esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Force Simulation  
The results of this study demonstrated that the functional rehabilitation brace with resistance significantly reduced ACL forces in martial arts athletes' post-reconstruction, with the experimental group (EG) showing markedly decreased ACL loading during walking at T4 compared to the controls (CG). This protective effect was particularly pronounced in athletes with high-grade ACL injuries [36], where the progressive resistance provided optimal rehabilitation intensity to restore joint stability without compromising graft healing. The skeletal muscle model analysis confirmed the brace's effectiveness in reducing ACL forces under controlled conditions, with greater force reduction observed in cases of more severe initial ligament damage [37], suggesting that the resistance brace's load-modulating capacity is particularly beneficial for high-intensity rehabilitation protocols. These improvements likely stem from enhanced joint coordination and stability, as the resistance brace promotes more controlled movement patterns while allowing graded return to functional activity-a critical advantage over traditional braces that often fail to provide this intensity progression, especially for athletes requiring sport-specific rehabilitation [38]. Our findings align with previous research showing that functional braces reduce ACL loading [39], but importantly extend these observations by demonstrating that resistance bracing offers superior protection during dynamic movements, particularly during the critical return-to-sport phase when rehabilitation intensity must be carefully matched to tissue healing status [40]. While conventional braces primarily limit excessive motion [41], our resistance brace actively enhances neuromuscular control, making it especially valuable for patients with greater baseline impairment who require both protection and progressive challenge during rehabilitation. This study provides compelling evidence that resistance bracing represents an important advancement in ACL rehabilitation, particularly for high-demand athletes, where precise control of rehabilitation intensity is crucial for successful return to pre-injury performance levels.  
Research recommendation: Future research could further explore how to optimize the skeletal muscle model to improve the simulation accuracy of ACL forces, especially under more complex movement patterns and a wider range of individual difference conditions.
# Performance Comparison of H.264 and H.265 Encoders in a 4K FPV Drone Piloting System
## 4 Experimental Results
### GOP Size, QP, and Target Bitrate Analysis  
One can notice high deviations between libx264 and libx265 at the highest and lowest bitrates. As previously mentioned, QP and target bitrate are strongly correlated, and oftentimes, QP restriction causes the target bitrate to become completely irrelevant. In other words, QP restriction sometimes causes codecs to deliver videos with much higher or lower bitrates than targeted. Both codecs were tested using the same set of parameters and, unlike libx264, libx265 almost always managed to output videos with bitrates very close to the target.  
Even though there is a possibility of using a GOP size greater than 90, in the case of UAV video streaming, it is not advisable due to the possible errors in the transmission of video data over a network with lossy conditions. We noticed that the GOP size did not have a significant impact on the compression quality. For the same encoding configurations (i.e., same codec, min and max QP, and target bitrate), the VMAF scores varied less than \(\pm 1.5\%\) for 90, 120, and 150 GOP sizes. Other quality measures showed similar results, and the encoding time was practically not affected.  
Regarding the classification of the sequences and the bitrates acquired with the same quality of the video, there were noticeable differences between classes A, B, C, and D. In Figure 10, considering the VMAF scores for all four classes and the two encoding algorithms, classes D and especially C had much higher bitrates when aiming at the same quality of the video. The same increase in bitrate can be seen regardless of the target video quality. This demonstrates that the increase in spatial complexity directly causes an increase in the output bitrate of the video sequence.
# High-Dimensional Data Analysis Using Parameter Free Algorithm Data Point Positioning Analysis
## 6 Results and Discussion
### Proposed Data Point Positioning Analysis  
This experiment is conducted on two publicly available datasets to validate the proposed model. The performance of the proposed model is illustrated in Figures 1 and 2. To visualize the outcomes of the proposed model, the t-SNE Python library is used. Both figures show the number of clusters achieved with the proposed method, with different colors representing different clusters. Figure 1 displays the experimental outcomes of the proposed model with dataset 1, while Figure 2 displays the experimental outcomes with dataset 2. The proposed method successfully identifies a total of 8 clusters for dataset 1 and 50 clusters for dataset 2, demonstrating its ability to handle higher-dimensional datasets, handle noisy data, and identify the correct number of clusters. Moreover, we calculate the silhouette coefficient for performance evaluation. With the proposed approach, a maximum coefficient value of 0.288 is achieved for dataset 1, while a coefficient value of 0.832 is achieved for dataset 2. We also compare the outcome of the proposed method with the popular clustering methods. From Figure 3 and Table 3, it is evident that our proposed method outperforms the other clustering algorithms.  
