esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis and Results
### MIM Waveguide with Only the Main Channel  
In the first place, an MIM waveguide with the main channel infiltrated by the LC is investigated. Thus, the FP effect on resonance frequencies of the MIM waveguide can be verified. In addition, different voltages are applied to change the dielectric properties of the LC and investigate their influence on the resonance.  
With different bias electric fields of the LC, the transmission spectra of the MIM waveguide are simulated and shown in Figure 4.  
In case the bias electric field of the LC equals zero, there are four resonant frequencies at 0.3553 THz, 0.7098 THz, 1.067 THz and 1.425 THz, corresponding to modes 1, 2, 3 and 4, respectively. While the bias electric field is increasing, the resonances of different modes are all shifted to lower frequencies. This is due to the increase of the effective refractive index \(n_{eff}\) seen by EM waves propagating along the MIM waveguide. Since Figure 3 shows that a larger bias electric field will lead to a larger \(k_{z}\), based on a well-known \(k_{z}\) = \(\omega/c\)\(n_{eff}\), the larger \(k_{z}\) of the MIM waveguide means the larger  
Figure 4: Transmission spectrum of the LC-infiltrated MIM waveguide.  
\(n_{eff}\) seen by the propagating EM waves. Consequently, under a larger bias electric field, the \(f_{FP,m}\) of the MIM waveguide governed by Equation (8) has a trend of shifting to lower frequencies. Such a phenomenon can be used for a tunable filter by controlling the bias electric field of the LC, if there is just one main channel in the MIM waveguide.  
In order to inspect the field distribution under different modes, their normalized \(H_{y}\) field strength in the \(xoz\) plane with zero-biased electric field of the LC is presented in Figure 5. Due to the intrinsic characteristic of FP resonance depicted in Equation (7), the number of periods of the field distribution is the same as the mode number \(m\). In fact, the peak field distribution of mode \(m\) under resonance is identical under different bias electric fields of the LC, which depends only on the geometry of the resonator. The demanded resonance of the mode \(m\) can be easily achieved by setting the MIM waveguide to operate under its \(m\)-th resonant frequency, which is given by Equation (8). From Figure 5, it can be seen that the maximum field of mode \(m\) appears at the \(z\)-coordinate of \(p_{m}\), which can be expressed by:  
\[p_{m}=\left(n+\frac{1}{2}\right)\frac{L}{m} \tag{9}\]  
where \(L/m\) stands for the period length of the mode \(m\), and \(n\) = 0, 1, 2,..., \(m\)-1 is the number of periods in front of the peak field.
# Intelligent Trajectory Prediction Algorithm for Reentry Glide Target Based on Intention Inference
## 3 Parameter Value Prediction Network
### Initial and Last State Modification Network \(\varphi_{l}(\cdot)\)  
When trajectory prediction is achieved by the integral-iteration method, the initial state of integration has a great influence on the prediction precision. As can been seen from Figure 1, The original data and observation data are brought into the initial and last state modification network, which is designed to modify the initial and last state of observation data, in order to generate a more accurate initial and last state. The LSTM network with a size of \([6,128,2]\), and the fully connected network with a size of \([128,6]\) are used for training. The observed normalized 6-dimensional state sequence is brought into the LSTM network with 128 hidden nodes at 2 layers to learn temporal relationship, and then it is integrated into the fully connected network for dimensionality reduction, which is used to obtain the state of modified initial and last state, \(S_{i}\) and \(S_{l}\), respectively. The structure is shown in Figure 2.
###### Abstract
The FLLF technique offers a localized approach that adapts to the image's intrinsic features, preserving image integrity while elevating its visual impact. The inherent adaptability of FLLF techniques to varying degrees of contrast enhancement makes it a compelling candidate for medical image enhancement applications. This research paper encompasses an in-depth examination of the application and outcomes of Fast Local Laplacian Filter techniques in the context of coronary angiography [12]. The FLLF algorithm is dissected and tailored to the unique requirements of angiography images, with special attention to achieving an optimal balance between improved contrast and the preservation of diagnostic information. This paper includes an overview of related works in contrast enhancement (Section 2); a detailed exposition of the FLLF methodology (Section 3); the experimental setup, dataset description, and the results and their implications (Section 4); and concluding remarks and avenues for future research (Section 5).
