esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
We have successfully constructed an active Ag/PDA/ZnO@GMF SERS substrate utilizing the combination of AgNPs, ZnO nanostructures, and PDA, on a GMF scaffold. This material exhibits both electromagnetic (EM) and charge transfer (CT) effects and has a strong SERS enhancement factor (EF) while also demonstrating efficient catalytic degradation of RhB under UV radiation. We further validated our findings by comparison to Ag/PDA@GMF and ZnO@GMF. The facile construction of the substrate may be attributed to the incorporation of PDA, because the additional oxidation process of catechol functional groups in PDA released electrons to ZnO and thereby lowered the excitation energy. Moreover, the long-range conjugated aromatic core of PDA served as an efficient electron transport or charge redistribution layer between AgNPs and ZnO. Additionally, the 3D steric-construction structure of GMFs offered a high surface area for immobilizing metal NPs. To our knowledge, this is the first report using PDA as an adhesive layer between a noble metal and semiconductor to achieve a significant SERS enhancement factor (of the order of \(10^{10}\)) on a xanthene dye RhB. In addition, SERS-based platforms are desirable to achieve high sensitivity for detection of very small trace amounts of dye, because in conventional methods, the dye takes a long time to produce and grow to the detectable range. SERS-based label-free detection of trace organic molecules in a dilute solution and visualization of their degradation on the designed substrate is an attractive and promising platform for use in monitoring pollutant concentrations in water, thus contributing to a clean and safe environment.  
H.-K.C.: Methodology, Data curation, Formal analysis. P.-Y.L., R.K., Z.-H.W.: methodology, formal analysis, original draft writing and Writing--review and editing. J.C.: methodology and data curation. S.H.: conceptualization, funding acquisition, project administration, and supervision. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the grants from Kaohsiung Armed Forces General Hospital, Taiwan, the Ministry of Science and Technology, Taiwan (MOST 109-2113-M-110-001), and National Sun Yat-sen University, Kaohsiung, Taiwan.  
Not applicable.  
No data availability.  
The authors declare no conflict of interest.
Figure A2: SEM images of substrates with different silver nanoparticle deposition times: (**a**) 2 h, (**b**) 4 h, (**c**) 6 h, (**d**) 8 h, (**e**) 10 h, and (**f**) 12 h.
## 2 Collision Avoidance System
### Communications Module  
Since the above action has been generated through the detection of a risk situation, the assistance system issues a warning to alert any vehicles circulating near it. Hence, once the emergency manoeuvre is selected by the automated vehicle ADAS, a warning is set to those other vehicles that are circulating in the driving area. This signal includes the GPS position, identifier and speed of the signalling vehicle and a timestamp to validate the message confidence. Every vehicle is also synchronized with the others since they equip a GPS receiver and use the GPS time to perform the necessary latency and validity calculus. With this information, the vehicle that receives the emergency signal will show a message in a human machine interface, so the driver is alerted in advance of the risk situation and would have more time to reduce speed if necessary.  
The communications system is based on wireless mesh networks, whose fundamental feature is that their topology can be automatically reconfigured at every instant, while always supporting an available route for the transmission of the information among network nodes in such a way that they form a VANET (Vehicle _Ad-hoc_ Network).  
The Vehicle-to-Vehicle communication mesh devices are Maxfor Inc. MTM-CM3100 gateways based on the TelosB platform. They are used as interface to access the vehicular mesh network. This device works under the TinyOS open code operating system. In order to access the wireless network at 2.4 GHz it uses the IEEE 802.15.4 standard at physical and link level and a mesh routing protocol, which guarantees the desired functionality of the VANET. The protocol implemented in TinyOS for the mesh routing reconfigures the network in accordance with the root mean square (RMS) value of the different network nodes signal. As shown in [61], the latency of the mesh network is less than 1 ms, in direct connection one hop and two hops. The number of lost messages in mobility is 6.25% at speeds up to 50 km/h and the mesh structure is reconfigured only when one node loses the connection with its established route, using the transmission and reception powers as parameters to take this decision.
