esa-sceva/satcom-chunk-collection huggingface dataset:
# Auditory Localization in Low-Bitrate Compressed Ambisonic Scenes
## 6 Conclusions  
Perceptual evaluation of bitrate compression schemes is an important part of mobile spatial audio technology development. Delivering spatially accurate and precise auditory information at low data bandwidth allows for a wider adaptation of immersive technologies. In this paper, we have presented a study on the localization precision of binaural-based Ambisonic reproduction using low-bitrate compression over different Ambisonic orders. The tests were conducted using headphone-based reproduction employing both individualized and generic HRTF sets and with real-world loudspeaker presentations for comparison. We conclude that using strong bitrate compression will not affect the auditory localization in scenes encoded using Opus compression when compared to uncompressed Ambisonic presentations; however, the timbral fidelity aspect of the compressed audio should be considered as well. Using HOA content instead of 1 st-order Ambisonics will improve localization within the scenes, especially when using personalized binaural rendering or multi-loudspeaker reproduction.  
Conceptualization, T.R., J.S. ([PERSON]) and G.K.; Methodology, T.R., I.G.-L., and G.K.; Software, T.R. and I.G.-L.; Validation, T.R. and G.K.; Formal Analysis, T.R.; Investigation, T.R.; Resources, T.R.; Data Curation, T.R., I.G.-L., and J.S. ([PERSON]); Writing--Original Draft Preparation, T.R.; Writing--Review & Editing, T.R., J.S. ([PERSON]) and G.K.; Visualization, T.R.; Supervision, D.T.M. and G.K.; Project Administration, T.R., J.S. ([PERSON]), and G.K.; Funding Acquisition, J.S. ([PERSON]) and G.K.  
This research was jointly funded by Google as part of a Chrome Media Research Award and by the Engineering and Physical Sciences Research Council (EP/M001210/1).  
The authors gratefully acknowledge the participation of the listening test subjects.  
The authors declare no conflict of interest. The sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
# Highly Reliable Fuzzy-Logic-Assisted AODV Routing Algorithm for Mobile Ad Hoc Networks
## 5 Conclusions  
In this paper, we proposed a highly reliable fuzzy-logic-assisted AODV routing algorithm. The proposed algorithm comprehensively considered delay, stability, and residual energy as the routing criteria, and realized the selection of a low-latency, high-link connectivity, and long-life routing through a fuzzy system. Simulation results verified that, compared with traditional AODV and FLRA algorithm, the proposed algorithm has a higher reliability without increasing delay, i.e., better link connectivity and longer route life and is more suitable for the scenarios where users are moving at high speed. Especially, the FL-AODV algorithm is about 10% higher than the AODV algorithm and 25% higher than the FLRA algorithm when the number of nodes is greater than 100 in terms of ratio of reliability to delay, which confirms that FL-AODV algorithm can better achieve high reliability and low latency performance.  
Conceptualization, J.L., M.W., D.W., and P.Z.; writing--original draft preparation, M.W.; writing--review and editing, J.L.; supervision, J.L. and M.W.; project administration, X.Y. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61971127, 61871465, 61871122, by the National Key Research and Development Program under Grant 2020 YFB1806600, and by the Fundamental Research Funds for the Central Universities.  
Not applicable.  
The authors declare no conflict of interest.
# LSTM Recurrent Neural Network for Hand Gesture Recognition Using EMG Signals
## 2 Methodology
### Recurrent Neural Network (RNN) Model  
To perform a hand gesture classification in real-time based on the pre-processed EMG signals, a novel Recurrent Neural Network (RNN) model of LSTM type was proposed. The RNN structure with LSTM configuration has been found to be a good architecture for the identification of temporal patterns in time series [57]. In general many researchers found that the RNNs have the ability to retain information making it an excellent approach for time series applications [58]. In this context, the RNN proposed in this research has a hybrid architecture composed of dense layers wrapping a recurrent layer; it has been found that the approach where dense layers support the recurrent layer allows for an increased performance over models that only have the recurrent layer [59,60]. The overall architecture of the RNN can be seen in Figure 4. Each one of its layers will be explained in greater detail in further Sections 2.3.1 and 2.3.2.  
Figure 5 shows the basic structure of the recurrent layer for the proposed model. Here, each input \(X\) is composed of one sample of each EMG channel in an specific time \(t\); where \(T_{x}\) is the length of the window that represent a hand gesture to classify (\(T_{x}=200\)); and \(a\) represents the activation values passed in each time instant from one recurrent unit to the next one. These activation values \(a\) are propagated thru  
Figure 4: Recurrent neural network general architecture block diagram.  
