esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions  
Cooperative communication refers to selecting multiple forwarding nodes for cooperative communication when forwarding data, which can improve the reliability of transmission; intelligent mobile agent can collect data in the network, and integrate, compress and encrypt data at the same time, which provides additional flexibility and new functions for the Internet of things network layer. The networks layer cooperative communication and intelligent agent routing algorithm of the IoT are studied in this paper. A new cooperative communication algorithm is proposed. K cooperative nodes are selected for cooperative communication in each hop. The directional source group algorithm based on multi-intelligent agent is studied by using the idea of software definition network. The size of the route is controlled by the angle of the directional sector. In the aspect of intelligent agent, a directional source grouping algorithm D-MIP is proposed, which divides the network into several directional sectors. The source node of the directional sector is assigned to a route. It is shown by a large number of simulations that the D-MIP algorithm can save more energy consumption and time delay than other algorithms. In the future, we will work to solve the problem of dynamic sector angle selection.  
In addition, the main experimental results of cooperative communication are based on an independent protocol layer. Many cross-layer theoretical studies, such as cross-layer optimization, have not been proved in experiment. In the aspect of intelligent agent, with the movement of nodes, the data of intelligent agent continuously increases. This causes an increase of forwarding energy consumption of the subsequent source node, which shortens the life of the entire network. It is worthwhile to study the technology of intelligent agent data unloading.  
Data curation, Y.Z. ([PERSON]) and Y.Z. ([PERSON]); Investigation, Y.Z. ([PERSON]); and X.Y.; Methodology, Y.Z. ([PERSON]); Project administration, Y.Z. ([PERSON]); Software, Y.Z. ([PERSON]); and X.Y.  
This research received no external funding.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Rule Inference Using Prolog  
In this section, we present examples of results from a set of NAARs that were simply entered into Prolog as the prototype to inference rules and obtain conclusions in accordance with PRs that we obtained. As mentioned above in Section 2, in the final extraction, NAARs are treated as facts in rule-based systems. In PRSs, note that it is possible to deduce new final conclusions by creating a chain and linking two or more rules through a predicate logic approach or rule of inferences as long as the rule chains are non-circular. For instance, in Figure 7, Prolog was asked to give all possible conclusions for a specific query condition of an elderly person who is overweight, i.e., (_Age : Elderly \(\wedge\) BMI : Overweight_). It shows that Prolog can give the user several possible conditions through reasoning or inference rules.  
Figure 6: Screenshot of command window MATLAB after circularity checking.  
Figure 7: Example of rule inference through PROLOG.  
As shown in Figure 7, Prolog shows several possible conclusions for the given conditions (premises). The results imply that elderly patients who are overweight might be likely to have hypertension type 2 and also potentially to suffer from abnormalities of the brain. Furthermore, another conclusion shows that patients with the given condition are also likely to have blood sugar (fasting glucose) at a prediabetic level and an abnormal MRI, which are the results of the inference rule chain (rule 366 \(\rightarrow\) rule 375 \(\rightarrow\) rule 394) using hypothetical syllogism, as shown in Table 10. In addition, patients with this condition also potentially have a total cholesterol (TC) level that is borderline high and an abnormal MRI, which were derived from rule 402: \(\left[A:
## 2 Materials and Methods
### Introduction to the WACCM4 Mode  
The WACCM4 mode is a three-dimensional global atmospheric mode developed by the National Center for Atmospheric Research [54; 55]. This mode adopts the finite volume dynamic framework, with the calculation approach structured as follows: The calculation area is divided into a series of non-repetitive control volumes, with a control volume around each grid point. In this way, the governing equations can be obtained for each grid point and then solved jointly. Therefore, the equation is integrally conserved at any volume. The height of the WACCM4 mode extends from the surface to the lower thermosphere (approximately 145 km), which can effectively reproduce the dynamic, radiation, and chemical processes between the troposphere and stratosphere. It also describes the chemical reaction of the mesosphere and the ion chemistry of the lower thermosphere, etc., meeting the experimental requirements [56]. The horizontal resolution of the mode selected in this study is 1.9\({}^{\circ}\)\(\times\) 2.5\({}^{\circ}\), and the vertical resolution in the tropical tropopause and lower stratosphere is 1.1-1.4 km.  