# Wind Speed Measurement via Visual Recognition of Wind-Induced Waving Light Stick Target
## 2 Theoretical Modeling
### Imaging Formulation
#### 2.1.3 Front View  
The theoretical model in front view is also given in centered and deviated imaging, where in centered imaging, the line between restrained stick end and optical center is perpendicular to the imaging plane. In deviated imaging, there is a deviation between the restrained stick end and the optical centerline, as well as the geometrical center of the imaging plane.  
In front view, the projection length is proportional to the stick length, as in Figure 7. Parameters are defined the same as in bottom view, all measured and calibrated before detection.  
Figure 7: Schematic of the front view model in centered imaging. (**a**) Schematic model; (**b**) geometry model.  
The yaw angle is calculated by the slopes of two lines at beginning and waved positions in Equation (24) as below.  
\[\alpha=\tan^{-1}\left(\frac{k_{B^{\prime}}-k_{A^{\prime}}}{1+k_{A^{\prime}}\cdot k _{B^{\prime}}}\right)=\tan^{-1}\left[\frac{(Y_{B^{\prime}}-Y_{O^{\prime}})\cdot( X_{A^{\prime}}-X_{O^{\prime}})-(Y_{A^{\prime}}-Y_{O^{\prime}})\cdot(X_{B^{ \prime}}-X_{O^{\prime}})}{(X_{A^{\prime}}-X_{O^{\prime}})\cdot(X_{B^{\prime}}- X_{O^{\prime}})+(Y_{A^{\prime}}-Y_{O^{\prime}})\cdot(Y_{B^{\prime}}-Y_{O^{\prime}})}\right] \tag{24}\]  
where \(k_{A^{\prime}}\) and \(k_{B^{\prime}}\) are the slope of line O\({}^{\prime}\)A\({}^{\prime}\) and O\({}^{\prime}\)B\({}^{\prime}\). (\(X_{O^{\prime}}\), \(Y_{O^{\prime}}\)), (\(X_{A^{\prime}}\), \(Y_{A^{\prime}}\)) and (\(X_{B^{\prime}}\), \(Y_{B^{\prime}}\)) are the imaging coordinates of restrained stick end O\({}^{\prime}\), and waving end A\({}^{\prime}\) and B\({}^{\prime}\), respectively.  
The critical yaw angle is \(\pm 90^{\circ}\) when the stick is blown to level limits:  
\[\alpha_{r}=-\alpha_{l}=\frac{\pi}{2} \tag{25}\]  
In deviated front view, the camera optical centerline deviates from the fixed stick end O by a magnitude \(S_{\rm X}\) and \(S_{\rm Y}\), respectively, in lateral and vertical directions. The intersection O\({}^{\prime}\) between the projection line and the imaging plane does not coincide with the imaging plane center O\({}^{\prime}\); however, the imaging plane and stick rotation plane are still parallel to each other, as in Figure 8.  
As seen from above, the detected imaging length \(\,|\)O\({}^{\prime}\)B\({}^{\prime}\,|\,\) remains the same because of the parallel planes at rotation and imaging. The imaging yaw angle is the same as the practical waving angle. Therefore, formulations are the same as in the centered front view model.
## 6 Related Work  
In the field of pricing mechanism design, there are two crucial focuses of research: query-based pricing and privacy-based pricing.  
