esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Temperature Variation Regularity of K67+300 Subgrade Section
The maximum temperature difference was 3.4 \({}^{\circ}\)C. However, with the increase in depth, the temperature difference became smaller and smaller. When the underground depth was 1 m, the temperature of the two boreholes was approximately the same. According to the geological survey report, the seasonal active layer depth of frozen soil was 0.9 m. It can be seen that the surface vegetation mainly influences the ground temperature of the seasonal active layer. From the perspective of time, the period with a large temperature difference between borehole T1 (with vegetation cover) and borehole T2 (no vegetation cover) was mainly in July, August, September, and October. However, as time went on, the difference gradually decreased. Since November, the temperature of the two boreholes gradually approached one another. It is shown that the influence of surface vegetation on ground temperature was mainly concentrated in summer and autumn, that is, the warm seasons. The vegetation could reflect a large amount of solar radiation in the warm seasons, reducing its reach to the ground, which could prevent the ground from warming too fast. Figure 7: Variation of monthly average underground temperature at the same depth of borehole T1 (with vegetation cover) and borehole T2 (no vegetation cover) in 2020. In winter, that is, the cold season, vegetation could increase the underground temperature. However, due to the more significant impact of snow cover, the regularity of the impact of vegetation on temperature was not obvious in the Greater Khingan Mountains forest region. Snow cover had the characteristics of high reflectivity, high latent heat of phase change, and low thermal conductivity. In the permafrost region of the Great Khingan Mountains, snowfall activities were frequent. The snow cover period was long, from November to May of the next year. This would undoubtedly have a great impact on the heat exchange between the frozen soil and the atmosphere. On the one hand, the high albedo of snow was conducive to the cooling of the surface and the underlying soil layer. On the other hand, the snow had a good thermal insulation effect due to its low thermal conductivity, which could reduce the heat loss in rock and soil in winter. However, in spring, the heat dissipation of rock and soil would be correspondingly reduced and delayed, leading to the rise of soil temperature, and aggravating the melting of permafrost. In general, for permafrost, vegetation cover has a cooling effect in the warm season and a warming effect in the cold season. Relatively, the cooling effect of vegetation cover on permafrost in the warm season is more significant.
## 2 Implementation of FPGA-Based On-Board SAR Processor
### SAR Image-Formation Algorithm  
In the application of digital SAR processing, signal processing poses a significant challenge because of its stringent computation-power and data-storage requirements. A high-resolution SAR system captures return echoes and yields huge amounts of raw data. The size of these data is dependent on several parameters, such as dynamic range, spatial resolution and sampling frequency of the SAR system. In the software layer of the digital SAR processor, the most commonly used SAR processing techniques and algorithms are the range-Doppler algorithm (RDA), chirp scaling algorithm (CSA) and the Omega-K algorithm (\(\omega\)KA) [22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34].  
Figure 1: Embedded SAR processor block diagram.  
RDA is a simple and mature SAR image-processing algorithm with a relatively small computation load. It is suitable for real-time processing. Basically, it divides the SAR echo-signal-processing into two one-dimensional processes in cascade, i.e., range compression followed by azimuth compression. If the size of the range migration is not more than one range resolution cell, i.e., the target impulse response is within the range resolution in a cell, it can be considered as a straight line. Thus, compensation for range-cell migration is not required. In summary, real-time signal-processing algo-rithms for airborne SAR can be implemented by RDA. An RDA block diagram is shown in the Figure 2.
