esa-sceva/satcom-chunk-collection huggingface dataset:
# Array Design and Transmitter Coils Selection for Underwater Wireless Power Transfer System
## 2 UWPT System for AUVs  
Aiming at the problem that the coupling mechanism offset caused by water flow disturbance affects the transmission efficiency in a complex marine environment, an array underwater wireless power transfer system suitable for AUVs was designed in this chapter. The coupling mechanism of the system adopts an array design, which expands the charging range and improves the anti-offset ability of the system. The working diagram of the UWPT system is shown in Figure 1.  
The array UWPT system adopts the S-S compensation network topology, and its simplified circuit diagram is shown in Figure 2. The system includes a high frequency inverter and rectifier, compensation capacitors \(C_{\text{a}}\) and \(C_{\text{b}}\), switch S11 to S33, transmitting array coil TX(1, 1) to TX(3, 3), and receiving coil RX. In the process of power transmission, the optimal power supply coil switch is closed by determining the position of the receiver, so that the power supply coil is connected to the compensation capacitor and the inverter; the other array coils are in the open circuit state.  
The S-S compensation topology was chosen for its simplicity and array compatibility: it provides stable impedance at 85 kHz, reducing complexity in 3 \(\times\) 3 array switching.
## 2 Materials and Methods
### Measurement of Odorous Volatile Organic Compounds  
Odorous VOCs, such as sulfur-containing VOCs, volatile fatty acids (VFAs), and phenolic compounds, are significant contributors to livestock odor [14]. VOC analysis was conducted in the same way as described in detail in the previous study [15]. Briefly, VOC samples were collected in 1 L gas sampling glass bulbs. An internal standard (hexane) was used to minimize variability in sampling and sample preparation. A 2 cm DVB/Carboxen/PDMS solid-phase microextraction (SPME) fiber (Supelco, Bellefonte, PA, USA) was used to extract VOCs from the glass bulbs for 50 min, then analyzed with a GC-MS within 12 h of sample collection. The NIST mass spectral library (with at least 80% spectral match) was used to confirm the compounds' identity. A set of 15 standards for targeted odorous VOC were used (acetic acid, propionic acid, isobutyric acid, butyric acid, isovaleric acid, valeric acid, hexanoic acid, dimethyl disulfide, diethyl disulfide, dimethyl trisulfide, guaiacol, phenol, \(p\)-cresol, 4-ethyl phenol, indole, and skatole) and calibrated to verify the GC retention time and MS spectral signal.
## 2 Materials and Methods
### Digital Elevation Data  
For digital topographic data, the 30 m SRTM and the 12.5 m ALOS PALSAR terrain dataset were used. Drainages were extracted based on a procedure by [25], with drainage pathways and flow accumulation delineated with the widely used 8D flow direction algorithm [17; 26]. Drainage networks were generated using a threshold of 2000 cells and were then compared against the actual subsurface channels revealed in Sentinel-1 and PALSAR radar scenes. A good agreement was found between the derived drainage networks and those revealed by radar images, validating the hydrologic delineation process.  
All the above data were projected to the Universal Transverse Mercator (UTM) and WGS84 datum. Satellite images and terrain model processing were carried out using ENVI 5.4 software and SARscape \"image processing workbench\" (Exelis Visual Information Solutions, Boulder, CO, USA) as well as ArcGIS 10.5.1 software (Environmental Systems Research Institute, Redlands, CA, USA). The above data were grouped in a geographic information system (GIS) to allow overlaying and correlation of the surface and near-surface features. Each data source added significant information which facilitated a clear examination of the Rimaal structure. In fact, the adopted procedure which utilizes optical and radar data was proven by the author to be effective in revealing crater structures is sandy desert regions, such as the Ibn-Batutah structure in Libya [9].
## 4 Results
### Occurrence Probabilities  
As was seen in our evaluations of boundary layer states and shape factors, the occurrence of high values for \(s_{p}^{2}\) (a highly non-Gaussian behavior) stems from a non-linear, dynamic process with chaotic phases, for which the term _intermittency_ was introduced [27]. The occurrence probabilities for all of our 119 measurements are listed in Table 3.  
