esa-sceva/satcom-chunk-collection huggingface dataset:
# Jet Noise in Airframe Integration and Shielding
## 4 Numerical Simulation of the Shielding Effect
### Numerical Approach
The DES formulation of the \(k-\omega\)_SST_[81; 82] model is achieved such that in the LES regions of the grid, the solution would reduce to a Smagorinsky-like sub-grid model, as described by [PERSON] [82], such that the eddy viscosity is proportional to the magnitude of the strain tensor, and to the square of the grid spacing. Therefore, the only term of the RANS model that is different in the DES mode is the dissipative term of the \(k\) transport equation. This equation in the DES model is defined as:  
\[\frac{\partial(\rho k)}{\partial t}+\frac{\partial(\rho u_{i}k)}{\partial x_{ i}}=\overline{P}_{k}-\beta^{*}\rho k\omega\widetilde{d}+\frac{\partial}{ \partial x_{i}}\bigg{[}(\mu+\sigma_{k}\mu_{t})+\frac{\partial k}{\partial x_{ i}}\bigg{]} \tag{3}\]  
where the length scale, \(\widetilde{d}\), is defined as:  
\[\widetilde{d}=F_{DES}=\text{max}\bigg{(}\frac{L_{t}}{C_{DES}\Delta},1\bigg{)} \tag{4}\]where \(\Delta\) is the local grid spacing, which for a three-dimensional grid is defined as \(\Delta=\max(\Delta x,\Delta y,\Delta z)\) and \(C_{DES}=0.61\). When the local grid is fine enough in all directions, compared to the turbulent length scale, the \(\overline{d}\) term grows larger than 1. This will in turn reduce \(k\), hence allowing the solution to resolve turbulence, reducing the amount of modeled turbulent shear stress and allowing the region to be treated as LES. _FWH acoustics integral surface_: Far-field acoustics is obtained using the Ffowcs Williams-Hawkings surfaces [51] integral technique implemented in OpenFOAM using the dynamic library mentioned in [83]. The FW-H equation is an inhomogeneous wave equation derived by manipulating the continuity equation and the Navier-Stokes equations. If one assumes that the control surface contains all acoustic sources, the volume integrals outside this surface can be dropped.
## 3 Results and Discussion  
### DES Synthesis and Examination of HBD: HBA Molar Ratio (\(R_{\mathrm{mol}}^{\mathrm{D/A}}\))  
The use of nicotinamide as HBA in L-lactic acid-based DES has been recently reported for the first time [24]; however, the use of glycerol as HBD in combination with nicotinamide as HBA, to the best of the authors' knowledge, is heretofore unreported. When designing a DES, the role of R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) in the polyphenol extraction performance is salient [19; 25], and therefore, an initial screening of DES with varying R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) was deemed essential in identifying the highest-performing combination.  
Attempts to combine glycerol and nicotinamide at R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) up to 4 were not met with success, since the DES synthesized tended to develop crystals within 24 h, at room temperature (23 \(\pm\) 2 \({}^{\circ}\)C). Combination at R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) = 5 produced a DES, which remained stable for several weeks, and based on this finding, a series of DES with R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) ranging from 5 to 13 were synthesized and tested for their effectiveness in extracting polyphenols from _M. oleifera_. All the DES assayed were used as 70% (_w/v_) aqueous mixtures and the outcome of this screening is given in Figure 1. The DES with R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) = 5 exhibited statistically higher extraction efficiency (\(p\) < 0.05) compared with all other DES and also 60% (_v/v_) aqueous ethanol and 60% (_v/v_) aqueous methanol. Water, on the other hand, was the least efficient solvent (\(p\) < 0.05). On this ground, the DES with R\({}_{\mathrm{mol}}^{\mathrm{D/A}}\) = 5, assigned as GL-Nic (5:1), was chosen for further examination.
## 5 Discussion
As soon as the latest scene of remote sensing data arrives, the ready classifier can be directly applied to it. In addition, implementing the process in other programming languages and utilising high-performance processors could also help promote efficiency. Above all, remote sensing data with middle-high spatial and temporal resolution are recommended in the proposed method, as the spatiotemporal contextual information in the image is important for the method. If the spatial or the temporal resolution is rather low in the data, the correlation between neighbouring pixels could be unremarkable.