Statistics of Different Types of EN Events and Analysis of Their Corresponding Characteristics of the Ozone Valley over the TP
# Evaluation of Ride Comfort under Vortex-Induced Vibration of Long-Span Bridge
###### Abstract  
The increasing number of suspension bridges has led to designs favoring greater length and flexibility, resulting in a common problem of vortex-induced vibration. While vortex-induced vibration typically does not cause structural damage, it diminishes the bridge's fatigue resistance and has a detrimental impact on ride comfort. Additionally, this study introduces a road-bridge-vehicle vibration model, proposing an evaluation method for assessing ride comfort during vortex-induced vibrations in long-span bridges. This method features simplified modeling and swift calculations, circumventing the need for intricate finite element modeling and iterative solving. Furthermore, it evaluates ride comfort for vehicles crossing a prototype long-span suspension bridge using the Overall Vibration Total Value (OVTV) and Motion Sickness Incidence (MSI) criteria. This study also analyzes the influence of various parameters on OVTV and MSI, including vehicle speed, road grade, vortex-induced vibration frequency, and amplitude. It establishes a reference limit for vortex-induced vibration amplitude based on OVTV and MSI values. Moreover, the study substantiates that, within the context of vortex-induced vibration, the MSI value is more suitable for evaluating driving comfort compared to the OVTV.  
long-span bridge; vortex-induced vibration; ride comfort; motion sickness +
Footnote †: journal: Applied sciences  
Article  
Evaluation of Ride Comfort under Vortex-Induced Vibration of Long-Span Bridge  
[PERSON]  
1 National Key Laboratory of Bridge Intelligent and Green Construction, Wuhan 430034, China; [EMAIL_ADDRESS] ([PERSON]; [EMAIL_ADDRESS] ([PERSON]); [EMAIL_ADDRESS] ([PERSON]; [EMAIL_ADDRESS] ([PERSON]); [EMAIL_ADDRESS] (Y.J.))  
11 National Key Laboratory of Bridge Intelligent and Green Construction, Wuhan 430034, China; [EMAIL_ADDRESS] ([PERSON]; [EMAIL_ADDRESS] ([PERSON]); [EMAIL_ADDRESS] ([PERSON]; [EMAIL_ADDRESS] ([PERSON]); [EMAIL_ADDRESS] (Y.J.))  
2 Key Laboratory of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin 150090, China; [EMAIL_ADDRESS]  
3 Key Laboratory of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin 150090, China  
4 School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China  
* Correspondence: [EMAIL_ADDRESS]; Tel.: +86-451-8628-2068
# Cybersecurity Requirements for Industrial Machine Control Systems
## 5 Case Study--Examples of Determining SLs of Safety Functions Implemented in Machine Safety Systems
### Example 4--Machine Control System: Category 2, PLC; Cybersecurity SL-T 2  
Figure 11 shows a turntable protected by a type 2 light curtain according to IEC 61496-1 [26]. The machine makes slow rotary movements (which implies that the danger can be avoided (parameter P1)). The rotary movements create shear points, with the implication that potential injuries could be severe (parameter S2). The user enters the danger zone several times per shift. This implies the F1 parameter is used. Taking into account the aforementioned characteristics, PLr = c is required.  
The light curtain is connected to a programmable safety unit (Figure 12) and is cyclically tested by it. However, not all faults can be detected. Therefore, the highest diagnostic DC cannot be achieved. The auxiliary contact Q1 is included in the feedback loop. The main and auxiliary contacts of the contactor are mechanically connected. When a fault occurs and is detected, the programmable safety relay is able to indicate the fault with a red lamp.  
Figure 10: Example of circuits implementing the process operations of the machine and the safety system responsible for the emergency stop to ensure that the PLc level is achieved (own elaboration).  
For the circuit implementing the presented function of detecting the violation of the danger zone from Figure 12 with the assumptions described above, protection against cyber-attack is required. The required security level takes SL-T 2 (medium level).