In the first row, the number of states is listed for all measurements. We see much more unstable (84) than neutral (23) or stable (12) conditions. The subsequent two rows list the numbers for offshore and onshore locations with their states. In the fourth row, the tallies for high shape factor events are listed for all measurements. The probability for the occurrence of a high-\(s_{p}^{2}\) event at a specific boundary layer state is shown in the next line. The same was done for both locations, offshore and onshore.  
To correctly interpret the data, one has to know the circumstances of the measurements. The onshore measurements took place in spring 2008 between March and May. During this time of year, the ground begins to warm up slowly while the air heats up much faster, yielding stable conditions. Project specific constraints limited the offshore measurement campaign to a period in late summer and autumn 2010. At this time of year, the sea is still heated up from the summer and warms the air near the surface, while the air temperature subsides, and many unstable conditions can be observed.  
The focus was laid on the onshore measurements for the relation between the boundary layer state and the occurrence of high shape factors in the turbulent pressure fluctuations. With a joint probability of about 16.7%, a high-\(s_{p}^{2}\) was found for unstable and neutral states (7 out of 42, see Table 3). However, in stable conditions, a high-\(s_{p}^{2}\) was not observed. So, we propose that turbulent fluctuations in the pressure may deviate from a normal distribution much more frequently under unstable or neutral boundary conditions than under stable conditions.
## 3 Results Analysis and Discussion
### The Effect of Fiber Content on Soil Behavior  
Within the scope of the study, fiber reinforcement was added to the soil at two different additive rates 1% and 2% by weight, and the effect of the fiber additive ratio on the bearing capacity was investigated. The fiber contents determined in the experimental study were selected as a result of the studies in the literature. When the fiber content is increased from 1% to 2%, it has been observed that the ultimate bearing capacity increases. When the fiber content does not exceed a certain amount, the fiber is effectively dispersed. As the fiber content increases, it affects the contact area between the fiber and the soil, affecting the cohesion and friction between the fiber and the soil. Similar observations were made by [PERSON] et al. [59] on natural and synthetic fiber-reinforced soil. Therefore, when the fiber content was increased from 1% to 2%, a larger contact area occurred in the soil and improved mechanical properties. When the tests were examined among themselves, the effect of fiber content was mostly obtained from tests with glass + macromesh fiber reinforcement (80%) with Dr = 30% Fl = 24 mm, reinforcement depth 2B, and it was obtained from tests (73%) with macromesh fiber reinforcement with Dr = 30% Fl = 48 mm, reinforcement depth B. However, as the fiber ratio increased, difficulties began to be experienced in placement. In addition, as the fiber content increased, it was observed that the amount of increase in the bearing capacity ratio decreased, especially in model tests performed at Dr = 50% relative density. If the fiber content is increased too much, the fibers may begin to show a tendency to agglomerate. As a result, the fibers do not effectively increase the contact area. They can reduce the effectiveness of the fiber by creating a weak surface in the soil. These results are consistent with those found by [PERSON] et al. [57]. According to [PERSON] and [PERSON] [60], increasing the fiber content above a certain point lessens the interaction between soil particles and, as a result, results in less cohesion being mobilized, which lowers the shear strength of the fiber soil composite. Therefore, the contribution rate was not increased above 2% in the tests. In addition, when the fibers were evaluated among themselves, the increase in the bearing capacity with the increase in fiber content was observed in the macromesh fibers the most. This is mostly related to the dispersibility of the fiber [61]. Even after the glass fibers are added to the soil and mixed well, they are mostly dispersed in the soil in bundles. This reduces the benefit to be gained from increased fiber content. Although basalt fibers showed better dispersibility than glass fiber, they were not as effective as macromesh fiber.