## 3 Results of Long-Term Triaxial Creep Tests at Different Temperatures  
To achieve a complete stress-strain curve, water in a triaxial cell was prevented from penetrating the surface of a cylindrical specimen during a test by covering the specimen's surface with a bitumen membrane. The specimens were tested by applying different pre-set temperatures. Initially, the vertical axial stress was equal to the radial stress. The tests were run by applying a pre-set constant radially confining stress level and increasing the axial stress in a stepwise manner. The long-term triaxial creep test results at different temperatures and the radially confining stress levels are shown in Figures 1-5.  
\begin{table}
\begin{tabular}{c c c c} \hline  & \multicolumn{2}{c}{**Sieve Size (mm)**} & \multirow{2}{*}{**Bitumen Content**} \\ \cline{2-3} \cline{1-1}  & **9.5–19** & **4.75–9.5** & **0–4.75** & **0–0.075** \\ \hline Ratio (\%) of mineral weight & 16 & 24 & 52 & 8.0 & 6.8 \\ \hline \end{tabular} Note: The total filler content (<0.075 mm) was 13% of the mineral weight. As the fine aggregates (0–4.5 mm) contained 5% filler, 8% imported filler was added to make the total filler content 13%.  
\end{table}
Table 1: Asphal concrete recipe used for the Quxue Dam core [3].  
Figure 1: Axial strain and volumetric strain versus time for dam core specimens under various radially confining stress levels and at 5 \({}^{\circ}\)C with a stepwise increase in axial stress (unit: MPa). (**a**) Confining stress of 0.5 MPa. (**b**) Confining stress of 0.8 MPa. (**c**) Confining stress of 1.0 MPa.  
Figure 2: Axial strain versus time for dam core specimens under various radially confining stress levels and at 15 \({}^{\circ}\)C with a stepwise increase in axial stress (unit: MPa). (**a**) Confining stress of 0.5 MPa. (**b**) Confining stress of 1.0 MPa (**a**) Confining stress of 1.5 MPa.  
Figure 4: Axial strain and volumetric strain versus time for dam core specimens under various radially confining stress levels and at 25 \({}^{\circ}\)C with a stepwise increase in axial stress (unit: MPa). (**a**) Confining stress of 0.5 MPa. (**b**) Confining stress of 1.0 MPa.  
Figure 3: Axial strain and volumetric strain versus time for dam core specimens under various radially confining stress levels and at 20 \({}^{\circ}\)C with a stepwise increase in axial stress (unit: MPa). (**a**) Confining stress of 0.5 MPa. (**b**) Confining stress of 0.8 MPa. (**c**) Confining stress of 1.0 MPa. (**d**) Confining stress of 1.5 MPa.  
Figures 1-5 indicate that the strain due to axial creep increasingly approached a constant value over time at low levels of deviator stress. When the deviator stress level was increased to a high value, the axial stain continued to increase until the strain started to accelerate and the specimen failed.  
Figure 1c, Figure 3a,c,d and Figure 4 show that the volumetric strain responded with time in a similar way to the axial strain. All of the volumetric strains were compressive strains. A few tests (Figures 1c, 3a and 4b showed some instantaneous dilation in the volumetric strain due to the swift imposition of an increase in deviator stress during the tests.
