esa-sceva/satcom-chunk-collection huggingface dataset:
# Model Experimental Study on De-Icing Method of Bridge Pylon Beam Based on Electric Heating
## 5 Conclusions  
In order to solve the icing problem of bridge pylon beam, a novel heating system was designed, and de-icing tests of the scale beam model were carried out. By comparing the anti-icing effects of the novel heating system under different conditions, the recommended anti-icing strategies were given, including the critical temperature required for the heating system to achieve anti-icing, the pre-heating time, and the applicable environmental range. The results of the research can provide a reference scheme for the de-icing problem of bridge pylon beams. The main conclusions are as follows:  
1. By pre-heating the novel heating system for a certain time, the surface of the beam can be prevented from freezing. Compared with the passive de-icing method, the pre-heating anti-icing method is more efficient and safer and is more suitable for bridge pylon beam de-icing.
2. The short pre-heating time will lead to icing in some areas of the novel heating system, and a longer pre-heating time will cause energy waste. When the pre-heating time exceeds 7 min, the entire anti-icing process can be ice-free.
3. When the wind velocity increases to 5 m/s, it is safer to shut down the novel heating system and use the passive de-icing method at the end of icing.
4. The time required to complete the de-icing is independent of the amount of icing, and the de-icing can be completed within 1 h. Combined with traffic control, the passive de-icing method can also achieve the purpose of eliminating the hidden danger of beam icing.  
The authors declare no conflict of interest.
## 4 Conclusions  
1. Based on the transient two-phase drift flow model with wellbore-formation coupling, the changes of the bottomhole pressure, gas holdup distribution and wellhead flow parameters during an underbalanced pressure gas kick and gravity displacement gas kick, are simulated and analyzed. Although both exhibit an increase in pit gain and a decrease in bottomhole pressure, there is a difference in the rate of change in the bottomhole pressure and pit gain.
2. The DTW algorithm is used to calculate the DTW distance between the measured outlet flow curve and the simulated curve, and the degree of similarity between them can be obtained. Then, the similarity between the curves is used to identify the type of gas kick. By using the feature, is it understood that the underbalanced pressure gas kick and gravity displacement gas kick present different characteristics on the outlet flow curve. With the increase of time series data, the judgment effect is better.
3. The method proposed in this paper can greatly reduce the identification time, and the dependence on drilling equipment is not high, which is not only suitable for managed pressure drilling but also for conventional drilling.
4. Using the dual drive of knowledge and data, can effectively improve the efficiency of the model identification. Field example simulations show that this method can identify the type of gas kick, based on real-time surface measurement parameters and provide a basis for taking targeted well control measures.  
Conceptualization, H.Y. and Q.L.; methodology, M.S.; software, M.S.; validation, M.S., H.Y. and H.C.; formal analysis, M.S.; investigation, W.L.; resources, W.L.; data curation, H.C.; writing--original draft preparation, H.Y.; writing--review and editing, H.Y.; visualization, M.S.; supervision, Q.L.; project administration, Q.L.; funding acquisition, Q.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the China National Key Research and Development Project (2019 YFA0708302).  
Not applicable.  
The authors declare no conflict of interest.
## 5 Conclusions  
In this paper, to improve the access number of ground terminal users of the S-IoT under the condition of limited frequency resources, the MHSTFC-UD is established. Users are distinguished in the four dimensions of space, time, frequency, and code. The central area and edge area are divided in each sub-beam, and the edge area is used as a protection interval. By dynamically adjusting resource allocation and beam layout, the number of user accesses is increased by 241 to 1585 times compared to the traditional method. Moreover, compared with fixed resource allocation, the dynamic resource adjustment scheme based on the user distribution can increase user access by about 11.5% to 33.1%. However, when users need to send multiple short or long messages during the time when the satellite passes overhead, they will occupy the channels of other users, resulting in a certain reduction in the user access of this model. Overall, compared with the traditional method, user access can still be increased by one to two orders of magnitude.  
Conceptualization, Q.L. and L.C.; methodology, Q.L.; software, Q.L.; validation, Q.L.; formal analysis, Q.L.; investigation, Q.L.; resources, Q.L.; data curation, Q.L.; writing--original draft preparation, Q.L.; writing--review and editing, Q.L. and L.C.; visualization, Y.X; supervision, L.C. and S.L.; project administration, L.C.; funding acquisition, L.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available upon request from the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.  
Figure 7: The number of actual users accessing to the system changes with the total number of users under the beam.
