esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In this paper, the aerodynamic performance of the quadrotor with rotor spacing L/R varying from 2.2 to 4.0 was studied by both experiments and numerical simulations. The interaction between the rotor systems is obtained with instantaneous thrust and power, the pressure, velocity vector, and vorticity of the quadrotor. It proves that the aerodynamic performance of the quadrotor was indeed much improved by changing rotor spacing. Conclusions of this paper are as follows:  
1. Compared with the isolated rotor without interference, the thrust of the quadrotor system is obviously increased with varied rotor spacing, which illustrates that the moderate aerodynamic interference between adjacent rotors can improve the overall hover efficiency of the quadrotor. The quadrotor has larger thrust at L/R = 3.2 and L/R = 3.6 comparing with other rotor spacing, and the largest increment of thrust is about 36.8% at L/R = 3.2.  
Figure 11: Velocity vector distribution: (**a**) L/R = 2.2; (**b**) L/R = 3.2; (**c**) L/R = 3.6; (**d**) L/R = 4.0.  
Figure 12: Vorticity distribution: (**a**) L/R = 2.2; (**b**) L/R = 2.6; (**c**) L/R = 3.6.  
Small rotor spacing will decrease the aerodynamic performance of the quadrotor due to the strong aerodynamic interference between adjacent rotors, resulting in thrust loss and power increment. However, extra power consumption will be also introduced with a large rotor spacing.
3. The optimal rotor arrangement of the quadrotor is confirmed as L/R = 3.6 with a higher thrust and lower power consumption, where the Figure of Merit (FM) is also the achieved maximum.
4. A better aerodynamic performance of the quadrotor is obtained from CFD results, showing that an appropriate rotor spacing is characterized by larger pressure difference around the rotor tip and a relatively intact tip vortex as well.  
[PERSON] carried out experiments and analyzed experimental results; [PERSON] wrote the manuscript with assistance of [PERSON]. All authors have read and agree to the published version of the manuscript.  
This research was supported by the National Natural Science Foundation of China (Grant No. 51505087), Fuzhou University Jinjiang Science and Education Park (No. 2019-JJFIDKY-59) and Fujian Provincial Industrial Robot Basic Components Technology Research and Development Center (2014H21010011).  
The authors thank the Key Laboratory of Fluid Power and Intelligent Electro-Hydraulic Control (Fuzhou University), Fujian Province University, and Fuzhou University Jinjiang Science and Education Park for applying the experimental field.  
The authors declare no conflict of interest.
# FOG De-Noising Algorithm Based on Augmented Nonlinear Differentiator and Singular Spectrum Analysis
## 4 Experimental and Verification
Besides, compared to ARKF, it does not need to pre-design any model in the application of SSA-AND, which makes the structure of the proposed algorithm simpler. Moreover, Allan variance analysis is introduced to provide the quantitative comparison for de-noising results of different methods. Allan variance analysis has advantages in evaluating and identifying random noise coefficients. The random noise coefficients are \(Q\) (quantification noise, QN), \(N\) (angle random walk, ARW), \(B\) (bias instability, BI), \(K\) (rate random walk, RRW), and \(R\) (angular rate ramp, ARR), respectively. Among these parameters, ARW is the most widely used for representing the white noise, and QN stands for the noise induced by A/D and D/A conversion. Therefore, ARW and  
Figure 6: Comparison results of different de-noising methods for the signal of FOG2: (**a**) original signal; (**b**) signal de-noised by AND, where \(R=0.5\); (**c**) signal de-noised by DFA-VMD; (**d**) signal de-noised by EMD-FLP; (**e**) signal de-noised by ARKF; (**f**) signal de-noised by SSA-AND. de-noising ability compared to other advanced de-noising algorithms, and the temperature drift of FOG can be extracted effectively without signal delay. The advantages of the proposed SSA-AND algorithm can be summarized as: (1) By combining SSA and AND together, the de-noising ability is enhanced effectively, and the signal delay caused by AND is eliminated; and (2) based on the correlation coefficient of each decomposed component, a parameter determination method for SSA-AND algorithm is proposed, which can be used as a reference for other similar hybrid de-noising methods based on multi-scale decomposition. Conceptualization, X.Z. ; Methodology, H.C.; Software, X.S. ; Investigation, J.L. ; Writing-Original Draft Preparation, C.S. This research was funded by the Natural Science Foundation of China (61603353, 51705477, 51575500), and the Shanxi Province Science Foundation for Youths (201601D021067), and the Fund for Shanxi \"1331 Project\" Key Subjects Construction. The authors declare no conflict of interest.