Furthermore, the proposed method does not require manual parameter selection, as it automatically determines the optimal cluster from the dataset without analyzing different parameter combinations. To compare and validate the performance of the proposed algorithm, this study also implements four popular algorithms with the higher-dimensional dataset. The experimental outcomes of these algorithms are presented below.  
Figure 1: Data point positioning analysis clustering result for dataset 1.  
Figure 2: Data point positioning analysis clustering result for dataset 2.
## 1 Introduction  
The subjective perception of sound originates from three auditory attributes: loudness, pitch, and timbre [1]. In recent years, researchers have established relatively mature evaluation models for loudness and pitch [2, 3], but a quantitative calculation and assessment of timbre is far more complicated. Studies have shown that timbre is a critical acoustic cue for conveying musical emotion. It also provides an important basis for human recognition and classification of music, voice, and ambient sounds [4]. Therefore, the quantitative analysis of timbre and the establishment of a parameterized model are of significant interest in the fields of audio-visual information processing, music retrieval, and emotion recognition. The subjective nature of timbre complicates the evaluation process, which typically relies on subjective evaluations, signal processing, and statistical analysis. The American National Standards Institute (ANSI) defines timbre as an attribute of auditory sensation in terms of which a listener can judge that two sounds similarly presented and having the same loudness and pitch are dissimilar [5], making it an important factor for distinguishing musical tones [6]. Timbre evaluation terms (i.e., timbre adjectives) are an important metric for describing timbre perception features. As such, a comprehensive and representative terminology system is critical for ensuring the reliability of experimental auditory perception data. Conventionally, timbre evaluation research has focused on the fields of music and language sound quality, traffic road noise control, automobile or aircraft engine noise evaluation, audio equipment sound quality design, and soundscape evaluation. Among these, research in English-speaking countries is relatively mature, as shown in Table 1. However, differences in nationality, cultural background, customs, language, and environment inevitably affect the cognition of timbre evaluation terms [7; 8; 9; 10; 11]. In addition, Chinese instruments differ significantly from Western instruments in terms of their structure, production material, and sound production mechanisms. The timbre of Chinese instruments is also more diverse than that of Western instruments and existing English timbre evaluation terms may not be sufficient for describing these nuances. As such, the construction of musical timbre evaluation terms is of great significance to the study of Chinese instruments.
# A Trusted Lightweight Communication Strategy for Flying Named Data Networking
## 3 Trust Establishment and Trust-Based Monitor Selection
### GroundStation-to-UAV Trust  
On every interaction with the ground station, UAVs send their neighbor trust evaluation list to the ground station. This information allows the ground station to have a quasi-global view about UAVs behavior within their respective region. Equation (6) shows how a ground station computes its evaluation (\(GSE\)) of a UAV \(j\) using the other UAVs' trust evaluation:  
\[GSE(GS,j)=\big{[}\prod_{n}Trust(i,j)\big{]}^{\frac{1}{n}} \tag{6}\]  
where \(n\) is the number of neighbors UAVs of \(i\) having a trust value regarding the UAV \(j\).  
In addition to the evaluation computed by GS, the received reports can also be used to detect and blacklist attackers within the network.  
\[\begin{split} GSBlacklist\leftarrow\forall j,\end{split} \tag{7}\]  
In Equation (7), \(DetectTH\) is the detection threshold, which is compared to the ratio between the number of UAVs considering the UAV \(j\) as dishonest and the total number of reporting UAVs.
# Empirical Study of Fully Homomorphic Encryption Using Microsoft SEAL
## 3 Methodology  
The research methodology and tools utilized for conducting experiments in this study are thoroughly described next. Throughout this study, we focus on the practical application of homomorphic encryption using the Microsoft SEAL library to carry out the experiments. The explanation includes system requirements, software, and tools.
# Review of Convective Heat Transfer Modelling in CFD Simulations of Fire-Driven Flows
## 3 Main Modelling Approaches
### Experimental Correlations
#### 3.1.3 Characteristic Length \(L_{c}\)  
The characteristic length, \(L_{c}\), over which convective heat transfer occurs depends on the type of scenario considered (i.e., natural or forced convection). An overview regarding the appropriate choice of \(L_{c}\) is provided in Figure 1.  