# Security Analysis of the MQTT-SN Protocol for the Internet of Things
## 4 MQTT-SN Baseline Scenario  
The first step in performing a security analysis of the MQTT-SN protocol in order to test attacks and evaluate their impact is to define a legitimate scenario without attacks and evaluate its performance. This scenario is referred to as the baseline. This is important because it makes it possible to compare the impact of each attack (which exploits a shortcoming in the protocol) on the system against the baseline. The evaluation can be focused on features such as packet size, packet rate, etc., and, on that basis, try to determine the impact of the attacks discovered.  
The proposed baseline scenario is composed of six devices: one is defined as the broker and the rest as regular devices (which perform the function of a simple sensor to acquire data to be sent to the broker). Within this set of regular devices, the baseline scenario includes one device with certain privileges, which is subscribed to a confidential topic, and four others without privileges. The overall behavior is quite simple: each non-privileged mode is subscribed to a topic referred to as _/topic1_. In addition, these non-privileged devices retrieve the information generated by other devices under the _/topic1_ label. The information generated as _/topic1_ consists of random floats with no practical meaning. This information could be, in a real scenario, the temperature taken in a room, the humidity in a vineyard, or the vital signs of a patient in a hospital. The generation and handling of this randomly generated information is beyond the scope of this work. In this case, the objective is to evaluate MQTT-SN as an information exchange protocol between the broker and the subscriber nodes.  
As mentioned above, the baseline scenario also includes a privileged mode, which generates a random float and publishes it in the other topic referred to as _/topic2_ in each cycle. The privileged note generates a symbolic message, which is confidential, and it is useful to evaluate a scenario that manages confidential information. These devices do not contain additional protection measures, but the differentiation of these measures makes it easier to observe the handling of the different topics and their contents. Finally, the broker manages all the connections, processes all the information collected by the devices, and centralizes the network.  
Figure 3 shows the baseline scheme, which is composed of devices that generate information on both topics, namely _/topic1_ and _/topic2_, and the broker. In this case, the device with an orange background color, which is located at the bottom left, is subscribed to topic 2, which simulates the sending of critical information. Including this device is useful to evaluate how the system can be altered when using two different topics. By establishing this scenario as the baseline, we can extract valuable information about the regular (not under attack) behavior of the network. Below, we compare the baseline scenario against scenarios with the system under attack.
# Reliable Semantic Communication System Enabled by Knowledge Graph
## 3 System Model  
As shown in Figure 1, the structure of the proposed system consists of a semantic extraction module, traditional communication architecture, and semantic restoration module. The proposed system can be divided into two levels, which are the semantic level and the technical level. The structure of the technical level is the same as that of the traditional communication system; thus, we mainly introduce the details at the semantic level. At the transmitter, the semantic extraction module can extract the knowledge graph (KG) of the transmitted sentence to represent its semantics. More importantly, the knowledge graph is sorted according to semantic importance. At the receiver, the semantic restoration module can recover the transmitted sentence according to the received knowledge graph.  
Figure 2 shows examples of the proposed semantic communication system in different channel qualities. At the transmitter, the transmitted sentence is first converted into the knowledge graph through the semantic extraction module. Next, the transmitter adjusts the knowledge graph according to the channel quality. Then, the knowledge graph is transmitted through the channel. With the noisy knowledge graph received, the semantic is recovered through the semantic restoration module. In Figure 2a, when the channel quality is good, the transmitted sentence and the restored sentence convey the same semantics although they have different sentence structures. When the channel quality is poor, all triplets cannot be transmitted correctly. Therefore, the proposed semantic communication system chooses to transmit the most important triplet. When it comes to [PERSON], people tend to care about his relationship with Apple rather than the college he graduated from. As shown in Figure 2b, the transmitter only sends \"< [PERSON]\" when the channel quality is poor.  
Figure 1: The structure of the proposed semantic communication system based on the knowledge graph, including the semantic extraction module, traditional communication architecture, and semantic restoration module.  
Figure 2: Examples of the proposed semantic communication system in different channel qualities. (**a**) An example of the proposed semantic communication system when the channel quality is good. (**b**) An example of the proposed semantic communication system when the channel quality is poor.
