esa-sceva/satcom-chunk-collection huggingface dataset:
# An Enhanced Adaptive Block Truncation Coding with Edge Quantization Scheme +
## 3 The Proposed ABTC-EQ
### The Proposed Schemes
Via Equation (13), we determine \(\mu^{\prime\prime}_{0}=61\), \(\mu^{\prime\prime}_{1}=83\), \(\mu^{\prime\prime}_{2}=115\) and \(\mu^{\prime\prime}_{3}=139\). Using quantization range in Scheme C, by the range \(R_{0}=(128\,64\,32\,16\,8\,4)\) and the condition satisfying \(\min[\mu^{\prime\prime}_{0}-\delta^{\prime}_{0}\;]\), we derive \(\delta_{0}=60\); by the range \(R_{1}=(64\,32\,16\,8\,4\,2)\) and the condition satisfying \(\min[\mu^{\prime\prime}_{1}-\delta^{\prime}_{1}-\delta^{\prime}_{0}\;]\), we derive \(\delta^{\prime}_{1}=22\); by the range \(R_{2}=(32\,16\,8\,4\,2\,1)\) and the condition satisfying \(\min[\mu^{\prime\prime}_{2}-\delta^{\prime}_{2}-\delta^{\prime}_{1}-\delta^{ \prime}_{0}\;]\), we derive \(\delta^{\prime}_{2}=33\); by the range \(R_{3}=(32\,16\,8\,4\,2\,1)\) and the condition satisfying \(\min[\mu^{\prime\prime}_{2}-\delta^{\prime}_{3}-\delta^{\prime}_{2}-\delta^{ \prime}_{1}-\delta^{\prime}_{0}\;]\), we derive \(\delta^{\prime}_{3}=24\)._  
Thus, the compressed data \((f=0,\delta^{\prime}_{0},\delta^{\prime}_{1},\delta^{\prime}_{2},\delta^{ \prime}_{3},M^{\prime\prime}_{e})\) is (0, 60, 22, 33, 24, 100110001110100 11010001) of 57 bits (\(\cdot\) \(|\delta^{\prime}_{0}|+|\delta^{\prime}_{1}|+|\delta^{\prime}_{2}|+|\delta^{ \prime}_{3}|=24\) bits), which is the same as [PERSON]'s ABTC-EQ (see Example 1). In reconstruction phase, the recovered values of \((\mu^{\prime\prime}_{0},\mu^{\prime\prime}_{1},\mu^{\prime\prime}_{2},\mu^{ \prime\prime}_{3})\) are (60, 82, 115, 139). Thus, the AMSE is 48.13. The AMBTC has the worst AMSE = 167.56, but it needs the least bits (32 bits) for representing a block. The above three examples imply that the AMSE = 48.13 of Scheme C is much lesser than those of other schemes (note: this significant improvement comes from the quad-clustering approach), and its number of required bits is the same as ABTC-EQ. Compared with ABTC-EQ, Scheme A has the same AMSE but has fewer bits for a block. About Scheme B, it can make a trade of the number of required bits for AMSE. For example, Scheme B-IV only needs 42 bits for a block, and meanwhile, the AMSE = 82.19 is far less than AMSE = 167.56 of AMBTC.
## 4 Analysis and Suppression Method of Short Circuit Current in MMC-Based MTDC Power Grid
### DC Short Circuit Current Suppression Method in MMC-Based MTDC Power Grid
#### 4.2.3 MMC Fault Current Suppression Control Strategy
The increasing rate of the DC short-circuit current with a current limiting measure significantly decreases. Figure 17: Flowchart of the proposed protection schemes. When compared with redesigning the MMC topologies and installing new current limiting devices, designing MMC control strategies for short-circuit current suppression can make full use of the control capability of MMCs and save capital cost.
