esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Gene Ontology Annotation  
Gene ontology (GO) is a standardized gene functional classification system, which tenders a dynamic-updated controlled vocabulary. The GO analysis indicated that a total of 15,640 GO terms were associated with all unigenes (Figure 2, Supplementary Table S1). According to the secondary classification of the GO terms, all unigenes are sorted into 48 functional groups. Biological process is the main category of GO annotations (6771, 43.29%) unigenes, followed by cellular component (5074, 32.44%) and molecular function (3795, 24.26%). The metabolic process (25.88%) and cellular process (24.09%) represent most of the biological process category, indicating that the bacterium has high metabolic activity. There are also some subcategories including response to stimulus (8.83%), biological regulation (8.26%), regulation of biological process (6.96%), localization (6.94%), multi-organism process (4.31%) and cellular component organization or biogenesis (3.71%). Cell (29.96%), cell part (29.84%), membrane (17.80%), membrane part (11.69%) and protein containing complex (4.85%) are the cell gene clustering of five main components. The catalytic activity (42.77%) and binding (39.53%) represent most of the molecular function category, forecasting that the bacterium has a high degree of molecular catalysis (Figure 2).  
Figure 1: Circular representation of two chromosomes and two plasmids of _Sphingomonas moridae_ sp. NBD5. Marked information is illustrated from the inner to outer ring: GC skew, GC content, the distribution of rRNAs and tRNAs, CDSs on the reverse stand, CDSs on the forward stand, genomes size.
## 3 Samples and Analytical Methods
### Analytical Methods  
#### 3.2.1 Biomarker Analysis  
The analysis and testing of biomarker compounds of source rocks and crude oil was completed at the State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation of Chengdu University of Technology.  
Soxhlet extractions were conducted on the powdered mudstone samples using chloroform/methanol (87:13) for 72 h before GC-MS analysis. The different components were separated from source rock extracts and oil samples. The GC-MS analysis of the saturated hydrocarbon fractions from source rock extracts and oil samples was performed on an HP6890 GC/5973 MSD instrument equipped with an HP5 MS fused silica column (30 m \(\times\) 0.25 mm i.d., film thickness of 0.25 \(\upmu\)m). The GC oven temperature was initially set to 50 \({}^{\circ}\)C for 1 min, then programmed to increase to 120 \({}^{\circ}\)C at a rate of 20 \({}^{\circ}\)C/min, to 250 \({}^{\circ}\)C at a rate of 4 \({}^{\circ}\)C/min, and to 310 \({}^{\circ}\)C at a rate of 3 \({}^{\circ}\)C/min, and finally kept at 310 \({}^{\circ}\)C for 30 min. The mass spectrometer was operated in full-scan and selective ion monitoring modes, and the biomarker ratios were calculated by the peak areas of the compounds.
# Applications of Wireless Sensor Networks: An Up-to-Date Survey
## 3 Discussion
Also, the communication should achieve high levels of throughput, security, reliability, and resistance to jamming and intervention due to the huge volume of data transmitted. Moreover, nodes should be robust enough to ambient conditions. Also, the WSN should be tolerant to the loss of a certain quantity of nodes. The abovementioned considerations, regarding the required features that WSNs should have per type of application, are synoptically presented in Table 1.  