Figure 3: EMG 200 samples window processing. (**a**) Raw EMG data in 200 samples window; (**b**) EMG window after mean subtraction; (**c**) EMG window after absolute value and moving average filter; (**d**) Filtered and normalized EMG window.  
dependencies between the different time steps and then the last activation \(a^{(T_{x})}\) is used to calculate the output of the network.  
The implementation of the proposed model and its training was done in Python using the Tensorflow library due to the fast and efficient way that this library gives in the implementation of deep learning models. However, in order to have a clear understanding of the models architecture, the next section presents the mathematical definitions for each component of the network.
## 5 Axial Piston Pump Simulation Test
### Experimental Platform  
In this study, simulation tests were conducted to detect anomalies in axial piston pumps using a specialized testbed designed for axial piston pump failure simulations, as illustrated in Figure 11. The test bed was equipped with a pressure sensor positioned at the outlet of the axial piston pump to record pressure signals. Additionally, three vibration acceleration sensors were strategically placed in mutually perpendicular directions (x, y, and z) on the end cover and casing of the axial piston pump to capture vibration signals. Simultaneously, the LabView 2021 software facilitated the monitoring of the operational state of the axial piston pump, enabling the collection of experimental data. A schematic of the experimental setup is shown in Figure 12.  
Figure 10: Flowchart of anomaly detection method.  
The axial piston pump used in the experiment was an MCY14-1B model with displacement of 10 mL/r. The drive motor was a Y132M4 model with a rated rotational speed of 1480 rpm. Data acquisition was facilitated using an NI-USB-6221 data acquisition card with a maximum sampling rate of 250 kS/s. The pressure transducer used was the PT124B-210-40 MPa-GB model, covering a pressure range of 0-40 MPa. The vibration acceleration transducer was a YD72D model with a frequency range of 1 Hz-18 kHz. In the test, artificial faults were introduced by substituting standard components with faulty components through fault injection. Three types of abnormal states were simulated: swashplate wear (artificially inducing wear on the swashplate), sliding shoe wear (removing rounded edges), and single-plunger loose shoe wear (faulty component). The faulty components are depicted in Figure 13. The data collected for the experiment, including those of the normal and three different abnormal states, were obtained under system pressure of 5 MPa. The sampling frequency was set to 50 kHz, with each sampling lasting 1 s.  
Figure 11: Axial piston pump failure simulation test bench.  
Figure 12: Schematic diagram of the experimental setup for simulation of faults in an axial piston pump.
## 4 Performance Evaluation
### Probability of Detection Evaluation  
The performance of the radar system with and without the proposed module is illustrated by the probability of detection (\(P_{d}\)) vs. SNR curves, which are depicted in Figure 15. To maintain a probability of false alarms (\(P_{fa}\)) of \(10^{-6}\), a typical value in radar systems, we used a CFAR processor. For each SNR value, we calculate the \(P_{d}\) value 500 times and plot the average. Doppler values from the low, medium, and high ranges were chosen to show the robustness of the proposed module. In fact, the module exhibited similarly excellent responses for all of these Doppler values. For an SNR greater than \(-12\) dB, the three curves converge and practically achieve 100% detection. As the SNR decreases, the three curves diverge slightly, with medium and high Doppler values being better than the lower ones.  
Comparing the detection curves of the proposed algorithm with the reference curve without the Doppler effect (indicated by the rhombus marker) reveals a degradation of 3 dB when compared to the medium-Doppler-value curve (indicated by the circle marker)  
\begin{table}
\begin{tabular}{c c c} \hline
**Doppler Value** & **Average Accuracy** & **SNR Value** \\ \hline Low Value & 100 \% & \\ \hline Medium Value & 98.2308\% & \(-12\):0 dB \\ \hline High Value & 96.32\% & \\ \hline \end{tabular}
\end{table}
Table 2: Average accuracy of the proposed algorithm.  
Figure 14: Box plot for the distribution of 100 trials on Doppler value data at SNR = \(-3\) dB. (**a**) Low Doppler value of 834 Hz, (**b**) medium Doppler value of 2250 Hz, and (**c**) high Doppler value of 13,010 Hz.  
and 5 dB when compared to the low-Doppler-value curve (indicated by the cross marker). It is important to note that this degradation is considered acceptable when compared to the curve for which the Doppler effect (indicated by the pentagon marker) was applied but without using our module; the curve shows no detection at any given SNR values.