# A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation
## 3 Experimentation with the Fuzzy Systems in Harmony Search for Benchmark Mathematical Functions  
For all the experiments used, the parameters are presented in Table 1. For all the functions, the global minimum is zero. The proposed method used six mathematical functions--some simple and some more complicated--in order to test the algorithm and measure its effectiveness. In this case, ten dimensions in each problem were used, as the literature suggests this number for the first tests. We then compare it with the bat algorithm method which also uses ten dimensions. Once you validate the performance of the method it will apply to problems of control.  
Table 1 shows the parameters of the methods to be considered in the comparison; in this case, the comparison of the proposed method (FHS) and the simple HS algorithm.  
Also for the comparison of the proposed method with respect to the HS without parameter adaptation, parameters that give the global minimum of each of the six benchmark mathematical functions have to be found. In Figure 14, there is a sample of the functions that are used [28; 29].  
As indicated in Figure 14, functions of ten dimensions for the experiments were considered. Once the fuzzy systems that dynamically adjust the parameters of HS are defined, and the problem to which this is applied is defined (benchmark mathematical functions), the proposal is as shown in Figure 1, where it can be observed that the harmony memory accepting (_HMR_) and pitch adjustment (_PArate_) parameters are adjusted by a fuzzy system, and in turn this \"fuzzy HS\" searches for the optimal parameters for the benchmark mathematical functions [30].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **Simple HS** & **FHS1** & **FHS2** & **FHS3** \\ \hline Harmonies & 4 to 40 & 4 to 40 & 4 to 40 & 4 to 40 \\ Iterations & 1000 & 1000 & 1000 & 1000 \\ _HMR_ & 0.95 & Dynamic & 0.95 & Dynamic \\ _PArate_ & 0.7 & 0.7 & Dynamic & Dynamic \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters for each of the methods.  
Figure 12: Rules for Fuzzy System 3 to Increase (FHS3).  
Figure 13: Rules for Fuzzy System 3 to Decrease (FHS3).
## 4 Conclusions  
This paper proposes a super-resolution reconstruction network (PCCSTSR) based on the Parallel Connection of Convolution and Swin Transformer Block (PCCSTB) to model both local and global features of images. Specifically, by combining the channel feature enhancement convolution with the Swin-Transformer parallel structure, the network extracts, enhances, and fuses both local and global information. Additionally, a fusion module is designed to merge the global and local features extracted by CNNs. These experiments demonstrate that the proposed network achieves a good balance between super-resolution performance and network complexity, achieving competitive results in the lightweight SR field. For example, under the same hardware conditions, in the \(\times\)4 super-resolution experiment on the Urban100 dataset, the network's inference speed reaches 55 frames per second, more than seven times faster than the excellent network SwinIR. Additionally, regarding the proposed network's PSNR, compared to SwinIR, the parallel structure of PCCSTB effectively combines local and global features, resulting in a 0.29 dB PSNR improvement on Set5 at the \(\times\)4 scale, indicating  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Algorithm**} & \multirow{2}{*}{
\begin{tabular}{c} **Sampling** \\ **Scale** \\ \end{tabular} } & \multicolumn{2}{c}{**Urban100**} & \multicolumn{1}{c}{**Manga109**} \\ \cline{3-4}  & & **PSNR** & **PSNR** \\ \hline PCCSTSR-SFEB & & 26.52 & 31.24 \\ PCCSTSR-FEB & & 26.57 & 31.28 \\ PCCSTSR-ESA & \(\times\)4 & 26.55 & 31.20 \\ PCCSTSR-FB & & 26.57 & 31.26 \\
**PCCSTSR** & & **26.63** & **31.32** \\ \hline \hline \end{tabular}
\end{table}
Table 4: Average running time on the Urban100 dataset (\(\times\)4).  
that the network can efficiently perform high-resolution image reconstruction with a relatively small parameter size (\(5.85\times 10^{5}\)).  
In order to further achieve the smallest possible computational complexity, it is expected that the next step of research will be to study a lighter network based on this scheme based on ablation experiments, frame generation time, network parameter quantity, etc.  