## 5 Fault Location in Direct Current (DC) Grid Having Cable and Overhead Line Segments
### Identification of Faulty Line Segment  
Ideally, the fault location is supposed to be known. However, practically, this is not known. An arrival time of the TW is measured at two ends of TL. Therefore, an arrival time difference is calculated. Hence, it is always important to identify the faulty segment to make it possible to find the location of fault. This is achieved by following the steps as explained in the Figure 5. For instance, consider an event in which dc fault occurs in the middle segment (\(L_{2}\)). The actual difference between the arrival time of traveling waves at two ends of TL is given by Equation (15). Now the estimated value of \(x_{F1}\) Is calculated by the substitution of \(\Delta t_{12}\) From Equation (15) into (12) and the result is:  
\[x_{F1}=L_{1}+x_{F2}\times\frac{v_{1}}{v_{2}} \tag{21}\]Since \(\left(\frac{v_{1}}{v_{2}}\right)>0\), therefore \(x_{F1}>L_{1}\). Hence, fault is not present in segment \(L_{1}\). Similarly, putting the estimated value of \(\Delta t_{12}\) From Equation (15) into (20) results:  
\[x_{F3}=(x_{F2}-L_{2})\times\frac{v_{3}}{v_{2}} \tag{22}\]  
Since \(\left(\frac{v_{2}}{V_{2}}\right)>0\), therefore, \(x_{f2}>L_{2}\). Hence, the estimated value of \(x_{f3}\) would be negative which is a clear indication that fault is not present in \(l_{3}\). In this way, faulty segment is identified and voltage samples measured at VSCs are used to trace the fault location in the faulty segment. This method can be extended to n number of heterogeneous segments and generalized fault location equation for a fault segment identification is:  
\[x_{Fi}=\Delta t_{12-Fi}-\frac{L_{1}}{v_{1}}-\frac{L_{2}}{v_{2}}-\ldots-\frac{L _{i-1}}{v_{i-1}}+\frac{L_{i+1}}{v_{i+1}}+\ldots+\frac{L_{n-1}}{v_{n-1}}+\frac{ L_{n}}{v_{n}} \tag{23}\]
# Omnidirectional Haptic Guidance for the Hearing Impaired to Track Sound Sources
## 6 Conclusions  
We conducted an experiment in which a subject wearing an eye mask and the developed hearing assistance system was able to track a single sound source. The subject was notified of the movement of the sound source by the vibration of vibrators on both shoulders according to the distance and direction to the sound source estimated from acoustic signals detected by the ear microphone. The ratio of the vibration intensity of the two vibrators varied according to the angle of the sound source: the closer to the sound source, the stronger the vibration intensity, thereby presenting the relative angle of and distance to the sound source to the subject.  
A subject wearing an eye mask and a hearing assistance system was able to track the direction of a sound source moving across the room 2 m in front of him with an accuracy of less than \(5^{\circ}\).
2. When the subject turned his face in the direction where the vibration intensity of both vibrators became equal, he could perceive the approach of the sound source as a change in vibration intensity.  
We conducted a tracking experiment for a sound source moving only 2 m ahead in a room. Although the experimental conditions were not very practical, the original purpose of this study was to detect the location of a vehicle driving on the road outdoors and to provide hearing assistance for the hearing impaired. The method described here is not always effective in detecting the direction and distance of distant sound sources. This is because the system can be affected by environmental sounds such as wind noise when outdoors. We plan to overcome this problem by introducing environmental sound recognition using artificial intelligence. A wearable assistance system such as that adopted in this study will surely help hearing-impaired people go out safely. It is not yet clear whether a world in which all vehicles are electrically powered and run almost silently, with no need to detect running sounds, will be safe for people, including able-bodied people.  
This research received no external funding.  
Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
Not applicable.  
The author thanks [PERSON] and [PERSON] especially for developing the present system, for conducting several experiments, and for processing the data as graduate students.  
The authors declare no conflict of interest.
## 3 Proposal  
In this paper, we report on attempts to detect dict-DGA malware by identifying malicious domain names from massive DNS queries. We focus on queried domain names for the traditional DNSs, in which name resolution is an unencrypted interaction that occurs prior to data exchange between malware and C&C. Table 1 shows examples of domain names generated by dict-DGA malware. Because these domains depend on the C&C of the callback destination, each type of malware uses its own dictionaries and algorithms to generate them. For example, a comparison of the Gozi and Matsnu dictionaries reported in Refs. [37; 38] reveals that the dictionaries contain 975 and 1391 words, respectively, with only 240 words appearing in both dictionaries (Ursnif in literature [37] is an alias name for Gozi). Moreover, the word usage is expected to exhibit significant differences between malware-generated domain names and human-generated domain names. Based on these observations, we propose an approach for identifying malicious domain names by analyzing character strings at the word-level. The novelties of this approach include the following: (1) the use of general graph-theoretical techniques to represent relationships among words in domain names; and (2) the use of centrality to quantify the importance of each word in this graph. These indicators characterize the differences between benign and malicious domain names on the basis of word biases in their character strings. Finally,  
\begin{table}
\begin{tabular}{l l} \hline \hline Banjori & earnestnessbiophysicalohaz.com \\  & pbmnestnessbiophysicalohaz.com \\ \hline Gozi & williameseasily.com \\  & printingthatlabel.com \\ \hline Matsnu & shoulderracecognizeblue.com \\  & emergencyadyatpeslectddoubt.com \\ \hline Suppobox & windowtherefore.net \\  & severadifference.net \\ \hline \hline \end{tabular}
\end{table}
Table 1: Examples of domain names generated by dict-DGA malware.  