# Biogenic Nanoparticles: Synthesis, Characterisation and Applications
## 2 Biogenic Synthesis of Nanoparticles
### Characterisation of Nanoparticles  
Nanoparticles have unique properties and features, which make them useful for numerous applications. It is crucial to assess them through extensive characterisation, particularly for biomedical applications, to be able to ensure them fit for purpose. This is achieved by using various techniques and equipment that can provide the required information. The most commonly used techniques include dynamic light scattering (DLS), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Fourier transform infrared (FT-IR) spectroscopy, Raman spectroscopy (RS) and scanning and transmission electron microscopy (SEM/TEM). These techniques are used in studying nanoparticle size, shape, structure, surface properties and interactions with materials such as human tissues. Table 4 shows a summary of some of the methods used to characterise the physicochemical properties of nanoparticles. For a detailed review of nanoparticle characterisation techniques, it is suggested to read the following review paper by [PERSON] et al., \"Characterisation techniques for nanoparticles: comparison and complementarity upon studying nanoparticle properties\" [88].  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Nanoparticle** & **Algae** & **Application** & **Reference** \\ \hline Silver & _Portieria hortenmanntii_ & Antibacterial & [82] \\ Silver & _Botryococcus brauntii_ & Catalysis & [83] \\ Gold & _Caulerpa racemosa_ & Biomedical & [84] \\ Iron oxide & _Colpomenia sinuous_ and _Pterocladia capillaca_ & Antibacterial & [85] \\ Gold & _Egregia_ sp. & Biomedical & [86] \\ Gold & _Cystoseira bacata_ & Cancer & [87] \\ \hline \hline \end{tabular}
\end{table}
Table 3: List of algae for nanoparticle production.
# Automated Detection of Gastric Cancer by Retrospective Endoscopic Image Dataset Using U-Net R-CNN
## 2 Methods
### Initial Detection  
We extracted the candidate regions for early GC from endoscopic images. For this task, we employed U-Net, a semantic segmentation technique [18], which was first proposed in 2015 as a method for extracting cell regions in microscopic images and widely used in fields other than medical imaging since. The network structure is shown in Figure 2. U-Net consists of five convolutional and pooling layers, followed by five encoder layers (upscaling layers). When an image is given to the input layer, the encoder layer in the first half extracts the features of the image. Then, the decoder layer in the second half outputs a segmented label image based on the extracted features. In addition, the encoder and decoder layers are connected to each other and the high-resolution information from the encoder layer is delivered directly to the decoder layer on the other side, thereby increasing the resolution of the label image. U-Net provides an initial candidate region for early GC corresponding to the input image. As for the U-Net parameters, the Dice coefficient was used as the loss function (the definition of the Dice index is described in Section 2.6), with the Adam algorithm [19] as the optimization algorithm, 0.0001 as the learning coefficient, 100 as the number of training sessions, and 8 as the batch size.
## Modeling and Analyzing the Energy Efficiency Using the Proposed Approach
### Modeling the Energy Efficiency in Each Cluster
* A comparison of rules 11, 15 and, 18 shows that similar homes in different areas have different energy efficiencies. The study of climatic conditions shows that the groups of areas that are located in one rule are not similar in terms of temperature and have different climates. Thus, it cannot be said that just the similarity or the difference in weather has led to different energy efficiencies. However, in this cluster, households living in Wales have generally a better energy efficiency. * In the rules 13 and 14, newly-built houses are noted in good energy efficiency groups. It is important to say that newly-built flats have the best efficiency. In fact, the type of house structure is not ineffective in the energy performance.
# Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information
## 4 Simulation Results  
We considered a heterogeneous evolution situation, illustrated in Figure 1, in which area 2 was covered by both an IEEE 802.16-based network (such as WIMAX (World Interoperability for Microwave Access)) and an IEEE 802.11-based network (such as WLAN (Wireless Local Area Network)), while the rest was covered only by WIMAX. For WIMAX, we assumed the transmission range was 500 m and its saturation bandwidth was 50 MHz (i.e., \(W_{1}=50\)), while, for WLAN, the transmission range was 100 m and its transmission rate was 11 MHz (i.e., \(W_{2}=11\)). The number of users in each area was 10. Practically, mobile users in the same area had similar influence factors to their QoS experience. Thus, we can study the follower game with two classes of users; users covered by multi-networks and the other users covered only by one network. Without loss of generality, the coverage area 2 is a hot spot region where the mobile users can be served by all of two networks and obtain more network resources. Thus, we assumed \(\alpha(2)=2\) for all users in area 2 and \(\alpha(1)=1.5\) for users in area 1.  