## 2 Materials and Methods
### PPP Time Transfer Model
Due to the lack of a reference in one-way PPP timing, which makes it impossible to verify the timing accuracy of kinematic PPP, we used time transfer results to validate the performance of kinematic PPP time transfer. During the PPP time transfer process, data loss may occur due to data exchange. This paper focuses on studying the kinematic PPP time transfer performance under conditions where no data are lost, while considering potential future data loss scenarios; future work could incorporate a receiver clock offset prediction model.
# A Reliable Publish-Subscribe Mechanism for Internet of Things-Enabled Smart Greenhouses
## 3 Research Methodology
### Architecture and Protocol Description
* Reduced Complexity: The structured approach simplifies the overall system, making it easier to manage and maintain. * Cost Efficiency: The system becomes more cost-effective by reducing the number of messages and processing time. * Enhanced Accuracy: The categorization system ensures that only relevant data are transmitted, improving the accuracy of the server's processing. In addition to improving the smart greenhouse system's general efficiency, this method makes sure it can handle any modifications or expansions that come its way. Numerous researchers have utilized IoT-enabled smart greenhouse systems to address the need for greenhouse crop growth optimization. For instance, ref. [36] evaluated lightweight cryptographic technologies between publishers and the original MQTT broker, and even between the broker and its subscribers, within the IoT network for smart irrigation systems in agriculture. Consequently, the evaluated protocol decreased resource consumption regarding memory application and execution time. However, a structured broker is not intended to be employed with the MQTT protocol to minimize the additional processing caused by publishers and brokers. Likewise, this results in a boost within irrelevant data, which diminishes the processing precision of the primary server. Similarly, another study [37] evaluated a low-cost IoT monitoring system for appropriate irrigation and pest control operations for olive plantations situated in the eastern coastal regions of Crete, Greece, that encounter water accessibility and pest infestation issues. In addition, the proposed solution, which utilizes the original MQTT protocol, transfers beneficial information from sensors, including soil moisture, soil temperature, and weather data, to the user, thus broadening the agricultural industry's awareness of optimal irrigation management issues. Nevertheless, the lack of a well-defined topic categorization system for MQTT broker poses challenges to efficiently routing messages to their intended subscribers [38]. This situation may require further computational steps to ascertain the proper destination for each message. Thus, this may result in heightened server processing duration and potentially impact the system's responsiveness.
## 2 Materials and Methods
### Sample Treatment and GC-MS Conditions  
The samples were ground to powder in liquid nitrogen and removed (1 g, 1 mL) immediately to headspace vials (Agilent, Palo Alto, CA, USA) added with a NaCl-saturated solution. For the SPME analysis, each vial was kept at 60 \({}^{\circ}\)C for 5 min. Then, its headspace was exposed to a 120 \(\upmu\)m DVB/CWR/PDMS fiber (Agilent) for 15 min at 100 \({}^{\circ}\)C. After sampling, the VOCs were desorbed from the fiber coating in the injection port of the GC meter (Model 8890; Agilent) at 250 \({}^{\circ}\)C for 5 min using the splitless mode. VOCs were detected and quantified using an Agilent Model 8890 GC and a 7000D mass meter (Agilent) with a 30 m \(\times\) 0.25 mm \(\times\) 0.25 \(\upmu\)m DB-5 MS (5% phenyl-polydimethylsiloxane) capillary column. Helium was used as the carrier gas at a 1.2 mL/min linear rate. The injector was kept at 250 \({}^{\circ}\)C and the detector at 280 \({}^{\circ}\)C. The oven was started at 40 \({}^{\circ}\)C (3.5 min), heated at 10 \({}^{\circ}\)C/min to 100 \({}^{\circ}\)C, at 7 \({}^{\circ}\)C/min to 180 \({}^{\circ}\)C, at 25 \({}^{\circ}\)C/min to 280 \({}^{\circ}\)C, and maintained for 5 min. Mass spectra were acquired using the electron impact (EI) ionization mode at 70 eV. The quadrupole mass detector, ion source, and transfer line were set at 150, 230, and 280 \({}^{\circ}\)C, respectively. MS using the ion monitoring (SIM) mode was performed to identify and quantify analytes. Metabolites were qualified and quantified as reported [23]. The repeatability of metabolite extraction and technical duplication was tested by overlapping the total ion chromatography (TIC) of the MS of different QC samples. Instrumental stability ensured the data were repeatable and reliable.