## 3 Experiments and Results  
### Experimental Scenarios  
To verify the feasibility of the proposed system, this study selected a temporary experimental site consisting of a surface iron-rubberized straight path (\(\Phi\)1.2 m \(\times\) L12 m), as depicted in Figure 4. The experimental site was a black sewage linear pipe, and data collection was performed without any interference from moving objects. In order to evaluate the performance of the proposed system, this study analyzed dynamic scenes and conducted experiments under varying lighting conditions. Instead of relying on natural light, this system utilized UAV-mounted lighting equipment to provide illumination during the experiments. The angle and position of the on-board lighting equipment were constantly adjusted, resulting in changes in the brightness of the pipe walls. This allowed us to collect data on the dynamic scene while also introducing tracking challenges. Achieving uniform coverage with artificial lighting is more challenging compared to natural light. However, the on-board lighting equipment effectively simulated challenging lighting situations encountered in real-world engineering applications, aligning with the goals of our test methodology.
## 4 Results and Discussion  
### Data Processing Flow  
After the consistency of all instruments reached the standard, we started to collect the data, and the collected data files were saved in an SG2 format. For the data processing of this experiment, we used the Surface Plus module in Canada's Geogiga Seismic Pro software. Firstly, we needed to import the raw data of each measuring point into the Surface Plus module. Secondly, when setting up the observation system, considering that some acquisition stations may be affected by interfering objects, such as trees, gravel and abandoned building residues, and when the acquisition stations were placed in accordance with the specified coordinates, we needed to place the acquisition stations in deviation, with the placement deviation not exceeding 5 m. To ensure the reliability of the data results, the allowable deviation of the ESPAC calculation was set to 5%. Thirdly, we removed the interfering seismic traces, and calculated the dispersion spectrum of this point after setting the dispersion analysis parameters. Finally, we picked up the dispersion curve of the point manually. Since there were few borehole data in this area, the initial velocity model of the formation could be automatically generated when the dispersion curve of this point was inversed.  
The relevant research on surface wave inversion shows that the surface wave inversion based on the genetic algorithm has a fast calculation speed, strong global search ability and much less dependence on the initial model than other linear inversion methods, so this algorithm was used in the inversion of the velocity model [19]. Based on [PERSON]'s theory of biological evolution, the genetic algorithm (GA) simulates the process of natural selection and biological evolution, and uses iterative processes such as coding, selection and transformation to solve the optimal solution, which has an advantage over the global nonlinear method [21].  
We used the built-in GA method to invert the dispersion curve. The algorithm built into the software automatically determines the thickness and number of layers of the initial model according to the measured dispersion curve curvature. We set the population size  
Figure 7: Schematic diagram of instrument rolling.  
to 128, the crossing probability to 95% and the variation probability to 9%, and obtained the apparent shear wave velocity and D-V curve of the point. Finally, we collected all the dispersion curves to obtain the underground velocity structure profile of the survey line.  
Figure 8 shows a waveform record of the WD1-1 measuring point within 10 s. It can be seen from the figure that the data interference of the No. 6, 7 and 8 acquisition stations at this measuring point was large, so it was necessary to remove it from the seismic channels when calculating the dispersion spectrum, so as to ensure the reliability of the results.
## 6 Results, Analysis and Discussion
### Analysis Spatial Distribution of Performance Metrics
#### 6.2.3. Tries with 2D Representation  
Figure 9 exhibits the tries metric when there is no jamming in the network and reactive cases where the jammer node position is near, in the middle and far with respect to the coordinator. In the no jamming column, we observe that for all three protocols, nodes that are close to the coordinator needed fewer tries to be reached (one try). AODV and DSR reach up to four tries, while the maximum tries for MPH is three. For reactive jamming, cases in the other columns are not well defined in any of the protocols with respect to a specific pattern; however, MPH presents shaded nodes with lighter colors than the AODV and DSR cases, representing that the differences in the tries metric under reactive attack are softer than in the AODV and DSR protocols.  
Figure 8: 2D representation of the average CSMA retries in the no jamming case and the difference between the values in the reactive and no jamming cases for each of the positions of the jammer node.  
Figure 9: 2D representation of the average tries in the no jamming case and the difference between the values in the reactive and no jamming cases for each of the positions of the jammer node.  
Table 3 helps us to visualize and quantify more easily the results that we observed in Figures 7-9. In this table, we can perceive the three studied metrics (retransmissions, CSMA retries and tries). Numerical values represent the total sum of the difference values in each of the nodes for each jammer node position. These values show what protocol presents the biggest changes for the worst case (reactive jamming) better. We note that in most cases, the MPH has the smallest sum, meaning that the protocol is less prone to change when a reactive jamming exists in the network and that nodes are able to diminish the attack or focus it in a small region of the network.