Additionally, apart from the aforementioned issues that are application dependent, the operation of WSNs is also obstructed due to general issues, such as difficulties of wireless communication and weaknesses of the nodes. Specifically, sensor nodes of WSNs suffer from extremely strict energy constraints. This is because their energy is typically supplied by batteries which are usually impractical to be either recharged or replaced, since the locations of sensor nodes are usually difficult or even impossible to reach. Therefore, the attainment of energy conservation is a vital issue for WSNs. For this reason, energy inefficiencies that exist at every one of the five layers of the protocol stack of sensor nodes must be eliminated. Given that data transmission is by far the most energy consuming task of nodes, power control schemes [61], data aggregation schemes that decrease the size of data transferred [62], [63] and energy efficient routing protocols [64] have been proposed. Likewise, in applications in which multimedia data are transmitted, the use of compression and restoration schemes provide a substantial reduction of communication load [65; 66]. Additionally, the presence of excessive data traffic in a specific region of a WSN causes network congestion which obstructs data transmission, generates packet losses, and decreases the network throughput. For this reason, methodologies for congestion avoidance [67; 68; 69], congestion control [70; 71], and load balancing [72; 73] are used. Furthermore, each time that a node is disconnected from the rest of the network, due to, malfunction, damage, or energy depletion the communication for the remainder becomes more difficult and the communication cost is increased. For this reason, methods for the preservation of network connectivity are essential to be applied [74; 75]. Moreover, it is anticipated that the nodes achieve the best exploitation of their sensing range and their communication range in order to cover as much of the network area. This is why coverage maximization methods  
are considered [76; 77]. Moreover, in WSN applications where multimedia data are transmitted, the attainment of high Quality of Service (QoS) is a necessity. Furthermore, the accomplishment of energy efficient routing in WSNs is often influenced by other issues such as the QoS attained [78; 79]. Last but not least, in most WSN applications, the data transmitted within the network must be protected from any unauthorized use. For this reason, security preservation schemes are used [80; 81].
# Effects of Fineness and Dosage of Fly Ash on the Fracture Properties and Strength of Concrete
## 5 Conclusions  
Based on the tests and evaluations presented in this study, the following conclusion can be reached:  
1. Incorporating finer fly ash into concrete may fill the micro-voids much better and produce higher packing density, resulting in larger strength enhancement. The compressive strength of fly ash concrete increases in conjunction with the fineness level of fly ash presented in the mixtures for each age and various fly ash replacement ratios.
2. Use of finer fly ash has beneficial effects on the fracture energy (\(\mathrm{G_{F}}\)) of concrete, even at an early age (14 days). The finer fly ash used, the greater the fracture energy of the concrete exhibited.
3. The increment of the fracture energy of all the fly ash concrete measured in this study from 14 days to 56 days was attained by 21-31%, which was much higher than that of control concrete (13.6%), such that the \(\mathrm{G_{F}}\) of the fly ash mixtures at 56 days almost exceeded that of the control concrete.
4. An increase in fly ash concrete compressive strength of 10% resulted in an increase in the \(\mathrm{G_{F}}\) value of around 14% when the compressive strength varied between 50 and 80 MPa. This rate of increase is significantly higher than that found in normal concrete, indicating that the use of finer fly ash can have unique effects on the enhancement of the fracture toughness of high-strength concrete.
5. Similar to the trend of development of the fracture energy, at an early age (14 days), most of the stress intensity factor (\(\mathrm{K^{S}_{IC}}\)) of the fly ash concrete was lower than that of the control concrete (R0), but exceeded that of the R0 after 56 days.
6. Concrete containing finer fly ash exhibited larger \(\mathrm{K^{S}_{IC}}\) value for various ages, and the stress intensity factor increased in conjunction with the fineness level of fly ash. This also implicates an increase in the fracture resistance of concrete.  
Conceptualization--C.-H.H. and T.Y.; Methodology--C.-H.H.; Validation--C.-H.H., and Y.-C.K.; Formal Analysis--C.-H.W. and C.-H.H.; Investigation--C.-H.W. and C.-H.H.; Resources--C.-H.H.; Data Curation--C.-H.W. and C.-H.H.; Writing and Original Draft Preparation--C.-H.W., C.-H.H. and T.Y.; Writing, Review, and Editing--C.-H.H. and T.Y.; Visualization--C.-H.H. and Y.-C.K.; Supervision--T.Y.; Project Administration--C.-H.H.  
This research received no external funding.  
The authors declare no conflict of interest.