Query-based pricing: [PERSON] et al. [16] observed flat-fee tariffs, usage-based prices, two-part tariffs, package pricing, free pricing, and freemium to be the main pricing strategies. [PERSON] et al. [17] believed that the existence of arbitrage opportunities, tuples being able to have the same value, per-query costs being irrelevant, and the lack of a feasible method for data providers to price tiers were four weaknesses of current pricing models. [PERSON] et al. [22] proposed a pricing model that was based on minimal provenance, which is a collection of tuples that contribute to a query. In [23], the concept of data view was proposed; this concept is equivalent to the version of the information product. [PERSON] et al. [7] proposed a pricing function and proved that it uniquely satisfies the arbitrage-free and discount-free conditions. The least expensive view set determines the price of the query. [PERSON] et al. [24] proposed a framework for arbitrage-free pricing of queries. [PERSON] et al. [25] studied the security implications of query pricing: how to set prices for data queries while protecting the seller's revenue (preventing arbitrage). [PERSON] et al. [26] presented a scalable pricing framework in which the data provider can choose a variety of pricing functions and control the price of the data by specifying the relation and attribute-level parameters; different parts of the data were assigned different values.  
Privacy-based pricing: [PERSON] et al. [21] proposed the first pricing framework ERATOfor the data markets providing common aggregate statistics over private correlated data. In [27], [PERSON] et al. discussed the privacy attitude, by which individuals were properly compensated and the private data of the data market could be sampled in an unbiased manner by the purchaser. In [28], it was recommended that private data be sold via auction, either completely hidden or completely public. [PERSON] et al. [29] studied a balanced privacy data pricing framework in which the purchaser purchases the query data with noise and the data owner is compensated accordingly according to the privacy loss. In [30], [PERSON] et al. indicated that privacy valuations are highly dependent on subtle scenarios and are inconsistent. [PERSON] et al. [31] proposed an effective data market security model, which can guarantee data authenticity and protect privacy. [PERSON] et al. [32] considered a practical personal data trading framework that strikes a balance between money and privacy.  
Our pricing model was also query-based, but unlike previous work, our pricing model was based on tuple granularity and minimal provenance. In addition, we proposed an exact algorithm and an approximate algorithm to calculate the price of the query, and verified it by instantiation on two real datasets. The original intention of our work is that all source tuples that contributed to the query result were reasonably priced.  
Figure 9: Memory consumption by different algorithms in complex query.
# Parameters Sensitivity Analysis of Position-Based Impedance Control for Bionic Legged Robots' [PERSON]
## 5 Dynamic Sensitivity Analysis
### Contrast of Dynamic Sensitivity Analysis in Each Working Condition  
For the convenience of contrast, the variation of system position response when each parameter increases 10% is calculated according to Equation (21). The curves of position variation with time is shown in Figure 17.  
Figure 16: The curves of dynamic sensitivity between two sensitivity methods. (**a**) First-order dynamic sensitivity of \(K_{D}\); (**b**) First-order dynamic sensitivity of \(C_{D}\); (**c**) First-order dynamic sensitivity of \(K_{p}\); (**d**) First-order dynamic sensitivity of \(K_{i}\).  
As it can be seen in Figure 17:  
1. The variation of each parameter affects impedance control position output. The position varies periodically with the sinusoidal disturbance force. Among the parameters, the desired stiffness \(K_{\text{D}}\) affects the output position much more than the others. The influence from integral gain \(K_{i}\) is the most irrelevant. Desired damping \(C_{D}\) and proportional gain \(K_{p}\) have similar influences on the output position. With the disturbance force in sinusoidal variation, \(C_{D}\) varies by following the curve of minus cosine, and \(K_{p}\) varies by following the curve of cosine.
2. The order of magnitudes of output position increases with the increase of sinusoidal disturbance force. However, there isn't an obvious relationship between the effects on output position and the frequency of the disturbance force.  
Using the method of dynamic sensitivity analysis, the qualitative effects on impedance control performance is analyzed. In order to analyze the effects on main system performance indexes and the varying patterns of parameter sensitivity under different working conditions, a quantificational analysis is needed.