## 7 Conclusions and Future Directions  
This study introduced efficient, lightweight, and secure symmetric key exchange and remote user verification methods for advanced IoT-driven smart healthcare systems. The approach employs uncomplicated procedures combined with a unidirectional hashing function, XOR operations, and arithmetic calculations for both the session key exchange and remote user verification stages. It offers substantial security against recognized threats like replay attacks, MITM attacks, DoS attacks, and others. Furthermore, we illustrated that our proposed method incurs minimal computational and communication expenses in comparison to existing methods. Specifically, the computational workload was reduced by up to 37.68%, and communication expenses were lowered by up to 32.55%, as contrasted with earlier approaches in this field. Consequently, we conclude that our suggested method is highly suitable for IoT-based smart healthcare scenarios that work with limited resources.  
In future work, we plan to focus on data sovereignty, ethical and legal requirements with data sharing, and environmental costs regarding the CO\({}_{2}\) footprint. Data sovereignty issues will be addressed through access control, data localization, and data encryption. Environmental costs related to CO\({}_{2}\) footprint issues will be addressed through a transition to renewable energy sources such as solar and implementing energy-efficient technologies.  
Conceptualization, methodology, validation, Z.A.; formal analysis, Z.A. and Z.M.; investigation, writing--original draft preparation, Z.A.; writing--review and editing, Z.A.; visualization, Z.M.; project administration, M.I.; funding acquisition, M.I. All authors have read and agreed to the published version of the manuscript.  
The APC was funded by Prince Sultan University, Saudi Arabia.  
The data presented in this study are available in this article.  
The authors would like to acknowledge the support of Prince Sultan University for paying the Article Processing Charges (APCs) of this publication. The authors would like to thank Prince Sultan University for their support. The authors also thank the anonymous reviewers and the editor for their valuable feedback on the paper which helped the authors to improve its quality and presentation.  
The authors declare no conflict of interest.
# Optimization Techniques for a Distributed In-Memory Computing Platform by Leveraging SSD
## 2 Background and Related Research Work
### Related Work
Similarly, [PERSON] and [PERSON] [18] analyze the impact of the most important tunable Spark parameters concerning shuffling, compression, and serialization on the application performance in an empirical manner. They provide extensive experimental results on the Spark-enabled Marenortum III (MN3) computing infrastructure of the Barcelona Supercomputing Center. In contrast to the empirical tuning method, [PERSON] et al. suggest an auto-tuning scheme for an in-memory computing platform [19]. They take the size of the input dataset and 41 configuration metrics as parameters of the performance model. They use hierarchical modeling (HM) to combine a number of individual sub-models in a hierarchical manner and use the genetic algorithm (GA) to search for the optimal configuration. Although the above research works try to reach the optimal performance by tuning parameters of Spark, which is similar to our work, our paper is different from these because we use an SSD-backed memory cache policy to effectively extend the physical memory limitation of a Spark cluster. * **Memory optimization for MapReduce-based data processing:** The authors of [20] analyze in depth the impact of memory efficiency on the performance of the Hadoop-compatible Flame-MR framework. They present several memory optimization techniques to reduce the amount of object allocations and deallocations, decreasing GC overheads and the overall execution time. In our study, we leverage SSDs for improving the performance on the in-memory system. * **Reducing JVM and garbage collection overhead in Spark:** JVM and GC comprise one of the major overheads in the Spark platform, especially when the workloadsuffers from memory limitations. [PERSON] et al. point out that JVM warm-up overhead is one of the major bottlenecks in HDFS, Hive, and Spark platforms [21]. They propose a new JVM that amortizes the warm-up overhead by reusing a pool of already warm JVMs. [PERSON] et al. find that GC-induced pauses can have a significant impact on Spark [22]. Thus, they propose a holistic runtime system, a distributed language runtime that collectively manages runtime services to coordinate GC-induced pauses across multiple nodes. Even though both papers deal with JVM- and GC-related issues in Spark for general cases, our paper assumes that workloads suffer from memory limitations. * **Cache management policy optimization for Spark:** The authors of [23] propose least composition reference count (LCRC), a dependency-aware cache management policy that considers both intra-stage and inter-stage dependency. LCRC can rewrite these inter-stage accessed blocks into memory before its next use. In our study, we leverage SSDs rather than enhancing the cache policy for improving the performance of the in-memory system.