* Forced convection: For flow parallel to a plate: \(L_{c}=L\) where \(L\) is the distance of the plate over which the fluid has to travel (i.e., in the direction of the flow). For flow around spheres: \(L_{c}=D\) where \(D\) is the sphere diameter.
* Natural convection: For vertical plates: \(L_{c}=L\) where \(L\) is the height of the plate. For horizontal plates: \(L_{c}=A_{s}/p\) where \(A_{s}\) and \(p\) are the surface area and perimeter of the plate, respectively. For spheres: \(L_{c}=D\) where \(D\) is the sphere diameter.
# Low-Complexity Online Calibration for Large-Scale Multi-Beam Antennas
## 3 Low-Complexity Online Calibration Method
### Online Calibration Method Based on Decorrelation Algorithm
Then the above equation can be rewritten as  
\[\widehat{\mathbf{\omega}}=\mathbf{\omega}+\mathbf{x}+\frac{1}{\beta}\mathbf{u}^{\mathsf{T}}\bm {u}\mathbf{x}-\frac{1}{\beta}\mathbf{u}^{\mathsf{T}}x_{0}. \tag{14}\]  
Figure 4: Structure of calibration receiver based on decorrelation. Substituting \(x_{0}=\mathbf{d}^{\rm T}\mathbf{n}\) into the above equation, the purpose of calibration is to obtain \(K\) estimated elements of \(\mathbf{\omega}\) as follows:  
\[\widehat{\mathbf{\omega}}=\mathbf{\omega}+\mathbf{x}+\frac{1}{\beta}\mathbf{u}^{\rm T}\mathbf{u}\mathbf{ x}-\frac{1}{\beta}\mathbf{u}^{\rm T}(\mathbf{d}^{\rm T}\mathbf{n}). \tag{15}\]  
The estimated amplitude and phase of the proposed method can be expressed as  
\[\widehat{a}_{k} =\left|\omega_{k}+x_{k}+\frac{1}{\beta}\Bigg{(}u_{k}^{2}x_{k}+ \sum_{i=1,i\
eq k}^{K}u_{i}u_{k}x_{i}-u_{k}x_{0}\Bigg{)}\right|,\quad k=1,2, \cdots,K \tag{16}\] \[\widehat{\varphi}_{k} =\arg\!\left[\omega_{k}+x_{k}+\frac{1}{\beta}\left(u_{k}^{2}x_{k }+\sum_{i=1,i\
eq k}^{K}u_{i}u_{k}x_{i}-u_{k}x_{0}\right)\right]\!,\quad k=1,2,\cdots,K \tag{17}\]  
where \(x_{k}=\mathbf{c}_{k}^{\rm T}\mathbf{n}\) follows complex Gaussian distribution \(\mathcal{CN}(0,\sigma^{2})\) and \(u_{k}=\mathbf{d}^{\rm T}\mathbf{c}_{k}\) represents the inner product of the normalized demodulation symbol (\(\mathbf{d}\)) with the normalized calibration code (\(\mathbf{c}_{k}\) ). According to the central limit theorem, we can obtain that \(u_{k}\sim\mathcal{N}(0,1/L)\). Comparing (16) with (5), or (17) with (6), the strong interference related to \(\omega_{0}\) has been eliminated. Meanwhile, the noise item becomes more complicated.
## 3 Results and Discussion
### ATR-FTIR Analysis  
The FTIR spectra of the raw material and the obtained prepared films are illustrated in Figure 1. It was obvious that the spectra of the typical signals of the prepared films were similar. It was reasonable that the main hard segment content and groups of the polyurethanes were almost the same. The main absorption bands were as follows: 3320 cm\({}^{-1}\) (N-H stretching); 2870 cm\({}^{-1}\) (CH\({}_{2}\) stretching) (polycarbonate diol); 2939 cm\({}^{-1}\) (CH\({}_{2}\) asymmetrical stretching) (polycarbonate diol); 790 cm\({}^{-1}\) (C-O-C asymmetrical stretching); and 1242 cm\({}^{-1}\) (O=C-O asymmetric bending). The following bands prove that the structure of the polycarbonate polyurethane polymer was successfully synthesized. The 1731 cm\({}^{-1}\) band of the polyurethane film was broader than PCDL where splitting into 1737 cm\({}^{-1}\) and 1680 cm\({}^{-1}\) bands occurred, and carbonyl stretching vibration of the carbamic acid ester at 1537 cm\({}^{-1}\) (C-N-H in-plane bending). The presence of non-bonded groups could be attributed to the high structural symmetry of the chain extender, and could inhibit the ordering by existing in the hard domain formation. Additionally, none of the curves exhibited a typical absorption peak at about 2270 cm\({}^{-1}\), indicating that all of the -NCO groups were removed during the Soxhlet extraction.  