## 5 Conclusions  
In this study, we developed a UAV information collection and sharing system called Drone Mapper. This system utilizes a V2V communication system with LPWA functionality. Building upon the Drone Mapper device, we also developed an AFCCS to enhance safe UAV operations. The AFCCS provided two essential functionalities for multiple UAV applications: collision avoidance and formation flying. To assess the performance of the developed AFCCS, field experiments were conducted. The experimental results demonstrate the effectiveness of our system and its potential application for UAV collision avoidance and formation fight. In the future, as the skies become more crowded with UAVs and urban air mobility vehicles, the significance of effective operational management will increase. To enhance safety and efficiency, it is predictable that dynamic information-sharing systems based on V2V communications in addition to ground networks will become indispensable components.  
Conceptualization, L.S.; Methodology, L.S.; Software, L.S.; Formal analysis, L.S.; Investigation, L.S.; Resources, R.M.; Data curation, L.S., R.M., T.M. ([PERSON]) and M.K.; Writing--original draft, L.S.; Writing--review & editing, L.S., R.M. and H.-B.L.; Visualization, L.S.; Supervision, T.M. ([PERSON]); Project administration, R.M. and T.M. ([PERSON]); Funding acquisition, T.M. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
New Energy and Industrial Technology Development Organization (NEDO), Japan: DRESS; ImPACT program of Cabinet Office Government of Japan: TRC.  
Data Availability Statement: Data are contained within the article.  
The devices for the vehicle-to-vehicle (V2V) communications system and the autonomous flight coordination control system (AFCCS) used in this research were developed by the ImPACT program of the Cabinet Office Government of Japan. The improvement of the AFCCS and the field experiments on V2V communications using multiple UAVs were conducted under the DRESS project commissioned by the New Energy and Industrial Technology Development Organization (NEDO).  
The authors declare no conflict of interest.  
Figure 19: Experimental data of deviation distance for follower UAVs with \(N=4\).
# Multi-Person Action Recognition Based on Millimeter-Wave Radar Point Cloud
## 4 Experimental Results Analysis
### Ablation Study  
This paper's data preprocessing module proposes a filtering method based on the inter-frame differences. To analyze the effect of this method on the final classification results, we perform an ablation study. In order to make a comparison under multiple conditions, we test the effect of deleting the modules of straight-through filtering, statistical filtering, and inter-frame difference filtering on the classification results at different human body radar distances and different radar placement heights, respectively. As shown in Figure 10, the maximum contribution of the frame difference filter to the system's overall accuracy reaches 11%, the minimum contribution reaches 6%, and the average contribution is 8.8% for different human body-radar distances. As shown in Figure 11, at different radar placement heights, the maximum contribution of frame difference filtering to the system's overall accuracy reaches 11%, the minimum contribution reaches 5%, and the average contribution is 8.3%.  
This experiment shows that our proposed filtering method based on millimeter-wave radar inter-frame differences significantly eliminates noise due to multipath effects and other interferences, which is more significant when the overall accuracy of the system is high. The addition of frame difference filtering can significantly improve the quality of the human action point cloud, which can significantly improve the classification accuracy of the overall system.  
Figure 11: Effect of each filter module on overall accuracy for different radar placement heights.  
Figure 10: Effect of each filter module on overall accuracy at different distances between human body and radar.
# Digital Twins Generated by Artificial Intelligence in Personalized Healthcare
## 3 Results
### Interoperability  
Interoperability between AI-based healthcare DT systems and other eHealth systems is key to seamless data exchange and integration. These systems are typically designed to communicate with EHRs, allowing DT systems to automatically retrieve patient data such as medical history, lab results, and imaging studies. Standard protocols such as HL7 and FHIR are often used to ensure consistent and accurate data exchange between the digital twin and various healthcare systems. AI-based DT systems are also capable of integrating with clinical decision support systems (CDSSs), enabling real-time insights to be incorporated into clinical workflows. Interoperability extends to mobile devices and remote monitoring tools, enabling the continuous transfer of patient data, which is then processed and visualized in the digital twin interface. These systems often include application programming interfaces (APIs) that enable connections to other healthcare applications, facilitating the creation of a comprehensive and connected ecosystem. Data interoperability ensures that digital twins can be used across healthcare settings, from hospitals to outpatient clinics, ensuring continuity of care. They are also designed to meet regulatory standards such as HIPAA and GDPR, ensuring secure data exchange between systems and protecting patient privacy. Furthermore, AI-powered DTs can integrate with public health databases and research platforms, providing anonymized data for large-scale research and epidemiological tracking. Finally, interoperability with telehealth platforms enables the use of digital twins during remote consultations, providing clinicians with detailed patient information regardless of location [61; 62; 63; 64].