## 5 Conclusions  
This study conducted a comprehensive assessment of the relative impacts of climate factors and vegetation changes on vegetation productivity in Northern China from 2001 to 2020. A significant correlation between forest coverage changes and GPP variability was identified, underscoring the positive effects of afforestation. The study also highlighted regional differences in the influence of various factors on GPP within ecological restoration areas. Forest coverage changes emerged as the primary driver of GPP in regions such as the Loess Plateau, western Inner Mongolia Plateau, and northern Xinjiang, while climate factors exerted a more substantial influence in areas like the eastern Inner Mongolia Plateau and northeastern regions. The findings emphasize the crucial role of forest changes, particularly through programs like the Three-North Shelterbelt Program, in enhancing vegetation productivity across Northwestern China, with the most significant impact observed in the Inner Mongolia Plateau and the Loess Plateau. In contrast, forest changes in the northeastern region had a lesser impact on GPP, where climate-related factors played a more dominant role. These results provide valuable insights for addressing desertification and inform decision-making for ecological restoration and sustainability efforts. Future research will aim to refine methodologies to further elucidate the contributions of these factors to vegetation productivities.  
Conceptualization, H.W. and K.L.; Methodology, H.W.; Formal analysis, H.W., X.W. and K.L.; Writing--original draft preparation, K.L. and H.W.; Writing--review and editing, H.W., X.W. and K.L.; Visualization, K.L. All authors have read and agreed to the published version of the manuscript.  
This study was funded by the National Natural Science Foundation of China (Grant Nos. 42371405 and 41871250), the Key Research Program of Gansu Province (Grant No. 23 ZDKA0004), and Youth Innovation Promotion Association CAS to X.W. (No. 2020422).  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
We are very grateful to the National Tibetan Plateau Data Center and the Resource, China Flux Observation and Research Network (ChinaFLUX), National Ecosystem Science Data Center and Environmental Science and Data Center of the Chinese Academy of Sciences for the availability of data.  
The authors declare no conflicts of interest.
## 2 Materials and Methods
### Characterizations  
The fabricated ZnO NRs were characterized by a variety of analytical, spectroscopic, and PV measurement techniques. For microstructure and surface morphology, a field emission scanning electron microscopy (FESEM, Hitachi 4800, Japan) was used. The confirmation of deposition of ZnO was verified by X-rays diffraction (XRD), photoluminescence (PL) spectroscopy and Raman scattering spectroscopy. The optical properties, such as reflectance of rod nanostructures, were investigated by ultraviolet diffused reflectance spectroscopy and recorded by a Shimadzu MPC-3100 scanning spectrophotometer in the wavelength range of 400-1200 nm. The detailed PV properties were derived by PC1D simulation by using the length of the ZnO NRs and the average reflectance as input parameters.
## 2 Instrument
For Krypton, LMM and LMN lines are well established from a range of experimental studies [26; 27; 28; 29; 30]. Figure 2a shows calibrated spectra from L\({}_{1}\), L\({}_{2}\), and L\({}_{3}\) Auger transitions taken with hxPES at different retardation voltages, which were each selected to focus on a particular kinetic energy region. Eight bands, labeled A-H, are identified. Note that for a fixed retardation voltage, resolution increases with decreasing kinetic energy. Transitions that are monitored at several retardation voltages are better resolved for higher retardation (temporal dispersion). The photon energy of 12 keV is below the K-shell ionization and was selected to prevent corresponding Auger cascades from contributing energy levels. The detector at 90\({}^{\circ}\) was used where direct photoionization lines are suppressed due to the horizontal polarization of the X-rays. The digitizer was configured to the highest available sampling rate of 4 GSs\({}^{-1}\). Enlarged regions of the spectra are presented in Figure 2b-f for comparison with literature data. Each transition leads to several final states, whereof the kinetic energies of the dominating states have been marked with vertical dashed lines in each panel. High agreement is found. We can confidently assign the Auger-Meitner transitions, and we estimate a calibration error of <5 eV. In particular, at the retardation voltage 1490 V and the transition L\({}_{2}\)M\({}_{4.5}\)M\({}_{4.5}\), the \({}^{1}S_{0}\) (1504.9 eV) and \({}^{1}G_{4}\) (1512.7 eV) final states are resolved. Thus, at around 1500 eV kinetic energy, a resolution of better than 8 eV is demonstrated. For hxPES, in addition to Krypton Auger-Meitner transitions, also Argon KLL and KLM [31] as well as Xenon LMM and LMN [32] lines were successfully used with this approach to validate the calibration. For sxPES, Neon KLL [33] and N\({}_{2}\) KVV [34; 35] transitions were used. Flight tubes are distributed in a plane oriented perpendicular with respect to the X-ray beam [19]. Recording signal intensity over the polar angle (\(\theta\)) allows for polarization measurements. For the fixed azimuth angle \(\phi=0^{\circ}\), the polarization function \(P(\theta)\) describes the photoemission intensity as a function of \(\theta\)[1],  
\[P(\theta)=1+\frac{\beta}{4}\bigg{(}1+3\cdot P_{L}\cos\Big{(}2(\theta-\psi) \Big{)}\bigg{)}. \tag{8}\]  
\(P_{L}\) is the linear polarization component and \(\psi\) is the tilt angle. Assuming no unpolarized contribution, the degree of circular polarization is given as \(P_{\mathrm{C}}=\sqrt{1-P_{L}^{2}}\). For perfect horizontal polarization, \(P_{L}=1\) and \(\psi=0\). \(\beta\) is the anisotropy parameter of the target gas electronic configuration and depends on the photon energy.