# An IoT-Based Participatory Antitheft System for Public Safety Enhancement in Smart Cities
## 3 Methods and Materials
### Gateway Operational Workflow  
The operation of the Gateway function is implemented as follows:  
In line with the workflow presented in previous sections, the Gateway requests from the server side the BLE tags that have been reported as being stolen. Then, it updates its local database and accordingly configures the BLE/USB module to either broadcast the appropriate device name to the remote BLE tag or alternatively scan, in order to detect already activated tags. In other words, it actually converts its operational status to peripheral mode and starts broadcasting a signal in order to switch the remote BLE sensor from scanner to peripheral mode. When in scanning mode, the BLE tag sensors that are found are reported back to the server as scanned or traced.  
Figure 6: Mobile phone message transaction scheme with REST Endpoint.  
On the server side, a storage file structure of BLE tags must be implemented and accessed by the Gateway.  
A simplified approach of the BLE tag status on the server side is as follows. It actually represents a database table with the following arguments:  
<SensorName>, <SensorStatus>  
where:  
<SensorName>: Name assigned to the remote BLE sensor upon configuration. This name is used to enable advertising and beacon mode activation. Normally, it can be defined as a multiple character string.  
<SensorStatus>: Current status of the BLE remote tag. Normally, it can be defined with three statuses: REG, ACT, and INA.  
* REG: Registered device. The device is considered as being in normal status as there has been no user report concerning their status modification.
* ACT: Active device. The device is considered as being a stolen device; therefore, associated sensors must be beacon-enabled by the Gateway.
* INA: Inactive device. The device is considered as being activated (not necessarily found or traced), and beacon broadcast will be terminated by the platform.  
Typical gateway operational workflow is illustrated in Figure 7.
## 3 Joint Power Control and Resource Allocation
### Power Allocation with Power Control Consideration
```
1: compute \(F=|l_{2}|^{2}(Q-\sigma_{u,r}^{2}|l_{1}|^{2})-\eta\rho Q|l_{r}|^{2}|h_{2}|^{2}\), \(\alpha_{0}\)
2:if \(F\leq 0\), denote \(P_{R}=Q/|l_{r}|^{2}\)
3: compute \(\alpha_{ir,mn},i=1,2,\alpha_{1r,2r}\)
4: if \(\alpha_{1r,ma}\geq\alpha_{2r,ma}\)
5:\(\alpha^{*}=\alpha_{1r,2r}\)
6: else if \(\alpha_{1r,ma}<\alpha_{2r,ma}\)
7: if \(H_{1}>H_{2}\)
8:\(\alpha^{*}=\alpha_{1r,ma}\)
9: else if \(H_{1}\leq H_{2}\)
10:\(\alpha^{*}=\alpha_{2r,ma}\)
11: end
12:else if \(F>0\), denote \(P_{R}=\eta\rho((\frac{|h_{1}|^{2}\alpha}{|l_{1}|^{2}}+\frac{|h_{2}|^{2}(1- \alpha)}{|l_{2}|^{2}})Q+\sigma_{u,r}^{2})\frac{t}{1-t}\)
13: compute \(\alpha_{ir,ma}\), \(\alpha_{1r,2r}\), \(\alpha_{ir,rj}\), \(\alpha_{\min,1}\), \(\alpha_{\max,2}\)
14: if \(H_{1}=H2\)
15:\(\alpha^{*}=\min(\alpha_{0},\alpha_{1r,2r})\)
16: else if \(H_{1}>H2\)
17: if \(\alpha_{\min,1}\geq\alpha_{\max,2}\)
18:\(\alpha^{*}=\min(\alpha_{0},\alpha_{1r,2r})\)
19: else if \(\alpha_{\min,1}<\alpha_{\max,2}\)
20:\(\alpha^{*}=\min(\alpha_{0},\alpha_{\max,2})\)
21: else if \(H_{1}<H2\)
22: if \(\alpha_{\min,1}\geq\alpha_{\max,2}\)
23:\(\alpha^{*}=\min(\alpha_{0},\alpha_{1r,2r})\)
24: else if \(\alpha_{\min,1}<\alpha_{\max,2}\)
25:\(\alpha^{*}=\min(\alpha_{0},\alpha_{\min,1})\)
26: end
27:end
28:Then substitute \(\alpha^{*}\) into Equations (44)-(45) to derive \(P_{1}\), \(P_{2}\), \(P_{R}\)