# Metabolism and Regulation of Ascorbic Acid in Fruits
## 2 Metabolic Pathway of Ascorbic Acid
### Regeneration and Degradation of Ascorbic Acid  
Aside from the above biosynthesis pathways, regeneration of AsA through the Foyer-Halliwell-Asada cycle is also an approach for AsA production [55]. Ascorbate peroxidase (APX) catalyzes the conversion of AsA to monodehydroascorbic acid (MDHA), which is then converted to dehydrocosorbic acid (DHA) by a nonenzymatic disproportionation [3]. Ascorbate oxidas (AO) is an ascorbate oxidase, and part of AsA can also form MDHA under the catalysis of AO. Meanwhile, both MDHA and DHA can be converted to AsA by monodehydroascorbate reductase (MDHAR) and dehydrorosorbate reductase (DHAR), respectively [3]. Much evidence has verified that DHAR positively controls AsA production in some horticultural crops, such as tomatoes and potatoes [56; 57]. Although _MDHAR_ also governs AsA regeneration, the expression level of _MDHAR_ does not always coincide with AsA content. Transgenic plans are overexpressing MDHAR to decrease AsA accumulation, while knockdown of _MDHAR_ gene decreases the AsA content [56; 58; 59]. However, overexpression of acerola MDHAR in tobacco significantly increases AsA content [60].  
AsA regeneration is often closely associated with environmental stresses. AsA will be degraded through multiple pathways in apoplast when supernumerary AsA is no longer needed in plants [48]. On the one hand, DHA is hydrolyzed to 2,3-diketo-gulonic acid, which is then hydrolyzed to multiple products, including L-threarate, oxalate, and tartaric acid [61; 62; 63]. On the other hand, DHA can be oxidated directly to L-threarate and oxalate [64]. Moreover, DHA can also be oxidated to 4-O-oxyl-L-threonate, which is then oxidated to L-threarate and oxalate [64]. Tartaric acid is an essential determinant of the fruit quality of the grape. Still, it cannot be detected from degradation products, indicating that oxidation of DHA is the primary process involved in AsA degradation [65].
# Streetlight Control System Based on Wireless Communication over DALI Protocol
## 3 System Architecture
### Supervisory Control and Data Acquisition System  
A SCADA (supervisory control and data acquisition) system was developed to control lighting systems. This application is executed on an embedded industrial computer in each wireless network of a section of the lighting network. The computer communicates directly with the coordinator node of the wireless network. Another SCADA system has been planned to control more than one section of the lighting network. This central SCADA system communicates with each local SCADA system. The central SCADA system collects the information from the local SCADA. The local SCADA is actually the one in control; as a result, it will be the one described below.  
The software used for the execution of the SCADA is the integrated development environment (IDE) NetBeans [37]. NetBeans is a free product without any restrictions on its use. It was mainly designed to be used with the Java programming language. In this way, it can be used in any Java virtual machine (JVM), no matter the architecture of the computer used.  
By means of SCADA, a user with the appropriate licenses has both individual and collective control over the lamps. The coordinator (who is connected to the computer) deals with forming/ managing the tree wireless network, so that an intermediate router node will be used to reach a lamp if the coordinator is unable to do so. Once all of the luminaires have been located, their status may be viewed and modified, making it also possible to specify different modes of operation from the interface. Figure 5 shows one of the windows of SCADA.  
As an example, Figure 6 shows the information of a selected street lamp, which allows the user to know:  
* Whether the light is switched on or off.
* Its current regulation setpoint.
* The existence of limit error events.
* The existence of lamp error events.
* The existence of ballast error events.
* The reset state.
