both years. Among minor alcohols, SCE-21 wines had higher levels of 1-pentanol, 2-decanol, and 2-undecanol than SPA-21 wines, reflecting similar trends observed for the related aldehydes (Table 6). SCE-22 wines exhibited increased concentrations of 2,7-dimethyl-2,6-octaleri-1-ol, 2-methyl-5-nonanol, 1-undecanol, and 1-dodecanol. 3-Ethoxy-1-propanol and 2-nonanol were significantly more abundant in SCE wines across both harvest years (Table 8). SPA wines, on the other hand, showed higher levels of 6-methyl-5-hepten-2-ol, 1-octanol, and _cis_-6-nonen-1-ol in both years, as well as higher levels of 3-octanol, 1-heptanol, 3-nonanol, 3-ethyl-4-methylpentan-1-ol, two 2,3-butanediol isomers, _trans_,_cis_-3,6-nonadeni-1-ol, and 1-decanol in specific years. In 2021 wines, the higher levels of 2,3-butanediol corresponded to the increased levels of acetoin. It is possible that in 2021, the conditions were more favourable for this specific metabolic pathway, which involves converting acetaldehyde to acetoin through the action of pyruvate decarboxylase via the acetaldehyde-TPP complex, followed by
# Evaluation of Noise Levels in a University Dental Clinic
## 5 Discussion
### Limitations of the Study  
Limitations of the present study that may have influenced the results could be the space/distance between dental units, which differs between different clinics and laboratories. Since the environment, devices, and furniture are factors that can magnify the intensity of the noise beyond the dental devices [36], and although statistical differences were not observed between old and new units in our study, further estimation of noise levels should be designed considering distance between units, the existence of prophylactic booths, sound-proof shields, or other furniture among them. Also, the use of new cutting handpieces could provide information on whether it is the type and maintenance of handpieces that influence noise levels. Further research in this field may include assessing the temporary threshold shift after a week-long work schedule. Another question could be whether the number of students working simultaneously with ultrasonic/airotor handpieces could change the upper sound limits in the renovated undergraduate clinics of the department where the compressor and water suction central unit are placed away from the dental operatory and within a metal cabin. Elsewhere, it was suggested that in such cases, the noise levels could be reduced by 75% to 47-60 dB(A) [67]. When suction units are attached to dental chairs, as in this case, the environment is often noisy and needs an exhaust silencer of the open-bore expansion type with interior baffling or shrouding to reduce sound levels below 80 dB(A), as mentioned elsewhere [68; 69]. It should then be examined whether an under-floored suction network connecting all units in the newly renovated undergraduate clinics would account for lower noise levels vs. the renovated postgraduate clinics, where each unit has its own suction unit at chairside. It is important to mention that in this study, no acoustic measurements were performed since both clinics and laboratories are working places with no exaggerated needs for acoustics, as in concert hall areas, to count sound halo and other effects that could possibly interfere with noise levels. Furthermore, no construction materials of the study areas were assessed since some of the clinics were more than 50 years old, and no renovation of building walls has ever been performed since the time of measurements. The next step in this approach would be noise measurements when dental equipment like ultrasonic and/or airotors, known to produce the highest noise levels, could be used in renovated clinics with soundproof construction materials and protective shields. Interesting enough would be to finally check noise annoyance levels and mental consequences in dental clinics, possibly by using the recommendations of the International Commission on Biological Effects of Noise (ICBEN) [69; 70; 71].
# Detection of Crustal Uplift Deformation in Response to Glacier Wastage in Southern Patagonia
#### Study Area  
The SPI has an average width of 40 km and north-south length of 350 km (Figure 1) [27], at elevations between 1000-1500 m a.s.l. (above sea level) [28]. The Equilibrium Line Altitudinal (ELA) at the glaciers of the western slope varies between 800 to 1000 m a.s.l., while at the eastern side, the ELA can reach 1300 m a.s.l. [29]. The large hydrographic basin of this region is the Santa Cruz river basin, including the lakes Viedma and Argentino. The lake Argentino is the largest in Argentina, with an east-west extension of approximately 100 km, an area of 1330 km\({}^{2}\), and a water depth exceeding 600 m near the Upsala glacier front [30]; while lake Viedma presents an approximate length of 80 km east-west, an area of 1088 km\({}^{2}\), and a maximum water depth of 919 m [31]. The region is located on the South American plate bounded to the west by the Nazca and Antarctic plates, forming the triple junction called Chile Triple Junction (CTJ) whose position is at \(-\)\(-\)46.5\({}^{\circ}\) S (Figure 1).