## 3 Results and Discussion  
### 30 Kc19\(\alpha\) Protein Expression and Its Intracellular Delivery  
First, we produced 30 Kc19\(\alpha\) and full-length 30 Kc19 proteins in soluble form in an _E. coli_ expression system. Recombinant plasmids were designed to express target proteins with a T7-tag at the N-terminus and a 6 \(\times\) histidine tag at the C-terminus (Figure 1a). Theoretical molecular weights (MWs) of 30 Kc19\(\alpha\) and 30 Kc19, including said tags, are about 13 kDa and 30 kDa, respectively. Western blot and SDS-PAGE analyses for soluble cell lysates revealed that 30 Kc19\(\alpha\), like 30 Kc19, as demonstrated in our previous study [28], was successfully expressed as a soluble form (Figure 1b,c). To compare the production yield, we repeated large-scale productions (4 L culture scale) for 30 Kc19\(\alpha\) and 30 Kc19 twice. Although production yields per unit culture scale for finally purified 30 kc19\(\alpha\) and 30 Kc19 were different (23.35 \(\pm\) 2.51 mg/L and 47.43 \(\pm\) 8.53 mg/L, respectively), the molar productivity of 30 kc19\(\alpha\) was similar to that of 30 Kc19 when it was converted into moles in consideration of the MW difference between the two proteins (Figure 1d). According to results of predicting the solubility of 30 kc19\(\alpha\) and 30 Kc19 from amino acid sequences using a web-based tool [31], the solubility of 30 kc19\(\alpha\) was significantly higher than that of 30 Kc19 (0.836 vs. 0.547). This implies that 30 kc19\(\alpha\) might exhibit a higher soluble expression than 30 Kc19 in an _E. coli_ expression system. However, no significant difference in molar productivity between 30 kc19\(\alpha\) (a part of 30 Kc19) and the full-length 30 Kc19 protein was observed as shown in this study. This might be due to the lack of optimization in the recombinant protein production using the _E. coli_ expression system. Further studies on various factors related to 30_kc19\(\alpha\)_ expression, such as medium composition, pH, dissolved oxygen control, temperature, duration of culture, and so forth, are needed to achieve a precise comparison of the productivity of 30 kc19\(\alpha\) and 30 Kc19 in an _E. coli_ expression system.  
Next, to determine whether 30 kc19\(\alpha\) could penetrate into EPO-CHO cells, cells were treated with 30 kc19\(\alpha\) for 4 h. It has been revealed that the ability of 30 Kc19\(\alpha\) to deliver cargo proteins into cells is a little higher than that of 30 Kc19 [28]. The results of the immunofluorescence analysis revealed that the intracellularly delivered 30 Kc19\(\alpha\) was detected as expected. However, there was no significant difference in the cell-penetrating abilities between 30 Kc19\(\alpha\) and 30 Kc19 (Figure 2). Such similar cell-penetrating abilities of 30 Kc19\(\alpha\) and 30 Kc19 shown above might be due to the non-quantitative nature of immunofluorescence analysis.
## 3 Methodology and Materials
### Methodology  
#### 3.1.1 Data Rationale and Technical Superiority  
As an indispensable tool in modern life, mobile phones provide a reliable foundation for population data acquisition through signaling records. In China, 99.8% of Internet users access services via mobile devices, ensuring the near-universal coverage of signaling data. Originating from the 1990 studies pioneered by the University of Maryland and INRETS, mobile positioning technology has evolved into a robust tool for mapping population distributions and mobility patterns [51]. [PERSON] et al. demonstrated its efficacy through dynamic OD matrix estimation using 1 million user records in the Boston Metropolitan Area [52]. Chinese scholars like [PERSON] established technical frameworks for megacity spatial planning using signaling data, addressing key urban issues including population distribution, commuting patterns, and job-housing balance [53]. This study utilizes mobile phone signaling big data to measure human mobility and comprehensively analyze the development dynamics of interstitial urban spaces, providing scientific support for urban planning. Mobile phone signaling data are collected by telecommunication operators during routine network maintenance, recording the geographical location information of mobile users. Specifically, base stations track user activities--such as powering on/off, making calls, sending and receiving text messages, and other network interactions in real time--generating signaling data at intervals of 5 to 10 min. Each signaling record contains a timestamp, spatial coordinates, and the socioeconomic attributes of the user, forming a complete dataset of individual movement trajectories and stay points.  