## 3 System Implementation
### Low Noise Transconductance Amplifier (LNTA) Design  
The LNTA, shown in Figure 5, was designed based on the topology described in detail in [1] and is used in this work primarily because of its low noise and high linearity. High linearity and low noise is achieved using a transformer based complementary common-gate stage with current reuse between NMOS and PMOS input transistors working in class-AB. The three-coil transformer acts as a balun and provides a dual differential signal to the NMOS and PMOS input pairs. The cascode stages provide high output impedance which makes it suitable for proper operation with the current-mode mixer. The main difference with respect to [1] is that the gates of the input transistors are not connected to the primary of the transformer but are simply cross-coupled. A similar approach was also followed in [8]. This allows to eliminate the external balun that was required in [1]. Cross-coupling increases significantly the immunity to common mode signals (including second-order distortion terms) that appear directly at the input of the LNA since they are equally present at the gate and at the source of the input devices. As a result, composed second order nonlinearity, which is the dominant term in the CG LNA third-order distortion, vanishes, boosting the LNA IIP3. This allows to reduce the LNA current from 6 to 4 mA while achieving an IIP3 of around 14 dBm, as shown in Figure 6a.  
Figure 5: System architecture: Active self-interference (SI) canceler, Low Noise Transconductance Amplifier (LNTA), passive mixer, and transimpedance filter.  
For the same reason, any common-mode second-order distortion term injected by the canceler is also suppressed and does not degrade the receiver IIP3. The noise figure of the LNTA is also improved thanks to cross-coupling. Neglecting transformer losses, the noise factor of the cross-coupled common gate is \(\mathrm{NF_{CG}}=1+\frac{\gamma}{2}\)[29]. Shown in Figure 6b is the simulated NF of the LNA, including transformer losses. It has a NF of 1.6-2.3 dB in the range between 1.7 and 2.4 GHz.
# Molecular Dynamics Simulation Reveal the Structure-Activity Relationships of Kainoid Synthases
## 2 Results and Discussion
### Binding Energy Analysis of Kainoid Synthases
Catalytic promiscuity refers to the ability of enzymes to catalyze different chemical reaction processes, through different transition states, to produce different intermediates or products. Catalytic promiscuity has attracted more attention in the field of protein engineering, as it can be used to enhance natural catalytic activity or obtain new catalytic functions. In the process of biosynthesis of natural products, enzyme-catalyzed promiscuity is not uncommon and is closely related to the chemical diversity of natural products. In the biosynthesis of terpenoids, the substrates can be transformed into various products through the cyclization, rearrangement, and quenching cascade reactions involving carbocations. Therefore, the key to studying the catalytic mechanism of terpene natural product biosyntheise is to explore the root cause of catalytic promiscuity or catalytic specificity in different terpene natural product biosynthetic processes. In theoretical studies of terpenoid biosynthesis, the importance of \(\pi\)-interactions between aromatic residues (such as PHE/TYR/TRP) and carbocation ions has been mentioned many times [13; 14; 15; 16; 17; 18; 19]. The two main roles of aromatic residues in the catalysis of kainoid synthases are to restrict the orientation of substrates through steric hindrance brought about by large side chains, and to stabilize carbocation intermediates and transition states through \(\pi\)-cation interactions [20]. According to the analysis, PnDabC is catalytically specific compared to DsKabC and GfKabC, whereas GfKabC has been shown to be catalytically promiscuous in previous studies [8]. By analyzing the interaction between carbocation intermediates and key residues in active pockets, and the key chemical regulatory factors of terpenoid natural product biosynthesis during the reaction process, the sources of chemical diversity of terpenoid compounds were revealed, enabling a better understanding and use of the catalytic promiscuity and specificity of terpenoid natural product biosynthease. Kainoid synthases belong to Fe\({}^{2+}\) and alpha-ketoglutate-dependent dioxygenases, which are extremely versatile biocatalysts in nature. They play a key role in the biosynthesis of meroterpenoids and have been less studied, including structural characteristics, catalytic mechanisms, engineering development, and the discovery of new enzyme properties. At present, there are very few studies on meroterpenoids synthase, and those that do exist have mainly focused on the meroterpenoids synthase of terpenoids and polyketones. The current research on kainoid synthases only focuses on the catalytic mechanism or expression and purification, without analyzing the conformational dynamics and catalytic promiscuity [21; 22]. The structure-activity relationship of meroterpenoids synthases from marine algae has not been fully researched. The analysis of the mechanism of kainoid synthases is expected to further elucidate the biosynthesis process of kainoids.