# Harnessing Odorant Receptor Activation to Suppress Real Malodor
## 2 Results and Discussions
### Identification of Effective Antagonists That Suppress Cat-Urine-Responsive Receptors
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \begin{tabular}{c} **Ret.** \\ **Time** \\ **(min)** \\ \end{tabular} & **Name** & \begin{tabular}{c} **Odor** \\ **Description** \\ \end{tabular} & \begin{tabular}{c} **Day6** \\ **Strong Malodor** \\ \end{tabular} & \begin{tabular}{c} **Day2** \\ **Strong Malodor** \\ \end{tabular} & \begin{tabular}{c} **Day3** \\ **Weak Malodor** \\ \end{tabular} & \begin{tabular}{c} **Day5** \\ **Weak Malodor** \\ \end{tabular} \\ \hline a & 5.31 & Trimethylamine & \begin{tabular}{c} ammonia, fish, \\ pungent, rotten \\ \end{tabular} & \(2.2\times 10^{6}\) & \(7.1\times 10^{8}\) & N/D & N/D \\ \hline b & 9.72 & \multirow{2}{*}{2-Pentanone} & \begin{tabular}{c} burnt plastic, \\ ether, fruit, \\ kerosine, ketone \\ \end{tabular} & \(4.5\times 10^{5}\) & \(4.3\times 10^{5}\) & \(7.3\times 10^{5}\) & \(2.8\times 10^{5}\) \\ \hline d & 10.85 & \begin{tabular}{c} 1,1,3,3,5,5,7,7-Octamethyl-7-(2-methylpropoxy)tetrasiloxan-1-ol \\ \end{tabular} & \(2.1\times 10^{5}\) & N/D & N/D & N/D \\ \hline e & 12.72 & \begin{tabular}{c} 2,3,3-Trimethyloctane \\ \end{tabular} & \(2.7\times 10^{6}\) & N/D & N/D & N/D \\ \hline f & 13.87 & gamma-decalactone & \begin{tabular}{c} apricot, fat, fruit, \\ peach, pleasant \\ \end{tabular} & \(2.4\times 10^{5}\) & N/D & N/D & N/D \\ \hline g & 14.07 & 4-Heptanone & Fruit & \(2.6\times 10^{5}\) & \(2.4\times 10^{5}\) & \(1.0\times 10^{5}\) & N/D \\ \hline h & 18.72 & Heyl acetate & \begin{tabular}{c} apple, banana, \\ confectionery, \\ fruit, grass \\ \end{tabular} & \(2.0\times 10^{5}\) & N/D & \(9.1\times 10^{4}\) & \(1.2\times 10^{5}\) \\ \hline i & 21.28 & \
\begin{tabular}{c} Silane, trimethyl[(1- \\ methylethylidene)cyclopropyl]- \\ \end{tabular} &
\begin{tabular}{c} N/D \\ \end{tabular} & N/D & N/D & \(1.2\times 10^{5}\) \\ \hline j & 23.15 & 2-Methyl-4-decanone & \(8.3\times 10^{4}\) & \(1.4\times 10^{5}\) & N/D & N/D \\ \hline k & 23.47 & 3-Metboxy-3-methyl/butanol & \(8.5\times 10^{5}\) & \(5.5\times 10^{5}\) & \(5.4\times 10^{5}\) & \(3.8\times 10^{6}\) \\ \hline
1 & 25.32 & Isovanillin, TBDMS derivative & \(7.1\times 10^{4}\) & \(4.7\times 10^{4}\) & N/D & N/D \\ \hline m & 25.52 & Pyrrole & nut, sweet & \(2.3\times 10^{5}\) & \(2.0\times 10^{5}\) & N/D & \(1.1\times 10^{5}\) \\ \hline n & 25.91 & 2-Hydroxy-iso-butyrophenone & N/D & \(1.2\times 10^{5}\) & N/D & \(1.6\times 10^{5}\) \\ \hline o & 28.88 & 5-Tridecanone &
\begin{tabular}{c} harsh, herb, oil, \\ old nut, spice \\ \end{tabular} & \(9.2\times 10^{4}\) & \(1.2\times 10^{5}\) & N/D & N/D \\ \hline p & 30.59 & Di-sec-Butyl ether & N/D & \(8.8\times 10^{4}\) & N/D & N/D \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cat-urine-specific compounds detected by GC-MS.  
compounds, those that demonstrated inhibitory effects against both cat urine and TMA were considered strong suppressor candidates.