## 4 Experimental Test Results
### Variable Amplitude Fatigue Loading  
#### 4.2.1 Behavior of the A-Jointed Precast FDDP under VAF  
The precast FDDP specimen S2 underwent sinusoidal waveform fatigue load cycles with incremental step low cycle fatigue loading. The compressive strengths of concrete cylinders for the normal strength concrete (NSC) used to cast S2 were 54.29, 57.22, 59.98, 46.54, 65.84, and 64.7 MPa, with an average value of 58.10 MPa. The splitting tensile test for the NSC resulted in tensile strengths of 3.53, 5.73, 5.31, 4.3, and 4.7 MPa, with an average value of 4.71 MPa. The compressive strengths of the concrete cylinder used to fill the joints of the UHPFRC were 154.17, 188.12, 184.61, and 181.91 MPa, with an average value of 179.52 MPa. The splitting tensile test for the UHPFRC resulted in tensile strengths of 15.12, 12.14, and 15.76 MPa, with an average value of 14.42 MPa.  
The first 501,002 fatigue load cycles were performed at a frequency of 2 Hz, then followed by 160,242 cycles at 1 Hz, and finally by 130,139 cycles at 0.5 Hz, leading to punching shear failure at a total number of cycles of 809,493. Figure 11a depicts the 60-mm-deep punching shear failure at the wheel footprint on top of the slab, while Figure 11b depicts the crack pattern at the bottom surface of the slab at failure. One may observe the radial cracks starting from the location of the footprint of the wheel load and propagating toward the support line in a fan shape. At failure, concrete spalling appeared in some parts of the bottom side of the large slab on one side only of the closure strip as a sign of punching shear failure. However, concrete spalling appeared to deviate from the traditional shape for punching failure (close to circular shape at the end of diagonal cracks through slab thickness). However, a major flexural crack appeared at failure just under the wheel load, extending in the direction of the girder towards the free end of the small FDDP segment while crossing the closure strip, as depicted in Figure 11b. This precast FDDP failed at a jacking load of 487.50 kN and a maximum slab deflection of 32.46 mm. It is worth mentioning that such a failure load is about 2.34 times the CHBDC factored design wheel load. Figure 12 depicts the monotonic load-deflection relationship of the slab S2 after each 100,000 fatigue load cycles. It can be observed that the slope of the curve decreased, leading to a reduction in slab flexural stiffness, with an increase in the number of VAF load cycles. Tables 4 and 5 summarize the test data for all specimens with A-joints, C-joints, and Z-joints under CAF and VAF loading.