# Marine Internet for Internetworking in Oceans: A Tutorial
## 2 Overview of Marine Internet
### Typical Applications
#### 2.2.5. Platforms for Collaboration and Optimization  
Many human activities take place in oceans, typically including fishing, shipping, tourism, and oil and gas production, along with a variety of marine environment observations (e.g., climate, tidal and hydrological data collection), detection, natural disaster warning (e.g., earthquake and tsunami) and scientific research (e.g., atmosphere, biology, physics, chemistry and geographies). At present, these activities are carried out almost separately without communication or collaboration between them. However, activities in oceans are costly, and sharing and cooperation can reduce costs. Marine Internet can be used to set up a platform for such sharing and collaboration since it can build the IoT in oceans as mentioned above.  
Now, data transmission to a remote site (e.g., a server on land) from oceans is usually through expensive satellite services. Much cheap mobile communication services are available only in near coast areas. When a vessel is moving in and out the two service areas, communication services should better changing accordingly. These services purchased by users individually cannot be shared, and, for prepaid services, the unused portion will be wasted after expiration. Marine Internet can be used to set up a unified platform to optimize network resource allocation in real-time according to users' location and application requirements. For example, the following system can be designed: (i) a company can purchase mobile and satellite services in batch; (ii) the user buys the services from this company ratherthan from the operators; and (iii) the company always allocates the best cost-effective service to the user in real-time according to its requirements and location.
# Utilization of Thermal-Activated Coal Gangue to Enhance the Properties of Sandy Soil Composites
## 1 Introduction
Commonly used modification methods include heat treatment, acid modification, inorganic salt modification, and organic modification to obtain better adsorption properties. On this basis, to reduce the influences of kaolinite on coal gangue and improve its exchange and adsorption properties regarding ions used to improve soil quality, this study investigates the modification effects of thermal-activated coal gangue (TACG) on the qualities of sandy soil. The physical properties of TACG-sand soil composites were evaluated, focusing on particle size distribution, water retention, the water evaporation process, a pore structure analysis, and element retention performance. By calcining the gangue at a certain temperature, the impurities attached to the pore structure of kaolinite are removed [15], which effectively increases the specific surface area and pore distribution of kaolinite and produces a porous organization on kaolinite. The temperature for the activation of coal gangue was selected as 600 \({}^{\circ}\)C and 850 \({}^{\circ}\)C to understand the effects of calcination history, while the untreated coal gangue was used as the reference. The related results can allow for a comprehensive understanding of the application of coal gangue in the modification and improvement of sandy soil. The gangue-improved soil prepared on this basis showed improvements in water-holding capacity and adsorption capacity of nutrient ions, effectively reducing sandy soil defects. This has long-term significance regarding agricultural applications.
## 4 Experiment and Analysis
### Analysis of Results
#### 4.4.3 Results of Ablation Experiments
Panels (e) and (f) illustrate that the SISGAN model, which incorporates the environmental information module, provides superior trajectory data for obstacle avoidance compared to the SIGAN model does not emphasize environmental context, particularly in situations where obstacles need to be navigated or when pedestrians are walking alongside them. We believe that the ablation experiments validate the effectiveness of both the social interaction module and the environmental information module in this study. However, due to the independence of individual pedestrians, even though the model can predict the final locations of pedestrians more accurately, there is still a need for the model to better understand pedestrians' walking intentions. This understanding would enhance the accuracy of trajectory predictions.