## 2 Theory and Method
### The Governing Equations
#### 2.2.2 Heat Transfer Equation  
The heat transfer equation describes the heat transfer processes in fluids and cavern walls. During the dissolution process, there is a temperature difference between the injected freshwater, the fluid in the cavern, and the salt solid wall. There will be heat convection exchange between the fluids of different temperatures and heat conduction between the fluids and the salt wall, expressed as Equation (2).  
\[\rho\mathrm{C}_{p}\frac{\partial T}{\partial t}+\rho\mathrm{C}_{p}u_{i}\frac{ \partial T}{\partial x_{i}}+\frac{\partial}{\partial x_{i}}\Bigg{(}-k\frac{ \partial T}{\partial x_{j}}\Bigg{)}=Q \tag{2}\]  
where \(\rho\) is the fluid density, kg/m\({}^{3}\); \(\mathrm{C}_{p}\) is the fluid heat capacity at constant pressure, J/K; \(Q\) is the heat source, W/m\({}^{3}\); \(u_{i}\) is the fluid velocity, m/s; and \(k\) is fluid thermal conductivity, m/K.
## 2 Literature Review
S represents a single objective, S* represents the normalization of multiple objectives into a single objective, and M represents multiple objectives. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Model Type** & **Author** & **Model** & **Scheduling Framework** & **Uncertain Times** & **Action Consolidation** & **Look- Forward** & **Multi-Objective/Single-Objective** \\ \hline [PERSON] et al. & & MVDD & One-time & & N & & S \\  (2020) [18] & & & decision & & & & \\  & [PERSON] et al. & & & & & & \\  & (2023) [19] & & & decision & & & S* \\  & [PERSON] et al. & & & & & & \\  & (2023) [20] & & & decision & & & S* \\  & [PERSON] et al. & & & & & & \\  & (2015) [21] & & & decision & & & S* \\  & [PERSON] et al. & & & & & & \\  & (2023) [22] & & & decision & & & M \\  & [PERSON] et al. & & & & & & \\  & (2022) [23] & & & decision & & & \\  & [PERSON] et al. & & & & & & \\  & (2020) [24] & & decision & & & & S* \\  & [PERSON] et al. & & & & & & S* \\  & (2018) [25] & & & decision & & & S* \\  & [PERSON] et al. & & & & & & \\  & (2022) [26] & & & decision & & & S \\  & [PERSON] et al. & & & & & & \\  & (2023) [3] & & & decision & & Y & & M \\  & [PERSON] et al. & & & & & & \\  & (2021) [6] & & and delivery & & decision & & & S \\  & [PERSON] et al. & & & & & & \\  & (2021) [17] & & & decision & & Y & c & f & S \\  & [PERSON] et al. & & & Rolling & & & \\  & (2018) [7] & & & decision & N & c & & S \\  & [PERSON] et al. & & & Rolling & & & & \\  & (2019) [8] & & DVRPs & decision & N & c & & S \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Related literature. According to Table 1, the following conclusions can be made: (1) Aiming at the uncertainties in takeaway delivery, some scholars adopt stochastic programming to make one-time scheduling decisions. At present, there is no relevant research to deal with uncertain scheduling optimization under dynamic conditions based on a rolling framework. (2) As for the combination problem in takeout delivery scheduling, the existing studies only discussed the order combination under the centralized transportation organization mode, while the action combination under the decentralized transportation organization mode was not mentioned. (3) For the consideration of after-effect, the existing results are based on statistical models for demand forecasting. This method performs well in macro-order demand forecasting but has difficulty predicting micro discrete events (e.g., customers, meal delivery times, etc. ).
# Synergistic Potential of Optical and Radar Remote Sensing for Snow Cover Monitoring
## 4 Results  
An analysis of temperature trends across the Iberian mountains revealed the Pyrenees as the coldest range during winter (considered as the time span from December to February), approximately 2 \({}^{\circ}\)C cooler than the Cantabrian and Iberian Ranges, and 3.5 \({}^{\circ}\)C cooler than the Central System and the Sierra Nevada. In spring (considered as the time interval from March to May), despite temperatures in the mid-spring period becoming similar to the Cantabrian System, the Pyrenees initially showed a colder trend. Conversely, the warmest temperatures were observed in the Sierra Nevada during winter and the Central System during spring (Figure 3b). Additionally, precipitation patterns across different mountain ranges were contrasted, highlighting the Cantabrian System and the Pyrenees as receiving the highest average accumulated precipitation during winter (506 mm) and spring (323 mm), respectively. In contrast, the Sierra Nevada exhibited the lowest precipitation levels in both winter (332 mm) and spring (132 mm) (Figure 3a).  
Figure 3: _Cont_.