To prove the accuracy of the simulation, we adopted some key parameters from paper [22] to model the proposed Stackelberg game. We set the channel gain regarded as user's type, which was uniformly distributed, ranging from 0 to 1. The transmit power was assumed as \(p_{i}=1\)\(i\in\{1,2,\ldots,n\}\) and the noise power was \(\sigma_{0}=0.8\). We set other parameters as \(\beta_{j}=1\), \(\mu_{j}=0.1\), \(j\in\{1,2,\ldots,m\}\), and \(\lambda_{i}=0.1\), \(i\in\{1,2,\ldots,n\}\). At the beginning of the algorithm iteration, the initial strategies of users and networks were respectively set as \(q_{ij}=0.1\), \(b_{j}=0.1\) for all \(i\) and \(j\), where the bandwidth price was assumed as a normalized number.  
Figures 2 and 3 respectively show the utility curves of mobile users and networks.  
Figure 2 shows the utility of one mobile user in area 2, which was plotted when given the pricing strategies of two networks. As illustrated in this figure, the utility curve shows one and only one peak with the iterations of the user's bandwidth requesting strategy. Moreover, as described in Section 3, the mobile users in area 1 had same objective functions but different strategy scopes with the users in area 2, thus, similarly, one and only one peak can be obtained on the utility curve of a user in area 1.  
Figure 3 illustrates the utility curve of WIMAX changing with its pricing strategy when given all mobile users' bandwidth requesting strategies in the follower game. The above results prove the existence of both BNE in the follower game and Nash equilibrium in the leader game, which can also be proved by the description in Section 3. In the following section, we analyze the obtained performances in the follower game and leader game, respectively.  
Figure 3: Utility of WIMAX with the bandwidth pricing strategy.  
Figure 2: Utility of mobile users with the bandwidth requesting strategy.
## 4 Simulation Results
### Source Specification/Requirement Analysis  
Due to the constraints in satellite QKD communications, such as the signal loss that takes place in free-space transmission due to turbulence-induced phenomena, as well as the limited time window for satellite visibility, the number of single photons that can be securely exchanged between two parties are limited. This limitation affects the efficiency of privacy amplification and error correction processes, which are crucial for ensuring the security and integrity of the keys. In space-based QKD, where satellites are used to distribute keys between ground stations over vast distances, the finite key size imposes additional challenges [41].  
In the following sub-section, the effect of the finite key size effect in various orbits is studied. As described above, a specific block size is used for the secure key distillation. Small block sizes are unable to provide secure key distillation when accounting for the finite key size effects, and since different orbits provide different communication time windows and link budgets, different systems requirements should be considered. For this sub-section, only tip-tilt correction was assumed for the cases in which fiber coupling was considered. In what follows, the minimum requirements for enabling key distillation over a single satellite pass in LEO, MEO, and GEO orbits in terms of Alice's emission rate and iQBER are examined.
# 5G New Radio Open Radio Access Network Implementation in Brazil: Review and Cost Assessment
## 6 Open RAN Costs in Brazil
### Total Cost of Ownership (TCO)  
TCO is a cost assessment metric that aims to calculate the assets related to the mobile network infrastructure. This metric addresses the actual cost by attributing it to the management and infrastructure of telecommunications, comprehensively considering initial capital and operating costs, among other components that complete a base cost estimate [53]. Regarding estimating the base cost, the TCO works according to some requirements, which together form the total assessment model. These requirements include the costs of equipment purchase, installation, infrastructure, energy, maintenance, and support, among others [53]. TCO covers two metrics, details of implementation and operation parameters: CAPEX, which represents the costs related to the acquisition and implementation of equipment, and OPEX, which means the costs associated with energy consumption, physical space renting, maintenance, and risk management of a telecommunications infrastructure.  