# Vibration Energy Harvesting from Raindrops Impacts: Experimental Tests and Interpretative Models
## 4 Video Analysis  
During indoor tests, in parallel with voltage measurements, a video analysis of the impact of the drops was performed. The objective of the analysis was to find any correlations between the movement of the water and the voltage peaks. For this analysis, only position 2 of Figure 6 was considered. Both empty and full spoons were studied, with multiple tests. Camera footage was recorded by means of a Teledyne Dalsa Genie Nano G3-GM10-M0640 camera, with an acquisition rate of 400 fps full-frame, an exposure time of 1000 ms, and Turbo Transfer Mode enabled. The camera was equipped with a telecentric lens Computar TEC-55. To reduce external disturbances, a light source of 625 nm was projected onto the camera sensor by means of a Phlox-LedR-BL-LLUB-Q-1R-24V, a device designed to emit a uniform beam of parallel light rays at a specific wavelength, and the corresponding red filter BP635-43 was installed on the camera lens.  
The bending of the harvester, due to the impact of the drop with the dry spoon, was so small as to be nearly imperceptible in the footage (see Figure 8). Such a small bending directly reflects on the amplitude of the output voltage as found in Section 3. Since with the empty spoon the drop has no other water to interact with, the collision can be considered inelastic. As a consequence, the voltage rapidly reaches its maximum value and then the damping of the system slowly reduces the amplitude of the response in the subsequent milliseconds.  
Figure 9 shows the footage of the full spoon, which is much more interesting: the movement of the water and the bending of the harvester are much more noticeable, as well as the output voltage amplitude. Before the water hits the spoon, the harvester is slightly bent under the gravitational force of the 2.5 mL of water. The timeframe for both the footage and the output voltage has been reset at the impact of the drop with the water. When the drop hits the water (0 ms in Figure 9), at first the impact force moves the spoon downwards, since also the water reacts in a similar manner to a rigid mass. However, in the subsequent milliseconds, the water that interacts with the drop starts moving upwards, whereas a crater is left under the free surface. The movement of the water upwards continues until it reaches its maximum height, and a full crown surrounds the impact site (4.1-8.3 ms in Figure 9). Then, the crown collapses (from 12.5 to 25 ms in Figure 9). After the crown collapse, the water mass keeps moving before returning to its initial state. However, at this stage, the water motion is essentially a sloshing motion (see Figure 9 from 66.7 to 86.4 ms), i.e., the water moves in a direction that is no longer perpendicular to the harvester but parallel. Therefore, the water dynamics no longer affect the dynamics of the harvester, which continues vibrating according to its free response.  
Figure 8: Drop impact on a dry spoon. The displacement due to the bending of the harvester is negligible with respect to the size of the spoon, even in the first vibration cycle.
# Asynchronous Chirp Slope Keying for Underwater Acoustic Communication
## 2 Materials and Methods
### Experimental Set-Up  
We conducted two experimental runs to verify our approach. One of a single band transmission, the other of a dual-band transmission. The experiments were performed in a steel-walled pool as shown in Figure 7, which was assembled temporarily inside a building. The transmitter and receiver hardware is a modified version of the indoor localization system [51], as we published before [19; 36].
## 3 System Functional Modules  
### Embedded Operating System ZKOS  
The proprietary embedded operating system ZKOS (Shingle Operation System) has a small amount of code, and is less dependent on system hardware features such as stacks, registers, timers and interrupters. Therefore, it can be implemented on different types of mono-chips [8]. The architecture of embedded ZKOS operating system is shown in Figure 3.  
Figure 1: Architecture of greenhouse monitoring system based on wireless sensor network.  
Figure 2: Topological structure of the system.  
ZKOS is a preemptive, priority-based, real-time, and multitasking operating system kernel, in which the high priority tasks with displace low priority tasks based on CPU privilege; the priorities of each task are different, therefore, the operation sequence of the tasks are arranged by the system according to these priorities. The real-time features of the tasks with high priority are thus ensured, and the scalability of the functions is improved by the multi-tasking feature. Additionally, ZKOS also features protection of shared resources.
# Software-Defined Named Data Networking in Literature: A Review
###### Abstract  
This paper presents an in-depth review of software-defined named data networking (SD-NDN), a transformative approach in network architectures poised to deliver substantial benefits. By addressing the limitations inherent in traditional host-centric network architectures, SD-NDN offers improvements in network performance, scalability, and efficiency. The paper commences with an overview of named data networking (NDN) and software-defined networking (SDN), the two fundamental building blocks of SD-NDN. It then explores the specifics of integrating NDN with SDN, illustrating examples of various SD-NDN models. These models are designed to leverage SDN for NDN routing, caching, and forwarding. The paper concludes by proposing potential strategies for further integration of SDN and NDN and some open research questions. These proposed strategies aim to stimulate further exploration and innovation in the field of SD-NDN.  