Conceptualization, [PERSON]; methodology, [PERSON]; software, [PERSON]; validation, [PERSON] and [PERSON]; data curation, [PERSON]; writing--original draft preparation, [PERSON]; writing--review and editing, [PERSON]; supervision, [PERSON] All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The data presented in this study are openly available in [Dlv2k] [[[https://www.kaggle.com/datasets/joe1995/div2k-dataset](https://www.kaggle.com/datasets/joe1995/div2k-dataset)]([https://www.kaggle.com/datasets/joe1995/div2k-dataset](https://www.kaggle.com/datasets/joe1995/div2k-dataset)) (accessed on 19 December 2024)].  
The authors declare no conflicts of interest.
# Fine-Grained High-Utility Dynamic Fingerprinting Extraction for Network Traffic Analysis
###### Abstract
Therefore, using the \(N\)-gram model in natural language processing can more accurately describe the process of communication between the two ends, especially taking the message type as the element of the model. The characteristics of network behavior analysis in recent years are from coarse grained to fine grained. Coarse grained and fine grained are relative concepts. They are distinguished according to the level of detail in the division of project modules, said to be fine-grained. Relative to fine grained, the larger each module (or sub-module) is, the coarser the work it is responsible for, which is called coarse grained. Some methods can directly analyze raw network traffic but can only extract coarse-grained features, not fine-grained features of a single mobile terminal. Moreover, anomaly detection can only rely on manual analysis methods of static datasets to obtain features, which is not suitable for dynamic and real network environments with huge data traffic. According to the existing problems, this paper proposes the fine-grained high-utility dynamic fingerprinting (Huf) algorithm to focus on solving the above problems. Given the existing problems, this paper proposes an approach to the fine-grained high-utility dynamic application fingerprinting extraction to solve them. In this paper, the original network traffic is taken as the analysis target, and the characteristics of the original network traffic are extracted by analyzing the communication session--a fingerprint is applied to solve the problem that the original network traffic cannot be directly dealt with by anomaly detection, and the fine-grained anomaly detection can be realized by a fingerprint. Then, the frequent item set mining algorithm is improved to realize the automatic extraction of network features and solve the problem that feature extraction depends on manual analysis. Extracting the characteristics of network traffic has always been the focus of network behavior analysis. Modeling a large number of independent data packets is the premise of traffic processing. The Huf algorithm proposed in this paper can realize dynamic application fingerprint extraction, solve the problem that anomaly detection cannot process the original network dataset and solve two problems that rely on manual feature extraction, and implement dynamic data stream processing. This paper consists of six sections: Section 1 is an introduction; Section 2 is a description of the problem, including the proposal and innovation of the problem and the process of the proposed method; Section 3 is the preprocessing of network traffic in the new method proposed in this paper; Section 4 is the efficient and dynamic fingerprint extraction method proposed in this paper; Section 5 is the experimental analysis; Section 6 is the conclusion of this paper.
# Grammar-Supervised End-to-End Speech Recognition with Part-of-Speech Tagging and Dependency Parsing
## 3 Integration of Grammar Knowledge
### The Auxiliary Text-To-Grammar Downstream Task  
Although the CTC branch makes the reinforcement of word embedding with grammar embedding possible, the grammar knowledge extracted from the CTC branch and the final hypothesis of the encoder-decoder branch support and interfere with each other. This situation may increase the risk of low robustness in complex scenes. An auxiliary text-to-grammar downstream task can be added to the ASR system based on the performance evaluation with different types of grammatical knowledge to constrain the final hypothesis directly. Under this circumstance, joint training patterns of speech recognition accuracy and intelligibility may be more effective.  
In this study, we propose a new architecture for text-to-grammar tasks based on the grammatical knowledge of part-of-speech and dependency parsing, a vital task format in natural language processing. The text-to-grammar task is a downstream task to constrain the primary ASR model, especially in grammatical representation. In order to enhance the effective efficiency of the text-to-grammar task and further influence the ASR output, the top hypothesis from the standard encoder-decoder ASR system is equally regarded as an additional input via a new embedding layer.  