Generally speaking, some hydrogen bonds are also involved in polyurethanes, taking the amide and the carbonyl groups as the donor and acceptor, respectively. Hydrogen-bonded N-H stretching vibrations in the urethane unit region is located at 3320 cm\({}^{-1}\) for all the polyurethane samples as shown in Figure 2, where PCU-30% is higher than those for the other samples, showing the most strengthened hydrogen bonding within relatively better feed ratios of the hard segments. This result suggested that PCU-30% could exhibit the highest degree of microphase separation between the hard and soft segments [32]. Therefore, from the discussion of the FTIR data, we can easily obtain the conclusion that we have successfully prepared the polymer membranes as shown in Figure 1.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Samples** & \(M\pi\times 10^{4}\)**(Da)** & \(M\pi\times 10^{4}\)**(Da)** & **PDI (_Mw/Mn_)** \\ \hline PCU-20\% & 2.66 & 4.47 & 1.68 \\ PCU-25\% & 1.37 & 2.08 & 1.52 \\ PCU-30\% & 0.92 & 1.14 & 1.23 \\ PCU-35\% & 0.88 & 1.06 & 1.20 \\ \hline \end{tabular}
\end{table}
Table 1: Molecular weights and molecular weight distributions of the synthesized polycarbonate urethanes (PCUs) used in this work. Here, polyurethanes are denoted as PCU-x%, where x is the hard segment weight fraction.  
Figure 2: The FTIR spectra of poly(1,6-hexanediol)carbonate microdiols (PCDL) and the prepared polyurethane films.
###### Abstract  
Molecular hydrogen (H\({}_{2}\)) is crucial for agricultural microbial systems. However, the mechanisms underlying its influence on crop yields is yet to be fully elucidated. This study observed that H\({}_{2}\)-based irrigation significantly increased strawberry (_Fragaria \(\times\) anamassa_ Duch.) yield with/without nutrient fertilization. The reduction in soil available nitrogen (N), phosphorus (P), potassium (K), and organic matter was consistent with the increased expression levels of N/P/K-absorption-related genes in root tissues at the fruiting stage. Metagenomics profiling showed the alterations in rhizosphere microbial community composition achieved by H\({}_{2}\), particularly under the conditions without fertilizers. These included the enrichment of plant-growth-promoting rhizobacteria, such as _Burkholeria, Pseudomonas_, and _Cuprizvidus_ genera. Rhizobacteria with the capability to oxidize H\({}_{2}\) (group 2a [NiFe] hydrogenase) were also enriched. Consistently, genes related to soil carbon (C) fixation (i.e., _rbcl._, _porD, frdAB_, etc.), dissimilar nitrate reduction (i.e., _npAB_ and _nrfAH_), and P solubilization, mineralization, and transportation (i.e., _prx-gppA_, _appA_, and _uspABCE_) exhibited higher abundance. Contrary tendencies were observed in the soil C degradation and N denitrification genes. Together, these results clearly indicate that microbe-mediated soil C, N, and P cycles might be functionally altered by H\({}_{2}\), thus increasing plant nutrient uptake capacity and horticultural crop yield.  
Keywords:strawberry; yield; rhizosphere microbiome; microbial functional gene; plant nutrient uptake +
Footnote †: journal: plants
# Coordination of Multiple Autonomous Agents Using Naturally Generated Languages in Task Planning
## 5 Experiments and Results
### Languages Comparison  
To measure the performance of the languages constructed in this work, we compare our languages with languages generated by the method in [24], denoted as CGL (complete global language), and the method in [25], denoted as MOL (minimal optimal language), in terms of message lengths, specified plans, and computation time. Figure 4 is the test example in which there are 10 task points, marked as blue stars, which need to be continually visited by two agents.  