# Optimizing IoT Video Data: Dimensionality Reduction for Efficient Deep Learning on Edge Computing
## 3 Materials and Methods
### Dataset  
The Visual WetlandBirds Dataset [11] consists of videos of birds from the Valencian region, each depicting different actions. The dataset consists of 2765 video frames and is distributed into 1834 samples for training, 440 for validation, and 491 for testing. This distribution was designed taking into consideration the bird species in the video, as well as the action performed in it. Furthermore, this division was not limited to bird species and actions but also considered the original video source, which was segmented into smaller video frames. This approach ensures that videos are separated based on factors such as the recording camera, the day of recording, and the time of day. These videos are annotated with the bird species and the actions performed. The videos encompass 16 frames, with three color channels per frame and a resolution of 224 \(\times\) 224 pixels. This dataset establishes a baseline for the classification of bird behaviors using 3 DCNNs and Video Transformers. The models trained end-to-end include ResNet3D, S3D, Video Swin Transformer, and MViTv2.
# Cognitive Routing in Software-Defined Underwater Acoustic Networks
## 3 Proposed Cognitive Acoustic Software-Defined Underwater Network
Any controller first calculates the path duration (s) of all paths \(P\) between source and destination as follows:  
\[PD_{p}=min(LDP_{1,p},LDP_{2,p},...,LDP_{TH,p}) \tag{3}\]  
where \(p=1,...,P\), \(TH\) is the total number of hops making up each path between source and destination, and \(LDP_{i,p}\) (link duration prediction) (s) is calculated as:  
\[LDP_{ij}^{ch}=\frac{L_{s}}{r_{ij}^{ch}}+GD_{ij}+ENC \tag{4}\]  
where \(ENC\) is the expected node connectivity, which can be measured from all the beacon messages a node receives from its neighboring nodes within transmission range in time \(t\), i.e., \(\frac{1}{hello\ messages/t}\). This connectivity parameter helps the network to avoid sparse conditions for both channel and relay selection. Finally, the controller finds the best route, \(R\), to the destination:  
\[R=min(PD_{p}) \tag{5}\]  
The source node, after receiving the best route, starts transmitting data. As this is a cognitive routing scheme, minimizing the path duration enhances the stability of the network that has a high data rate with low delay. This is because the unique challenges of underwater environment along with mobile PUs increase the chances of link fragility. Therefore, selecting the route with high data rate and low delay sustains stability in underwater networks. If any intermediate node fails to sustain stability, it repeats the above procedure to reach a nearby LC without sending the request packet back to the source node. Consequently, the SDN approach reduces delay by reducing the number of control messages.
## 2 Flexible Graphene RF Transistor Fabrication  
Figure 1 shows the typical device structure of our fabricated flexible graphene field-effect transistors. GFETs are typically prepared on smoothened commercial 125 um-thick polyimide (Kapton) films. Gate fingers (evaporated 2 nm Ti/40 nm Pd) and gate dielectric films (prepared by atomic layer deposition of 10 nm-thick Al\({}_{2}\)O\({}_{3}\) or hexagonal boron nitride films) are prepared by electron-beam lithography using JEOL-6000 FSE (JEOL USA Inc., Peabody, MA, 01960, USA). Chemical vapor deposited high-quality graphene films grown on commercial Cu-foils or films are transferred via the conventional wet-transfer process using ammonia persulfate as the Cu-etchant [10]. Active channel area of graphene and metallic electrodes for source and drain contacts are subsequently patterned via additional electron-beam lithography processes. Low power oxygen plasma is used to etch redundant graphene areas and electron-beam evaporation of 2 nm Ti/50 nm Au is used as the contact metals. Figure 1a is 3D view of freestanding polyimide film with multifingered GFET. Figure 1b is the enlarged optical image of a representative GFET fabricated on polyimide substrate. Devices with channel length of 0.25 um and an effective width of 60 um (six fingers with 10 um width) are prepared for electrical measurements, which can afford GHz high frequency performance.
# Towards a Cyber-Physical Range for the Integrated Navigation System (INS) System (INS)
## 2 Related Work
### Cybersecurity of the INS  
Shipboard cybersecurity has become a significant concern lately, with the IMO and several other organizations providing guidelines on how to address it. Accordingly, several relevant research articles have appeared in the literature. In particular, a cybersecurity-related survey on the INS was conducted in [11], where different aspects, such as operating systems (e.g., Windows and Linux), networking (e.g., ethernet, Controller Area Network (CAN) bus), internet connection possibility, sensor integration, Electronic Chart Display and Information System (ECDIS) controlled autopilot of a total of 22 INSs in the market were investigated.  