## 4 Conclusions  
In summary, we have proposed and demonstrated utilization of diffraction of a trapping laser beam for the optically guided assembly of colloidal particles at the glass-water interface. The trapping laser beams include linearly, azimuthally and radially polarized beams. The diffraction optical traps assemble the particles to form ring structures for linearly polarized beams. The results show that the particle distributions in the transverse plane are drastically affected by the particle size and concentration. With the help of a polarizer, the particles are arranged as fan-shape structures with azimuthally polarized beams. The particles are accumulated and crystallized as a two-dimensional compact structure under the optical force generated by the radially polarized beam.  
NaCl, serving as the electrolyte, is used to change the particle-particle interaction, and the interaction between the particles and substrate slide. Under the concentration of NaCl at 0.5 mol/L, the particle patterns are easily printed steadily on the glass surface. The ability of trapping and manipulating an amount of particles has been expected to provide an intersecting method for self-organization assembly [44; 45; 46]. Furthermore, we discuss the influence on the application of optical tweezers in microfluidic channels, and use a reflector as the surface of the sample cell to avoid the diffraction traps' induced aggregation. The demonstrated examples in this paper might have applications for two-dimensional colloidal assembly and understanding the principle of optical tweezers.  
[PERSON] conceived and designed the research. [PERSON], [PERSON] and [PERSON] performed the experiments. [PERSON] and [PERSON] processed images and analyzed the experiment data. [PERSON] wrote the manuscript. All of the authors revised the manuscript.  
This work is supported by the National Natural Science Foundation of China (Nos. 11302220 and 11874138), and the Fundamental Research Funds for the Central Universities (No. PA2017 GDQT0024).  
The manuscript has been greatly improved by addressing the constructive comments and suggestions made by two anonymous reviewers, whom we would like to thank for their time and efforts.  
The authors declare no conflict of interest.  
Figure 7: Optical trapping of a number of particles leads to aggregation in the micro-channel. (**a**) initially, optical tweezers trap one particle and flows quickly through the micro-channel; (**b**,**c**) more particles are trapped by the diffraction fringes, and more and more particles are settled in the micro-channel. The laser power is 1.5 W; scale bar, 10 μm; the circles indicate the optical trap and the arrows indicate the flow direction.
## 6 Results
### Energy Reduction
#### 6.3.3 Focus on Bad Radio Conditions  
As we observed, radio condition 4 is particularly interesting as the measurements showed a very high latency for the message exchange as well as high energy consumption. Because some exchanges (an uplink and a downlink) were experiencing extended duration, we implemented a threshold of 90 s, beyond which the exchange was considered unsuccessful. In addition, we extended the number of measurements in this case to obtain a better resolution.  
Taking the case of 100-byte uplink and downlink messages over the IP as an example, we saw that the percentage of unsuccessful exchanges was 14.2%. This percentage dropped to 3.2% when using SCHC. In the case of sending 200 bytes over NIDD, the percentage dropped from 16.6% to 8.3% when using SCHC. SCHC reduces the size of the message, thus reducing the possibility of transmission errors and thus the probability of unsuccessful exchanges.  