By aggregating and integrating massive volumes of mobile phone signaling data, a population movement trajectory database with spatiotemporal continuity and comprehensive spatial coverage can be constructed. Compared to traditional static statistics or travel frequency data, mobile phone signaling data exhibit superior real-time characteristics, dynamic adaptability, and continuity [49, 50, 54]. With a spatial resolution typically ranging from 200 to 1000 m, these data enable the precise localization of users' actual activity locations, facilitating an efficient mapping of human spatiotemporal behaviors onto geographic space [55]. Consequently, mobile phone signaling data serve as a scientifically robust foundation for quantifying intercity human mobility, offering a precise method to assess developmental linkages between interstitial urban spaces and their surrounding cities.
## 3 Results and Discussion
### Methane Equivalent
#### 3.4.2 Industrial Interest and Major Challenges of the Technology  
The proposed electrochemical regeneration (with CO\({}_{2}\) capture) consumes the same amount of energy as the classical thermal process without CO\({}_{2}\) capture. However, compared with the thermal process with CO\({}_{2}\) recovery, the electrochemical process is clearly attractive from an energy point of view. In addition, this technology has the advantage of converting H\({}_{2}\)S directly into H\({}_{2}\) and solid S in the same unit as the regeneration of the solvent. This technology might therefore be more compact. In addition, instead of burning methane to regenerate the solvent, the use of renewable electricity can be considered for the electrochemical regeneration, which will reduce the associated CO\({}_{2}\) emissions. This technology might be 100% selective between H\({}_{2}\)S and CO\({}_{2}\) and allow for a recovery of 100% of the CO\({}_{2}\). Because electrochemical regeneration takes place at lower temperature, the amine will be less degraded, resulting in less solvent losses as well as less potential emissions of harmful compounds. Finally, in the thermal process, the regeneration takes place at atmospheric pressure. The electrochemical process can be operated at higher pressures, partially avoiding repressurization of the CO\({}_{2}\) for storage or reuse.  
There are, however, many questions and challenges related to the new electrochemical process. One of the major constraints is to find a couple amine-metal suitable for not only the electrochemical regeneration process but also attractive for the absorption process. The CO\({}_{2}\) absorption properties of aqueous EDA have been studied, and EDA seems comparable to MEA (monoethanolamine) [26; 27; 28]. More work is definitely required, not only on the CO\({}_{2}\) but also on the H\({}_{2}\)S absorption properties because the treated gas often needs to respect stringent specifications (typical 4 ppm H\({}_{2}\)S), which are challenging to meet with primary or secondary amines. Another challenge is that side reactions might occur on the electrodes, resulting in more compounds (e.g., sulfur compounds, CO, etc.). Moreover, the practical removal of the products (gaseous H\({}_{2}\), gaseous CO\({}_{2}\), and solid sulfur) raises questions. Another important point is the quality of the sulfur, which should be comparable to the high purity obtained with the Claus unit. The potential precipitation of iron is also a potential challenge.
## 4 Performance Analysis of the BOC Signal and BPSK Signal
### Data Demodulation with Difffferent BOC and BPSK Ratios  
According to Equation (6), the communication signal and the BOC signal are orthogonal in the time domain. Therefore, as long as the chip accumulation time of the BPSK signal is the length of one chip of the BOC signal, the BOC signal cannot affect the demodulation of the BPSK signal. The bit error ratios (BERs) of the BPSK signal at different SNRs and ratios are shown in Figure 11. This shows that the demodulation of the BPSK signal is only influenced by the BPSK signal power in the composite signal. When the proportion of the BPSK signal in the composite signal is 50%, the signal power needs 3 dB more than the pure BPSK signal to meet the same BER.
# Impacts of Integration of Wind Farms on Power System Transient Stability
## 4 Case Studies, Results and Discussion  
As shown in Figure 4, the modified 4-generator 14-bus IEEE system is used as the benchmark to investigate the impacts of adding wind farms (WFs) or capacitors on system transient stability. In this system, the dynamic models of four conventional generators are 4 th order for transient stability analysis, while each generator is equipped with a IEEE Type 1 exciter. For wind farms, an aggregated model is used to investigate wind generation impact on the system transient stability [23], the DFIG  
Figure 3: Block diagram of FMAC controller.  