The authors of [10] revealed cyber vulnerabilities of the INS on a roll-on/roll-off (RO-RO) type of vessel. The vulnerability analysis was carried out by using the Nessus Professional vulnerability scanner [39]. After scanning the INS, the scanner produced a report consisting of 27 pieces of information, four of which were classified as vulnerabilities of the system. Other potential cyber risks onboard, such as crew awareness, cybersecurity procedures, and unauthorized access were also investigated in [10]. Cyber threats and vulnerabilities in the Integrated Bridge System (IBS) are presented in [40]. Several bridge components including AIS, Ship Security Alert System (SSAS), anemometer, echo-sounder, speed log, and such are described briefly. The paper is based on historical evidence including cyber incidents, experimental studies, malfunction and misuse of the equipment. Historical events are investigated and collected data are classified by the authors. According to the study, the number of cyber incidents increased in recent years. State-sponsored cyber attacks involving the INS were investigated in [41].  
Bridge simulators are used for the training of cadets and seafarers to improve their navigational skills. Moreover, researchers from Tallinn University of Technology also used bridge simulators for maritime cybersecurity training [42], and researchers from Plymouth University discussed the combination of a cyber range and a full mission bridge simulator for technical aspects of cybersecurity research [43]. Further, researchers from Genova University announced that a full mission bridge simulator will be used for cybersecurity studies [44]. However, although existing bridge testbeds have been used for some cybersecurity-related purposes such as the above, they have not been used for assessing the cybersecurity posture of an INS. To do so, more than the existing functionality is required.
## 1 Introduction
They present their results for the height of the clear liquid as a function of the flow ratio \(\Psi\) and show that the height of the clear liquid increases as the flow ratio \(\Psi\) increases. In the same study, they also plot that the tray pressure drop increases by increasing the gas kinetic factor, Fa. [PERSON], [PERSON] et al. (2017) [8] studied the effect of the gas velocity on the average height of the clear liquid that is on the tray; their experimental study was conducted in a dual-flow sieve plate scrubber. The authors found that at constant liquid flow rates, the average clear liquid height increased as the gas loading factor (Fs) was increased. [PERSON], [PERSON] et al. (2017) [8] examined the effects of gas and liquid flow rates on the percent removal of H\({}_{2}\)S at H\({}_{2}\)S input concentrations of 50-300 ppm. Their experiments were performed in a lab-scale three-stage dual-flow sieve plate column scrubber. The authors concluded that the percentage of H\({}_{2}\)S removal increases as the gas flow rate is increased. [PERSON], [PERSON] et al. (2018) [9] analysed the effects of the Fs factor on dry pressure drop, wet pressure drop, clear liquid height, and froth height. Their experiments were conducted using a folding sieve tray (FST), which consists of double-perforated oblique planes folding at a specific angle. The author found that the dry pressure drop, wet tray pressure drop, clear liquid height, and froth height increased when the Fs factor of the gas was increased, while the clear liquid height decreased when the Fs factor was increased. There are numerous studies in the literature investigating the effect of parameters such as temperature, flow rate of the solvent flow rate of the inlet gas on CO\({}_{2}\) absorption, but the study of the correlation between the hydrodynamic characteristics of the sieve tray and CO\({}_{2}\) absorption is still limited. The objectives of this study are summarized as follows:1. To experimentally investigate the effect of inlet gas flow rate on the hydrodynamic properties of the sieve tray column, such as total tray pressure drop, wet tray pressure drop, dry tray pressure drop, clear liquid height, liquid holdup, and froth height, an absorber test rig was constructed and operated. 2. Investigating the influence of inlet gas flow rate on the hydrodynamic characteristics of the sieve tray and its effect on the performance of a sieve tray absorber for CO\({}_{2}\) capture using water as the absorbent.