Taking into account only successful exchanges, we present the average measured energy consumption of the device for exchanging an uplink followed by a downlink with a 95% confidence interval in Figure 13. For 50-byte messages, SCHC reduces the average energy consumption. However, there is a noticeable overlap in confidence intervals between scenarios with and without SCHC. Nevertheless, as the message size is increased, the confidence intervals start to separate, becoming fully disjointed for 200-byte messages. This demonstrates the effectiveness of SCHC in reducing the energy consumption of a device, especially in bad radio conditions.  
Figure 12: Energy consumption (mWh) for NIDD scenario without SCHC (no DTLS).
## 4 Simulation Results  
This section presents the simulation results to compare the performances of the ACA and the GA. We consider a circular urban area with parameters \(\alpha~{}=~{}9.61,\beta~{}=~{}0.16,\eta_{LoS}~{}=~{}1,\eta_{NLoS}~{}=~{}20\). The radius of the circular area is \(R_{o}\) and the initial value of hovering radius is \(r_{o}\). The carrier frequency is \(f~{}=~{}20\) GHz. In addition, it is assumed that the path loss threshold is \(L_{th}~{}=~{}100\) dB. The optimal height of the UAV can be calculated according to the maximum path loss. Then, the UAV is placed at this altitude and the user scheduling, along with the hovering radius of the UAV, are further optimized. We first use ACA to optimize user scheduling and then GA to optimize the hovering radius of the UAV. The optimal hovering radius of UAVs maximized the fairness was obtained through iterative optimization of ACA and GA.
# A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments
###### Abstract  
Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3 GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments.  
vehicle positioning; 5G positioning; time delay estimation; multiple signal classification; super-resolution +
Footnote †: journal: Sensors
# Satellite Measured Ionospheric Magnetic Field Variations over Natural Hazards Sites
## 2 Magnetic Field Measurements at Low Earth Orbit Altitudes
### Cses  
The main objective of CSES is the study of ionospheric responses to lithospheric processes, i.e., electromagnetic- and plasma-phenomena related to natural hazards, in particular earthquakes (EQ) with possibly precursor phenomena. The three axes stabilised spacecraft with eight scientific instruments was launched on 2 February 2018, into a sun synchronous polar orbit with an altitude of \(\sim\)507 km and an inclination of 97.4 deg [2]. One of the instrument packages is the high precision magnetometer (HPM) consisting of two fluxgate magnetometer (FGM; FGM1 and FGM2) and a scalar coupled dark state magnetometer (CDSM). The HPM data processing pipeline includes corrections, interference mitigation, synchronisation, and calibration steps for the nominally sampled 60 Hz FGM vectors and 30 Hz CDSM values [3]. The science data cover the latitude range from \(-65\) deg to \(+65\) deg with a temporal resolution of 1 s. The CDSM instrument is a scalar magnetometer based on two-photon spectroscopy and has a noise level of \(\sim\)50 pT/sqrt(Hz) at 1 Hz, an accuracy of 0.19 nT (1\(\sigma\)), and a total magnetic field measurement range from \(10^{3}\)-\(10^{5}\) nT [4]. The HPM instruments are parallel aligned, from the satellite surface outwards in the layout FGM1-FGM2-CDSM, and mounted along a 4.7 m madir pointing boom in order to minimise the spacecraft magnetic disturbances. In-orbit results with a performance analysis have been reported by [5], the CSES data description, and data service are detailed in [6].
## 2 The Intelligent Fault Diagnosis System Model  
A new framework for the intelligent fault diagnosis system is proposed in this paper, which consists of MEC servers and intelligent terminals, as shown in Figure 4. Both MEC servers and intelligent terminals can process monitoring data, and the intelligent terminal can offload data to any MEC server through the agent. The interaction between the intelligent terminal and the MEC server operates in the orthogonal frequency division multiple access frameworks. The offloading policy includes the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection. According to the offloading policy, the monitoring data is split into two parts: one is offloaded to the MEC server for processing and the remaining part is kept locally for processing by the intelligent terminal. The intelligent fault diagnosis system based on the MEC framework can be divided into three models: the network model, the communication model, and the computing model. These will be introduced separately in the following.