Figure 2: Structure of Doubly Fed Induction Generators.  
parameters are cited from [22] with wind turbine parameters: \(K_{tw}\) = 0.6 p.u./rad, \(D_{tw}\) = 0.45 and \(H_{t}\) = 3.8 s. In this paper, the power system analysis toolbox (PSAT) developed by Dr. [PERSON] is used to conduct the transient stability analysis in this paper [20].
###### Abstract  
This paper deals with speech enhancement in dual-microphone smartphones using beamforming along with postfiltering techniques. The performance of these algorithms relies on a good estimation of the acoustic channel and speech and noise statistics. In this work we present a speech enhancement system that combines the estimation of the relative transfer function (RTF) between microphones using an extended Kalman filter framework with a novel speech presence probability estimator intended to track the noise statistics' variability. The available dual-channel information is exploited to obtain more reliable estimates of clean speech statistics. Noise reduction is further improved by means of postfiltering techniques that take advantage of the speech presence estimation. Our proposal is evaluated in different reverberant and noisy environments when the smartphone is used in both close-talk and far-talk positions. The experimental results show that our system achieves improvements in terms of noise reduction, low speech distortion and better speech intelligibility compared to other state-of-the-art approaches.  
Keywords:dual-microphone smartphone; beamforming; relative transfer function; speech presence probability; postfiltering +
Footnote †: _Appl. Sci._**2019**, 9, 2520; doi:10.3390/app9122520
# A Reverse Shortest Path Tree-Based Multicast Joining Node Selection Method
## 5 Conclusions  
One of the challenge of multicast technology is to efficiently establish downlink multicast paths in the case of asymmetric routing. To solve this problem, we propose an MJN selection algorithm based on the reverse shortest path tree (RSPT). DR constructs an RSPT for its k-hop subgraph. The RSPT has the DR as its root and consists of all of the shortest paths from other nodes in the k-hop subgraph to the DR. As long as the leaf nodes of the RSPT send probe messages to the DR, the DR can evaluate the cost of any multicast path in the k-hop subgraph and select the MJN with the lowest cost to join the multicast tree. This method can effectively cope with the establishment of downlink multicast paths (with MJN as the starting point and DR as the endpoint) in the case of asymmetric routing. Compared with existing methods, the proposed method has an extremely low path probing cost and delay, and can effectively balance the network load state, thereby increasing the number of multicast groups accommodated by the network.  
Conceptualization, Z.T., J.Y. and L.H.; methodology, Z.T. and J.Y.; software, Z.T.; writing--original draft preparation, Z.T.; writing--review and editing, Z.T., J.Y. and L.H.; supervision, J.Y. and L.H.; project administration, J.Y. and L.H.; funding acquisition, J.Y. and L.H. All authors have read and agreed to the published version of the manuscript.  
This work was funded by Strategic Leadership Project of Chinese Academy of Sciences: SEANET Technology Standardization Research System Development (Project No. XDC02070100).  
Not applicable.  
Data availability StatementData sharing is not applicable to this article.  
We would like to express our gratitude to [PERSON], [PERSON] for their support for this work.  
The authors declare no conflict of interest.
## 3 Medical Sensor Applications for Closed Spaces
### Analysis of Computational Requirements  
We compared the performance of the arrhythmia detection algorithm to select a set of processor architectures that would perform adequately. Presented in the previous section, the four types of processors currently used for deploying nodes in sensor networks were used: ARM7 TDMI, MSP430, PIC18, and MC9S08 GB60.  
For the analysis, the same operating speed of 8 MIPS was used for each processor. The total computation time of the implementation of the Pan and Tompkins algorithm is presented in Table 1. The total computation time was estimated using the sum of the individual function values of each architecture (derivation, squaring and integrating window). Results show that the ARM architecture requires a lower utilization rate (U), while the PIC architecture requires a higher utilization rate (U).  
Another aspect considered is the active mode power consumption (PA) of the four architectures during the execution of the Pan and Tompkins algorithm, which is related to the four architectures' power consumption in active mode with their respective percentage use of CPU capacity.  
Table 2 shows the PA \(\times\) U parameter. The ARM7 architecture has a value very close to the MC9S08 GB60 architecture. Therefore, these two architectures are suitable for use in this study. The MSP430 architecture has the lowest value, making it the best of the four architectures insofar as the PA \(\times\) U parameter is concerned.