The details of the auxiliary text-to-grammar task are shown in Figure 3. Here, we mark the grammar-label sequence as \(y_{gram}\). In addition, the \(h_{u}\) is used to express the hidden states of the decoder module and the \(\text{h}_{\text{e}}\) is the representation of the one best decoding  
Figure 2: Reinforcement of word embedding with grammar embedding.  
result encoded by the embedding layer. After obtaining \(h_{u}\) and \(h_{e}\), the addition operation is employed to merge them as the input of the text-to-grammar task. The encoder of the transformer is used as the backbone network of the text-to-grammar. The following formula describes the final loss function at the training stage and \(\theta\) is introduced as a hyper-parameter to balance the two tasks.  
\[Loss_{t2g}=CE\big{(}[h_{e}:h_{u}],\ y_{gram}\big{)} \tag{5}\]  
\[Loss_{final}=Loss_{asr}+\theta Loss_{t2g} \tag{6}\]
The grading of black tea primarily relies on traditional sensory evaluation and analysis, which is highly subjective. Combining grade samples with indicator components for auxiliary classification may serve as an effective approach for future tea grading. Flavor chemistry studies on standard samples of different grades have been frequently reported. [PERSON] et al. [19] compared sensory and metabolomic differences among various grades of innovative Congou black tea. They found that MKH (the full name of MKH is Minkehong, an innovative black tea from the Ningde region) grades were highly correlated with Thr (Threonine), Ile (Isoleucine), and Pro (Proline), and identified characteristic key aroma components and their features from premium to third-grade MKH, integrating sensory analysis results. [PERSON] et al. [20] analyzed the flavor chemistry components of different grades of traditional Tanyang Congou tea. They found that epigallocatechin (EGC), catechhin (C), and gallic acid (GA) were closely associated with its sweet and mellow aftertaste. Additionally, they identified volatiles such as 1-pentanol, propyl hexanoate, and linalool, which are linked to sweet and floral aromas. Furthermore, researchers have conducted comprehensive and objective metabolomic studies using standard samples of premium teas (e.g., Wuyi rock tea, Anxi Tieguanyin, Longjing green tea, Fuding white tea, and Pu'er tea) of different grades [21; 22; 23; 24; 25; 26]. These studies not only established relationships between grade, flavor, and chemical components but also provided indicative metabolic markers for tea grading. However, as a renowned tea-producing region in China, research on Ningde Tianshan tea remains limited, with only preliminary studies by [PERSON] et al. [8], [PERSON] [27], and others reporting on its processing techniques and quality characteristics. In 2021, the group standard \"T/NDJCCX 003-2021 Tianshanhong Congou Black Tea\" was issued by the Jiaocheng District Tea Industry Association of Ningde City. The implementation of this standard provided an official reference for the production and grading of TSH-related products. However, the differences in intrinsic compounds among different grades of TSH, as well as the relationships between sensory quality, chemical components, and flavor, remain to be further explored. In this research, different grades of TSH samples, obtained from the Tea Association of Jiaocheng District, Ningde, produced by Fujian Hongjun Agricultural Development Co., Ltd. (Ningde City, Fujian Province, China), were utilized as research materials. Sensory evaluation and basic biochemistry indicators were conducted as the preliminary step. UPLC-MS and GC-MS were utilized to identify the non-volatile components (including five catechins, 19 amino acids, etc.) and volatile compounds in TSH. Furthermore, we identified the key differential compounds among different grades of TSH using stoichiometry combined with multivariate statistical analysis. This study aimed to provide molecular evaluation results for approving the classification of different grades of TSH, as well as act as a reference for standardized production methods.
(e.g., fruit or protein-like yeast hydrolysates) can be mixed with insecticides and used in traps or sprays to target both immature sexes [7], these food baits display relatively low persistence. In addition, their efficacy is highly dependent on the size of the population and weather conditions [1]. As such, in the absence of a strong female-specific synthetic attractant, pest management alternatives are urgently needed.  