we apply ML techniques to the feature vectors derived from these indicators and thereby reduce the number of false positives in identification.  
Figure 2 shows an overview of the proposed approach, which has four steps: (1) Noise reduction, (2) word segmentation, (3) word graph construction, and (4) feature-vector-based identification. The following sections describe the training datasets and each of these steps in detail.
## 3 Discussion
### Lc-Esi-Qtof-Ms/Ms Analysis
#### 3.5.1 Putative Identification of Flavonoids
The putative identification of catechin and epicatechin was based on the ion [M + H]\({}^{+}\)\(m/z\) 291.0864 and molecular formula C\({}_{15}\)H\({}_{14}\)O\({}_{6}\). These compounds were considered isomers, corroborating with common fragmentations in the literature [65; 66], such as \(m/z\) 165.0548, \(m/z\) 139.0390, and \(m/z\) 123.0440. For the aerial parts extract of _B. caapi_, after decoction, considerable amounts of catechin and epicatechin were obtained, showing antimicrobial activity and action against pathogens [67]. Additionally, _B. caapi_ extracts investigated for important chemical markers, including epicatechin and procyanidin B2, detected consistently in various parts of the plant across different seasons, were associated with high antioxidant value [68]. Epicatechin is also an inhibitor of the enzyme monoamine oxidase (MAO-B), and when combined with _g_-carbolines, the potential synergistic effect may be valuable for neuroprotective activity. The presence of catechins in leaves and stems of various _Byrsonina_ species [58] has been associated with diverse activities including antileishmanial, antiulcer, antioxidant, antimicrobial, analgesic, anti-inflammatory, and others mentioned in studies. Recently, among the flavonoids identified in _M. glabra_ fruits, it was found that the quantification of epicatechin significantly increases in ripe fruits compared to green fruits. This increase is directly related to free radical scavenging activity [69]. Gallocatechin or epigallocatechin was also noted in this study, with the positive ion [M + H]\({}^{+}\)\(m/z\) 307.0809. The characteristic fragmentations observed in this study align with the literature [65], with major cleavages resulting in \(m/z\) 181.0500 and \(m/z\) 139.0390. Flavonoids, including gallocatechin, investigated in _M. emarginata_ leaves, stand out for their antioxidant and antifungal activities [58]. Another identified flavonoid has the positive ion [M + H]\({}^{+}\)\(m/z\) 585.1257 and formula C\({}_{28}\)H\({}_{24}\)O\({}_{14}\), with characteristic fragments of vitexin _O_-gallate. These fragments include: \(m/z\) 415.1028, \(m/z\) 313.0708, and \(m/z\) 153.0183, possibly resulting from the loss of the galloyl group, cleavage of the cross-ring hexose portion, and the galloyl fragment, respectively, as reported in the literature [70].
# A Blockchain-Based Auction Framework for Location-Aware Services
## 3 The Proposed Blockchain-Based Auction Framework  
The proposed framework consists of three components: the pre-auction, the auction, and the post-auction. The pre-auction component is for participants' registration and identity verification. To ensure the legitimacy of the auction process, participants must submit the requested information to identify themselves during the registration process. Once a participant registers with the system, they can act as a seller or buyer of services.  