```  
**Algorithm 1** Power allocation under power control with fixed \(t\) and \(\rho\).
## 4 Simulation and Experimental Results
### Experimental Results
There is a third harmonic in the inverter line-to-line voltage, which can circle in the delta-connected winding. This explains the differences between the line and phase currents THD in Table 2. However, it is worth noticing that the third time harmonics in the phase currents of a symmetrically wound machine cannot create a space vector and contribute to the air-gap flux. Figure 15 shows an XY chart of the estimated stator flux linkage vector in the stationary \(\alpha\beta\) coordinate system for a star and delta winding configuration. The oscillograms were obtained using a digital/analog converter of the dSpace platform. It was evident that in the case of the delta winding configuration, the algorithm operated  
Figure 14: Line and phase current comparison for a delta winding connection; reference speed 1000 RPM, reference stator flux 1.7 Wb, load torque 0 Nm. Figure 13: Line current comparison for a star and delta winding connection; reference speed 1000 RPM, reference stator flux 1 Wb, load torque 15 Nm. Figure 16 compares the motor phase voltage of a star-connected machine and the inverter line-to-line voltage (i.e., the motor phase voltage when the machine is delta-connected). In the case of star connection, the phase voltage took values \(\pm 2/3U_{\text{DC}}\), \(\pm 1/3U_{\text{DC}}\) and 0 V, while in the delta connection it took \(\pm U_{\text{DC}}\) and 0 V. The higher instantaneous peak phase voltage in the delta connection was the leading cause of the higher current and, consequently, flux and torque distortion.
# Insight from Review Articles of Life Cycle Assessment for Buildings
## 2 Methodology  
A holistic method, combining quantitative and qualitative analysis, is adopted in this study. In general, the holistic method contains three stages, as shown in Figure 2. In stage 1, bibliometric analysis was conducted to search and collect review articles related to LCA-B. Web of Science (WoS) is commonly employed as a literature database as it provides high-quality and authoritative publications, and it was therefore chosen as the basic database source for this investigation. In the retrieval, an abstract search was firstly conducted as follows: AB = (Life cycle assessment OR life cycle analysis OR lca OR life cycle cost OR life cycle energy OR life cycle carbon emission) AND (building OR housing OR homes OR dwelling OR house), and it was labeled as #1. Secondly, topic search and author-specified keywords were combined together as follows: TS = ((Life cycle assessment OR Life cycle analysis OR lca OR Life cycle cost OR Life cycle energy OR life cycle carbon emission) AND (building OR housing OR homes OR dwelling OR house)) AND AK = (Life cycle assessment OR Life cycle analysis OR lca OR Life cycle cost OR Life cycle energy OR life cycle carbon emission), and it was labeled as #2. Thirdly, both #1 and #2 were considered and the published language was refined as English, the results show that 4300 documents satisfy the above requirement. Finally, 327 review articles were derived and thus selected as literature analysis samples for further investigation. Moreover, the publication time was set from 2009 to 2025.  
Figure 2: Research framework of this study.  
In stage 2, scientometric analysis was conducted based on the 327 review articles, the co-occurrence of journal sources, regions, keywords, co-authorship, and document citations were investigated by VOSViewer version 1.6.20.0. VOSViewer has the advantage of visualizing complex networks and facilitating quantitative analysis for textual data mining applications [98,99]. A four-fold philosophical framework was further proposed to cluster the keywords based on the study of [76,100].  