Bacteria present on the host plant phyllosphere constitute the main source of proteins for female fruit flies [8], which is necessary for egg development and to reach sexual maturity [9; 10; 11; 12]. Most bacteria identified from fruit fly digestive organs belong to the family Enterobacteriaceae, which constitute the dominant microbiome taxa associated with fruit fly infested fruits and plants [13; 14; 15; 16]. Enterobacteriaceae, which are not obligate endosymbionts, are acquired by the insect from its environment while foraging for food on leaves and fruit surfaces [13; 16]. Although previous chemical and behavioral studies have linked bacterial symbionts with attraction of fruit fly species, such as the Mediterranean fruit fly (_Certaintis capitata_), the Mexican fruit fly (_Anastrepha ludens_), and the olive fruit fly (_Bactrocera oleate_) [17; 18; 19; 20; 21], the role of bacterial symbionts in the biology of _B. tryoni_ remains poorly understood.  
Olfaction is essential for insects to locate potential food, mates, or search for suitable habitats, and oviposition sites [22]. Recent studies of plant-insect interactions have revealed that the attractiveness of the host plant to an insect is not only driven by the volatiles produced by the host plant but may also be influenced by microbial volatile organic compounds (MVOCs) present on the plant [22; 23]. Yet, despite recent descriptive studies of the microbiome associated with _B. tryoni_[16; 24], pest management efforts have been focused on using generic yeast hydrolysate or autolyase as sources of attractant, and not bacterial symbionts.  
In this study, we investigated the olfactory responses of virgin QFF to four symbiotic bacteria belonging to the family Enterobacteriaceae, commonly found in association with QFF. MVOCs emitted from these bacteria were collected under different media and conditions using two different headspace volatile collection methods. Chemical profiles were identified through gas-chromatography coupled with mass-spectrometry (GC/MS), and responses of female QFF to MVOCs were assessed via electrophysiological and behavioral assays.
# Ferrites and Nanocrystalline Alloys Applied to DC-DC Converters for Renewable Energies
###### Abstract  
The medium frequency transformer (MFT) with nanocrystalline alloys is quintessential in new DC-DC converters involved in various front-end applications. The center piece to achieve high-performance, efficient MFTs is the core. There are various options of core materials; however, no deep information is available about which material characteristics and design procedure combo are best to get high performance MFTs while operating at maximal power density. To provide new insights about interrelation between the selection of the core material with the compliance technical specifications, differently to other proposals, this research work aims to design and build, with the same methodology, two MFT prototypes at 20 kHz, with nanocrystalline and ferrite cores, to highlight power density, and overall performance and cost, as matching design criteria. As the experimental results show, a nanocrystalline core has the highest power density (36.91 kW/L), designed at 0.8 T to obtain low losses at 20 kHz, achieving an efficiency of 99.7%. The power density in the ferrite MFT is 56.4% lower than in the nanocrystalline MFT. However, regarding construction cost, the ferrite MFT is 46% lower, providing this a trend towards low-cost DC-DC converters. Finally, high power density in MFTs increases the power density of power DC-DC converters, which have relevant applications in fuel cell-supplied systems, renewable energies, electric vehicles, and solid-state transformers.  
DC-DC converter; electric vehicles; renewable energy; solid state transformers +
Footnote †: journal: _Sciences_
# Research on Optimal Dispatching Strategy for Micro-Energy-Grid of Protected Agriculture
## 5 Optimal Dispatching of Micro-Energy-Grid
### Constraint Equation
#### 5.2.2 Energy Conversion Element Constraints  
Energy conversion elements in agricultural greenhouse of micro-energy-grid include MT, absorption heat pump, ASHP and PV power generation equipment, which should meet the inequality constraints of Equations (20)-(24).  
\[0\leq P_{CHP}(t)\leq P_{CHP\max} \tag{20}\]\[0\leq P_{AHP}(t)\leq P_{AHP_{\max}} \tag{21}\]  
\[0\leq H_{CHP}(t)\leq H_{CHP_{\max}} \tag{22}\]  
\[0\leq H_{AHP}(t)\leq H_{AHP_{\max}} \tag{23}\]  
\[0\leq P_{PV}(t,s)\leq P_{PV\max}(t,s) \tag{24}\]  
where \(P_{CHP\max}\) and \(H_{CHP\max}\) are the maximum power of CHP generation and heat generation. \(P_{AHP_{\max}}\) and \(H_{AHP_{\max}}\) are the maximum power of ASHP consumption and heat generation. Equation (24) denotes the range of actual PV output power. \(P_{PV\max}(t,s)\) is the maximum PV output value of scenario \(s\) at moment \(t\).