For CAPEX and OPEX, the following costs participate in this calculation:  
* RU costs, DU costs, CU costs;
* 5G network core cost;
* Equipment cooling costs;
* Antenna tower construction costs.  
OPEX
* Electrical costs;
* Operation and maintenance costs;
* Equipment and site rental costs;
* License and SW costs and updates;
* Cost of renting an area for the sites.  
The cost in Open RAN architecture is not presented as equipment but rather as the virtualization of the elements, servers that host the virtualized solution, and the rental or construction of sites for the data centers depending on the number of Open RAN sites, DU sites, CU sites, and the location of the virtualized core of the network. It is also possible to predict the number of servers for each virtualized module of the network and the number of racks needed to organize these servers within the data center.  
The _backhaul, midhaul_, and _fronthaul_ interconnection can be customized using other technologies, such as radio links or diversity in the optical transmission medium. For this example, we demonstrate the traditional model of fiber optic connection between the RAN elements.
# Fault-Resilient Manufacturing Scheduling with Deep Learning and Constraint Solvers
## 7 Case Study and Results
### Results and Discussion
#### 7.4.4 Discussion of Results  
The comparative analysis between EDD and PFAS reveals several significant insights. The overall result is shown in Table 7. In the fault-free environment, both methods demonstrated identical performance across all metrics, with Machine Group A showing 100% utilization, Machine Group B at 54.5%, and Machine Group C at 83.3%, validating their basic scheduling capabilities.  
In the fault-present scenario, PFAS showed notable advantages over EDD through its predictive fault avoidance and resource allocation strategies. While both methods experienced the same total completion time of 14 time units, PFAS achieved an 8.3% higher due date compliance rate (83.3% vs. 75%). This improvement was primarily achieved by preventing cascading delays that occurred in EDD due to rework operations. For instance, in EDD, Job_10's rework led to delays in Job_02 and Job_07, whereas PFAS avoided such chain reactions by proactively scheduling jobs on alternative machines during predicted fault periods.  
\begin{table}
\begin{tabular}{l l c c c} \hline \hline
**Performance Metric** & **Method** & **Baseline** & **With Faults** & **Improvement** \\ \hline Total Completion Time (time units) & EDD & 11 & 14 & - \\  & PFAS & 11 & 14 & 0\% \\ \hline Due Date Compliance (\% of jobs) & EDD & 100\% & 75\% & - \\  & PFAS & 100\% & 83.3\% & 8.3\% \\ \hline Machine Utilization (by group) & EDD & A:100\% & A:75\% & - \\  & & B:54.5\% & B:42.9\% & - \\  & & C:83.3\% & C:57.7\% & - \\  & PFAS & A:100\% & A:75\% & 0\% \\  & & B:54.5\% & B:47.6\% & 4.7\% \\  & & C:83.3\% & C:83.3\% & 25.6\% \\ \hline Number of Rewords & EDD & 0 & 4 & - \\  & PFAS & 0 & 0 & 100\% \\ \hline \hline \end{tabular}
\end{table}
Table 7: Performance comparison: EDD vs. PFAS.  
Figure 7: PFAS scheduling results with fault avoidance.  
Machine utilization was particularly improved in PFAS through efficient alternative resource allocation. Machine Group C maintained 83.3% utilization compared to EDD's 57.7%, representing a 25.6% improvement, mainly by redirecting Job_12 to Machine_C2 during Machine_C1's predicted fault period. Machine Group B also showed better performance under PFAS with 47.6% utilization compared to EDD's 42.9%, a 4.7% improvement. Most significantly, PFAS completely eliminated the need for rewards, while EDD required four rework operations, including critical jobs such as Job_10, which required 6 time units of rework across its tasks.  
These results demonstrate that PFAS effectively maintains scheduling efficiency in fault-prone environments while matching EDD's performance in fault-free conditions. The improvement is particularly notable in scenarios with complex task dependencies and multiple machine alternatives, where PFAS's predictive capabilities can effectively prevent both direct delays from reworks and their subsequent cascading effects on dependent tasks.