# Breath Analysis: A Promising Tool for Disease Diagnosis--The Role of Sensors
## 3 Types of Nanomaterial-Based Sensors in Breath Analysis
### Chemiresistors
#### 3.1.1 Selective Applications
The combination of CNTs with conducting polymers has been reported as well, especially for selective detection of ammonia. Such sensors employ carboxylated-MWCNTs-polypyrrole [84] or polyaniline-MWCNTs nano-composites featuring increased sensitivity in the presence of H\({}_{2}\)S, NO\({}_{2}\) acetone, ethanol, and isoprene [85].
## 4 Applications of FBFET
### Neuromorphic Cells  
ANNs, which have been developed based on the neurotransmitter structure of biological neurons, have been proposed as a powerful method that can be used in place of conventional Neumann computing, especially for pattern recognition and classification [57; 58]. Unlike [PERSON]'s existing computer architecture, ANNs have been proposed to solve the problem of not being able to compete with the energy efficiency of the biological brain. A new generation of ANNs have been proposed using spiking neural networks (SNNs) (see Figure 13) [59; 60; 61; 62]. However, the traditional neuron circuits of SNNs require large areas as well as high power consumption. The application of FBFETs to neuromorphic devices is being investigated to solve these issues. PF devices with a split-gate floating body are proposed as new neuron devices that demonstrate integration-and-fire capabilities (see Figure 13). This simulation used a common magnetic controller in the neuron layer and demonstrated the successful operation of a high-density multiple-PF neuron system exhibiting reset and lateral suppression. A reduction in power consumption of ~100 times was reported, demonstrating the potential for use of FBFETs in neuromorphic circuits. The energy consumption of the current is proportional to the number of spikes. The average energy consumption of the total output neurons was reduced by approximately 94% compared to conventional neuron circuits. When the PF device  
Figure 12: Illustrated 2T-static random-access memory (SRAM) circuit composed of FBFET [52].  
value was applied, a low threshold swing (0.04 mV/decade) of the device was obtained, which reduced the existing 25 pJ/spike of the neuron circuit to \(\sim\)0.25 pJ/spike (see Figure 13c,d). In addition, charge storage through trapping in the potential walls of the wider body of the FBFET functions to imitate the integration in biological neurons without large capacitors. By replacing the C\({}_{\text{mem}}\) of the conventional neuron circuit, which requires a large space, by using positive feedback for the charge trap layer of the device, a smaller area and higher density of devices are available. Note that C\({}_{\text{mem}}\) refers to the membrane capacitor of the average neural circuit. As many transistors and capacitors have traditionally been needed for neuromorphic circuits, creating high density is important for their development. A 17-fold reduction in the area of the neurons was reportedly achieved through the use of FBFETs [21].
# Network Pharmacology-Based Study on the Efficacy and Mechanism of _Lonicera japonica_ Thunberg
###### Abstract  
Network pharmacology is an emerging method for investigating the potential effects and mechanisms of natural products through system-level analyses of gene sets in herbs. _Lonicera japonica_ Thunberg (LJ) is known to have anti-inflammatory, anti-bacterial, anti-oxidant, anti-tumor and neuroprotective effects. In the present study, network pharmacological analysis was performed to assess the potential efficacy and mechanisms of LJ. First of all, constituents of LJ were gathered from public databases: the Oriental Advanced Searching Integrated System (OASIS) database, PubChem and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Then, a network was constructed using Cytoscape3.8.2, which visualizes biomedical interactions, and a functional enrichment analysis was conducted to uncover the pathways most relevant to LJ through Enrichr based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway 2021. Further, we performed a study of the literature to determine whether the results of our study were consistent with those of previous studies. The results showed that 'Advanced glycation end products-Recoper for advanced glycation end products (AGE-RAGE) signaling pathway in diabetic complications' was the pathway most relevant to LJ, especially through 'Mitogen-activated protein kinase (MAPK) signaling pathway', 'Phosphatidylinositol 3 kinase-Protein kinase B (PI3K-AKT) signaling pathway and Janus kinase-Signal transducers' and activators of transcription (JAK-STAT) signaling pathway'. Based on the literature study, LJ showed relevance to MAPK, PI3K-AKT and JAK-STAT and was associated with therapeutic effects on diabetes and diabetic complications. This study shows that network pharmacology can be a suitable approach for analyzing LJ and suggests the potential efficacy and mechanisms of LJ.  
Lonicera japonica Thunberg; network pharmacology; potential efficacy; age-rage signaling pathway; diabetic complications Article  
Network pharmacology; protein efficacy; age-rage signaling pathways; diabetic complications