## 5 Conclusions  
In this study, _R. chrysanthum_ was used as the study subject for metabolomic analysis to study plant responses to UV-B caused by an ozone hole. In order to clearly respond to the mechanisms of plant responses to UV-B stress, the pathway map was constructed in order to show the interactions between the DMs. Potential UV-B stress biomarker and UV-B-responsive metabolites were screened by comparing DMs between groups. After UV-B irradiation, 404 metabolites and 93,034 unigenes were detected. A total of 26 of these different metabolites were classified as UV-B-responsive metabolites. Glyceric acid is used as a potential UV-B stress biomarker. The domesticated _Rhododend chrysanthum_ Pall. had high amino acid and SOD content. Enhanced UV-B resistance in tamed _R. chrysanthum_ could stem from the stimulation of sucrose and starch metabolism. The study shows that the domesticated _Rhododend chrysanthum_ Pall. showed significant UV-B resistance. Transcriptomics results showed that both _R. chrysanthum_ showed similar trends after UV-B stress, and both DEGs were mainly focused on cellular process, cellular anatomical entity, catalytic activity, and binding. And, it was also found that the enzymes MGLL, GPAT1_2, GPP, DGK, plSC, and ALDII closely affect the changes in the content of Glyceric acid in _R. chrysanthum_.  
The results of this study further reveal the regulatory mechanism of _R. chrysanthum_'s resistance to UV-B radiation from a metabolomic perspective. In future studies, we will explore the molecular mechanisms of Glyceric acid and 26 UV-B-responsive metabolites and whether they play a role in the resistance of other plants to UV-B stress. The experimental results provide reference for the practical application of extracting a UV-B-resistant complex from plants.  
Writing--original draft preparation, W.Y. and F.G.; writing--review and editing, J.L.; methodology, W.Y.; software, W.Y. and F.G.; visualization, W.Y. and F.G.; supervision, J.L. and X.Z. (Xiangru zhou); project administration, H.X. and X.Z. (Xiaofu zhou). All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Jilin Province Science and Technology Development Plan Project (Grant numbers: YDZJ202301 ZYTS517).  
Not applicable.  
The data used in this study are available from the corresponding author on submission of a reasonable request.  
We are grateful to Jingjie PTM Biolab (Hangzhou, China) Co., Ltd. for providing mass spectrometry support.  
The authors declare no conflicts of interest.
## 4 Field Tests of the GFZ-WISE  
The GFZ-WISE is being developed with the primary goal of performing real-time analysis of data during seismic array measurements for the estimation of S-wave velocity profiles. Once the system is deployed in the field, the GFZ-WSUs create a WMN, allowing an operator with a laptop, where the SeisComP software is running, to retrieve in real-time data from all stations of the network. Therefore, signal analysis procedures can be performed from the user directly on the field. In the meantime, each station continuously stores the raw data in the ring buffer contained on the flashcard (_i.e._, about 20 days worth on a 2 GB card).
## 2 Concept of a Tailored Tether  
The original concept of the tether to be used for AWES application was addressed in detail in [16; 22], where a one-dimensional flexible composite was proposed. The tether structure consisted of a matrix and high-strength fibers and was designedwith supplementary and additional load paths in case of sequential failures. Figure 1(a) shows the schematic concept modeled in drawing software and Figure 1(b) shows the physically manufactured demonstration of the tether made of the elastomer matrix and high-strength glass fiber.  
Figure 1: Examples of airborne wind energy systems (AWES) [12].  
Figure 2: A schematic concept of a tether structure (**a**) and its physically manufactured example (**b**).  
A tailored structural member was conceptually designed to generate a yield-type response with applicability to the arrest of a moving body. The structural member comprised a primary load path, called the primary element, connected in parallel to a longer secondary load path, called the secondary element, at a pair of common nodes. Both primary and secondary elements were combined to form the connector element, which had the sum of the cross-sectional areas of both elements. When external loads were applied to the system in the longitudinal direction, the main elements and connectors were subjected to the tension loads. If all the main elements had the same geometric and material distributions, the failure probabilities of the main elements were the same. In reality, however, there exists an unpredictable progressive failure sequence starting from the main elements, meaning that the secondary elements break after all the main elements break. Figure 3 shows the progressive failure mechanism of the tether structure with ten main elements. As shown in Figure 3, complete failure occurs after the failure of all the main elements and the ensuing failure of the one of secondary elements. Figure 3 also shows the traditional tether structure made of a single element with constant cross-sectional areas along the longitudinal direction with the same total length. The failure responses of both traditional and tailored tether structures are shown in Figure 3 as straight line and zigzag-type (yield-type) responses, respectively. In Figure 3, the areas under the traditional and tailored tether structures represent the mechanical work (force times displacements) required to reach complete failure for each structure. They show that more energy is required to completely break the tailored tether structure compared to the traditional structure because of the larger area (Ats) compared to the area (Aus) of the untailored traditional tether structure.