In stage 3, a comprehensive qualitative analysis was performed to summarize the key findings and challenges based on selected 30 highly cited review articles. The highly cited articles are widely accepted as the \"cornerstone\" of a certain field, which enable researchers to quickly grasp the current development status of this field and provide them with key findings and future research directions based on a comprehensive summary of multiple studies.
# Energy-Balanced Routing Algorithm Based on Ant Colony Optimization for Mobile Ad Hoc Networks
## 4 Simulations
### Verification of Algorithm Convergence
At the convergence rate, the basic ant colony optimization algorithm can be seen to be the fastest because the criterion for path routing is the pheromone concentration. Compared with the algorithm which introduces random numbers, the algorithm proposed in this paper introduces the transition probability, so the number of iterations is significantly reduced, and the convergence speed is obviously improved. The IEMACO improved in this paper can obtain the convergence speed higher than the ACO with random numbers, but achieves the optimal path similar to the basic ACO. Figure 2: Routing performance with varying _offset coefficient_\(\theta\).
# Cross-Medium Photoacoustic Communications: Challenges, and State of the Art
## 4 Properties of Nonlinear Photoacoustic
### Acoustic Source Level and Directionality  
The nonlinear PA process can generate intense acoustic signals. The PA generation efficiency using ionization (\(\leq 10\%\)) is higher than the efficiency (\(\ll 0.1\%\)) for thermal expansion. Figure 11 shows the acoustic source level (SL) as a function of pulse energy for narrowband and broadband lasers based on data collected by NRL [74; 76; 77]. The SL is measured at 1 m distance from the acoustic source with \(10^{-6}\) Pa reference pressure. We can observe the SL increases with laser pulse energy which is expected but for laser pulse energy less than 10 mJ, narrowband nanosecond laser generates a higher SL than broadband femtosecond laser for approximately the same pulse energy. Nanosecond pulses create higher electron density which in turn results in a higher absorption coefficient of the plasma and stronger acoustic signal. [PERSON] et al. [78] also demonstrated that mechanical effects are significantly reduced for shorter laser pulses because the energy required to produce optical breakdown decreases with decreasing pulse duration. Thus, a more significant fraction of energy is required to overcome the heat of vaporization with shorter laser pulses. [PERSON] and [PERSON] [79] investigated the input pulse duration effects on the laser induced underwater acoustic signals with nanosecond and picosecond pulse duration, where they found nanosecond pulses achieve better energy conversion efficiency. [PERSON] et al. [80] studied the acoustic signal strength by varying the distance between the focusing lens and the water surface and found that the strength of the acoustic signal decreases as the distance between the focusing lens and the water surface decreases due to greater optical refraction.  
The directionality of the generated acoustic signal is also dependent on the plasma shape. The generated acoustic signal has peak pressure in the direction of the laser beam for femtosecond laser pulses where a more localized, spherical plasma volume is observed just below the water surface [71]. Here the femtosecond breakdown volume is axially localized due to short pulse length and GVD-induced pulse stretching. However, the peak pressure is perpendicular to the laser propagation direction for nanosecond laser pulses, where more elongated plasma is observed well below the water surface [71]. Figure 12 illustrates the generated SL with observation angle relative to laser propagation direction for different laser parameters; the data was collected by NRL [71; 74; 77]. As indicated by the plots, the SL increases with the observation angle for narrowband nanosecond laser pulse and decreases with the observation angle for broadband picosecond laser pulse.  
Figure 11: Acoustic source level as a function of laser pulse energy for non-linear photoacoustic generation with narrowband and broadband lasers.  
Figure 12: Acoustic source directionality for (**a**) narrowband nanosecond laser and (**b**) broadband femtosecond laser.
## 5 Experiments  
Next, we conducted experiments on six real-world datasets to demonstrate the effectiveness of DSTGFCN in traffic speed or flow prediction tasks. In this section, we will first introduce the datasets, experimental settings, evaluation metrics, and representative baselines. Next, we will discuss the experiments comparing the performance of DSTGFCN against other baselines. Furthermore, we conducted ablation experiments to assess the impact of individual components in the model on predictive performance. Finally, we will visualize the predicted values and dynamic adjacency matrix for a more intuitive understanding and evaluation of the model.