Figure 1 illustrates the interaction between the auction functionalities. To initiate an auction, the buyer submits the requested service details to the blockchain. These details include the maximum price a participant is willing to pay. In addition, the buyer must submit the requested submission fee to start the auction. All submitted fees during an auction will be deposited into an administrative account for redistribution at a later stage. The buyer must also submit the required SI for the participating sellers (bidders) in the submitted auction request. In the proposed framework, each bidder and buyer has an SI, where the value of this index can be either (1) undecided, (2) positive, or (3) negative. A participant's SI is determined based on the feedback received about this participant in previous interactions (auctions). Participants who have not previously interacted with other participants are assigned an undecided SI. Based on the feedback received during past interactions, positive and negative service indices are assigned to participants. A participant's SI captures the overall expected quality of service provided by the participant. For instance, participants with a positive SI value are expected to provide a higher quality of service compared to participants with a negative SI value.  
Once the auction is initiated, the submitted request is propagated to the bidders that satisfy the requested SI criteria. Interested sellers submit their offers along with a participation fee to be deposited into the administrative account. Once the auction ends, the details of the cheapest (winning) bid will be submitted to the buyer, and the buyer's wallet will be charged based on the payment mechanism submitted as part of the auction request. This mechanism could be either full payment or installments. The money is deposited to the service provider (winning bidders) using the same charging mechanism. During the post-auction period, the participating bidders are rewarded by the distribution of the collected fees in the administrative account among them. Once a particular auction agreement period is over, the seller and the buyer's SI will be updated based on their interaction experience. Moreover, during the contract agreement period, any of the auction parties (seller or buyer) can raise a service violation claim. This claim is processed by the violation dispute component, which works in a decentralized manner to resolve any dispute between the auction parties.
## 4 Discussion
The studies on fall phenology in New England [13] also found that the maple and birch dominated northeastern highlands had higher sensitivity to drought than the corresponding southern coastal zone dominated by oak. Phenology changes in response to climate might also contribute indirectly to our observed pattern in vegetation greenness. For example, cooling winter helps trees to meet chilling requirements to break dormancy and the cooling winter but warming early spring is found to advance the growing season of deciduous-broadleaved forests in Northern China during 2001-2013 [14]. The onset of green-up advanced on average \(-2.4\) to \(-0.45\) days yr\({}^{-1}\) for the deciduous forests with significant changes in the start of growing season during 2001-2013, mostly distributed north of 48\({}^{\circ}\)N in Northern China [14]. In this study, we also found that both \(T_{\max}\) and \(T_{\min}\) showed a decreasing trend in nongrowing season in the deciduous forests which might help to advance the green-up (Figure 3). The lengthened growing season, in turn, might help partially explain the significant negative correlation between EVI and nongrowing season \(T_{\min}\) that we found in the north (Figure 5b), that is, cooling winter relates to advanced green-up and the lengthened growing season favors high greenness. The Earth System Modeling predicted that the high-latitude northern regions will continue the greening trend till 2100, which will enhance the regional C sequestration, strengthen regional hydrological dynamics, and induce localized warming via reduced albedo or cooling via transpiration [47]. This study made efforts to disentangle the climate contribution to greenness of temperate vegetations from land-use contribution which is essential in mechanistic understanding of the interactions of multiple drivers. These efforts are also important for our knowledge about greening, rational land-use planning, and natural-resource management for climate change mitigation. Our current study focuses on the vegetation greenness in response to climate without considering the changes in atmospheric CO\({}_{2}\) concentration or nitrogen deposition that also drive greenness [2]. Further advancement in remote sensing will likely provide the atmospheric CO\({}_{2}\) concentration and nitrogen deposition datasets with the spatial and temporal resolutions compatible to those in greenness or climate, thus leads to more comprehensive understanding of the drivers of vegetation greenness. In this study, we used the deciduous-broadleaved forest as an example to interpret that the differentiated relationship between greenness and climate might be attributed to the species composition. Further studies to link species composition to grassland greenness in response to climate based on ecophysiology will help elucidate this mechanism in various ecosystems.