For this environment, there are a total of 8100 tasks (a task is specified by a pair of agents' states <initial, goal>, \(8100=10*9*10*9\)), of which 350 tasks introduce RC. We obtain that the number of language words generated by our approach, CGL, and MOL are 6, 7, and 2, respectively. For the sake of contrast, we conduct 100 RC tasks at random and record the relevant data. Figures 5-7 separately show the length of the communicative messages, the number of specified optimal plans, and the time cost of sentence generation, respectively. The red, purple, and green curves represent the results achieved by our method, CGL, and MOL, respectively. In Figure 5, the blue curve denotes the number of states in the plans. As we can see, coordination messages generated by our algorithm are quietly shorter than those of other communication methods, which greatly reduces the burden of communication of agents. Figure 6 shows that our sentences could specify many available plans for agents to follow, which gives them more flexibility to execute tasks. Although the constructed language in this work is not minimal, our approach has nearly comparable benefits to those of MOL in this respect. Furthermore, as can be seen in Figure 7, the computation costs of language planning using our method are much less than the costs of MOL. As with CGL, the complexity of the SGP in our method is almost equivalent to the task planning problem. In general, the results show that our languages offer considerable advantages compared to CGL and MOL in these
# Modeling and Performance Analysis of mmWave and WiFi-Based Vehicle Communications
## 3 Performance Analysis
### Average Throughput  
The average throughput (AT) is a measure reflecting the channel transmission performance in terms of the number of correctly received bits per second [36]. It is directly proportional to the average ergodic capacity, which indicates the number of properly received bits per second per hertz.
## 1 Introduction
For the frequency stability studies, an appropriate transient model must be proposed which is compatible with power system simulation tools. In this paper, a detailed model, considering dynamics of WTGs, has been extracted and applied in frequency stability studies. In order to allow different modes of WTGs' operation in power system with large portion of wind power penetration, frequency control capabilities must be added to individual wind turbines [16]. Contribution of WTGs in system frequency control can be performed through different control strategies. After modeling of power system components, in the second part, control strategies must be studied carefully and a proper strategy must be introduced. One method is inertial control. Inertial response can be provided through exploiting wind turbines below MPPT curve, known as de-loading operation. In this strategy, the kinetic energy stored in the rotor is used for frequency control [17; 18]. Installing wind energy storage systems to WFs is an effective way to provide system frequency response [19]. Speed droop response control is another method of system frequency control, but it requires the wind turbine to preserve generating margin. Therefore, it inevitably distances the operating point from best economic conditions because of high installation cost of storage systems [20]. In medium size to large size WTGs, pitch angle control (PAC) is a usual method for output power control in above rated wind velocities, and hence, frequency control can be achieved [7]. In this paper, a new control strategy based on improved PAC with emotional learning based intelligent controller has been proposed for individual WTGs' output power control. The remainder of the paper is organized as follows. In Section 2, the proposed transient model of DFIG, suitable for frequency stability studies, is extracted and dynamic equations have been applied in the studies. In Section 3 the proposed strategy to control dynamic behavior of WTGs in a power system, when participating in frequency regulation, is explained completely. The proposed strategy is based on coordinated application of emotional learning based intelligent controller in the WTG pitch angle controller and FLC in WF control unit. Geographical dispersion of wind velocity is modeled in Section 4 to get a close estimation of wind velocities dispersed in WF. In Section 5, the contribution of wind power in frequency control is investigated in a test system which is composed of two zones, each zone consisting of a conventional unit with an interconnected WF supplying a local load demand and connected to the other zone via a tie line. All of the results are compared and mentioned in Section 6. At last, the conclusion has been extracted.
## 3 Fuzzy-Logic Topology Control (FTC)
### WSNs Topology Control Using Fuzzy-Logic  
In general, there are two ways to design the fuzzy-logic controller. The most commonly used approach is to design the membership functions and the if-then rules on the basis of understanding the system from domain experts. However, due to the complexity and dynamic of the system (such as WSNs), the design of the membership functions and if-then rules might not be easy. Without any (or with incomplete) knowledge about a system, tuning the parameters often takes very long time, e.g., the shape of the membership functions. Another way to design fuzzy controllers is to use the training data set obtained from extensive experiments or mathematical description if it exists. By means of applying some learning algorithms, the fuzzy controller can be learnt from training data set. In this paper, our FTC leverages the second approach.