SDN; NDN; IOT; caching; forwarding; routing; network architecture  
and distributing routing and forwarding tables, handling data naming and matching, and managing in-network caching [5]. Leveraging SDN to relieve NDN routers of routing responsibilities, thus allowing them to focus solely on data forwarding, can significantly enhance their performance. In addition, transferring the routing task to a centralized control unit can provide a comprehensive network perspective, facilitating the development of more efficient in-network caching strategies for NDN. Furthermore, this global network perspective can bolster support for consumer and producer mobility within the NDN framework.  
While merging NDN with SDN offers numerous benefits, compatibility issues between existing SDN protocols/controllers and NDN persist [5]. This necessitates either modifying current SDN protocols/controllers or developing new ones suitable for NDN while preserving the key features of both architectures. This paper surveys the various software-defined named data network models in the literature, compares them, and then provides a list of open research questions and potential strategies for SD-NDN.  
The paper is structured as follows. First, we provide an overview of NDN and SDN. Following this foundational understanding, we proceed with a comprehensive survey of various implementations that leverage the advantages of both NDN and SDN. Subsequent to this survey, we discuss the surveyed implementations and provide insights into open challenges, potential strategies, and open research questions. Finally, we conclude by summarizing our findings and presenting our conclusions.
## 3 Results
### Effect of the Cooling Water Flow Rate
The condensation efficiencies obtained in the cases when the cooling water flow rates were 60 kg/h and 120 kg/h were about 50%. The temperature distributions at higher inlet flue gas temperatures and different cooling water flow rates presented in Figure 5c,d do not differ much from the cases at lower inlet flue gas temperatures (Figure 5a,b). The difference is slightly higher temperature values when the flue gas inlet temperature is increased. In the case presented in Figure 5c, the difference between the wall and dew point temperatures at the beginning of the tube is small, and therefore the heat transfer is rather low (Figure 6b, Nu\({}_{\rm t}\approx\) 25). However, as the difference between those two temperatures increases, the condensation heat transfer also increases rapidly and at x/d \(\approx\) 120 the maximum value of Nu\({}_{\rm t}\approx\) 415 is reached. As a certain part of the water vapor had condensed until x/d \(\approx\) 120, the influence of condensation heat transfer gained a weakening character, and thus, the heat transfer from x/d \(\approx\) 120 until x/d \(\approx\) 170 was decreasing. Despite that, the Nu\({}_{\rm t}\) at the tube end remained high, i.e., Nu\({}_{\rm t}\approx\) 300 (Figure 6b). For cooling water flow rate of 120 kg/h, due to a larger temperature difference between the wall and dew point (Figure 5c), the heat transfer at the initial part of the heat exchanger was much intense (Figure 6b, Nu\({}_{\rm t}\approx\) 175) in comparison with the water flow rate of 60 kg/h. Farther along the tube, it increased slightly up to Nu\({}_{\rm t}\approx\) 225 at x/d \(\approx\) 120. After that, due to previously discussed reasons, it started decreasing. At the tube end, the Nu\({}_{\rm t}\) remained high (Figure 6b, Nu\({}_{\rm t}\approx\) 190). The condensation efficiencies at water flow rates of 60 kg/h and 120 kg/h were determined to be almost the same, i.e., about 42%. The efficiencies in the case of Re\({}_{\rm in}\approx\) 21,000 were smaller than in the case of Re\({}_{\rm in}\approx\) 9500. This happened because the flue gas of a higher Re\({}_{\rm in}\) number moves faster through the experimental setup, spends less time in it and, therefore, a decreased condensation efficiency is obtained. For comparison purposes, all the local Nusselt number distribution results for Re\({}_{\rm in}\approx\) 21,000 are presented in Figure 7. As the Figure shows, at a higher cooling water flow rate, Nu\({}_{\rm t}\) remains more constant along the tube. This leads to a conclusion that the condensation in this case is more even.