esa-sceva/satcom-chunk-collection huggingface dataset:
# Demodulation Technique Based on Laser Interference for Weak Photo-Acoustic Signals on Water Surface
###### Abstract  
To detect underwater sound-generating targets, a water surface acoustic wave laser interference and signal demodulation technique is proposed in this paper. The underlying principle of this technique involves casting a laser beam onto the water surface disturbed by an underwater acoustic source and creating interference between lights reflected by the surface and reference lights. A data acquisition and processing system was employed to obtain water surface acoustic wave information from the interference signals by means of demodulation, thus allowing detection of the underwater target. For the purpose of this study, an interference detection platform was set up in an optical dark chamber. High-frequency water surface fluctuations were introduced in the reference optical path as the phase generated carriers to create laser interference signals in two different paths, which received demodulation based on an improved arc tangent demodulation algorithm and characteristic ratio algorithm, respectively, in view of their different frequencies. Water surface wave information was then derived from such low-frequency and high-frequency signals. According to test results, in the frequency range of 200 Hz-10 kHz, the frequency detection accuracy was better than 1 Hz. The amplitude measurements exhibited high repeatability, with a standard deviation lower than 2.5 nm. The theory proposed in this paper is therefore experimentally verified with good results.  
Keywords:optical interference; phase generated carrier; phase demodulation; water surface acoustic waves +
Footnote †: journal: Applied Sciences
# Research Progress on Conducting Polymer-Based Biomedical Applications
## 2 Conducting Polymers (CPs)  
CPs have \(\pi\)-conjugated backbones in their structure. sp2-hybridized atoms with alternating single and double bonds enable the CPs to exhibit electrical conductivity. For this reason, they are also called conjugated polymers in their neutral states before they are processed to obtain permanent charges. Polyacetylene (PA) was first recognized as a CP in the 1970s and has been widely exploited ever since [39; 40]. However, this noncyclic polyene is unstable in air and is therefore difficult to process [41]. As a result, solution-processible aromatic CPs, such as PPy, PANI, polythiophene (PT), and poly(3,4-ethylenedioxythiophene) (PEDOT), have become a popular alternative [42]. Their phenyl or pentyl groups offer excellent thermal stability and conductivity [43; 44]. In Table 1, the structures and applications of the aforementioned aromatic CPs are shown.  
Two commonly used methods to synthesize the CPs are chemical and electrochemical redox polymerization. The former usually produces powders, whereas a thin film is obtained via the latter.  
Although the chemical synthetic route enables the mass production of CPs, its process is typically more complicated [41]. It is also worth noting that further modification of bulk CPs after polymerization is necessary to obtain the required electronic properties. On the other hand, the processes of polymerization and doping are more controllable, and thin films are readily obtainable in the case of the electrochemical polymerization technique. However, this method is not suitable for large production quantities [45].  
The charges in the CPs are controlled via doping where they are oxidized (p-doping) or reduced (n-doping) while retaining neutrality via counter ions from doping. Figure 1 depicts the p-doping of heterocyclic polymers. Charge carriers injected in the form of charged polarons (radical ions) or bipolarons (dications or dianions) migrate along the conjugated CP backbone, from which electrical conductivity is generated [41]. Owing to their unique electrical properties, the CPs have been of interest in a variety of scientific applications, including capacitors, field emission display, surface protection, and biomedical engineering [42].
## 2 Preliminaries to the C-HARQ Protocol
### Incremental Redundancy-HARQ and RCPC Codes  
For any wireless network, when a basic ARQ scheme is combined with forward error-correcting coding, the resulting error-control scheme is called Hybrid ARQ (HARQ). In HARQ, the original data is encoded with a FEC code, and the redundant FEC bits are either immediately transmitted along with the data or on request from the destination when it detects errors. Based on these two different techniques, two types of HARQ are defined: Type-I and Type-II. In Type-I HARQ, the source always transmits/retransmits the entire code (consisting of data bits and redundant FEC bits) to the destination, whereas in Type-II HARQ (also known as Incremental Redundancy-HARQ), only part of the data is transmitted at first, and the FEC part (which may be further divided into smaller FEC packets) is sent later to the destination, when required. The destination then combines the erroneous data packets with these transmitted redundancies to attempt forward error correction. Generally, Type-I HARQ suffers from capacity losses under good channel conditions because of the extra redundancy introduced, which may be twice the size of data in some FEC codes, whereas, IR-HARQ does not suffer from such a loss, as it expends channel capacity only when needed; it also performs with good sensitivity under poor channel conditions because of the coding gain. Thus, in this paper, IR-HARQ is selected as the HARQ technique, to be combined with CARQ, primarily because of its on-demand method of forward error correction.  
To implement IR-HARQ, the most commonly used error-correcting codes are the rate-compatible punctured convolution (RCPC) codes [15]. They employ a convolution encoder equipped with predefined puncturing patterns to generate redundancies of IR-HARQ. At first a suitable convolution encoder is used to encode _d-bit_ data into _m-bit_ codewords called the Mother code (code rate = _d/m_). Then, by using a suitable puncturing pattern, some bits in the Mother code are deleted, to be left with a punctured codeword of higher code rate. The punctured mother code forms the message for original transmission and the deleted bits are enclosed into multiple packets to form the FEC packets, which are sent later. The probability of error correction increases when the erroneous message is decoded along with the following FEC packets. The detailed description of the packet formation technique, using convolution coding and puncturing, is presented in Section 3.
# Hybrid Multi-Granularity Approach for Few-Shot Image Retrieval with Weak Features
## 6 Conclusions  
This paper presents a multi-granularity retrieval algorithm based on an unsupervised image augmentation network, and it is designed to tackle the challenge of efficient retrieval of few-shot and weak-feature data. By introducing the AugODNet_BRA feature extraction method, the algorithm employs unsupervised learning to capture high-level semantic features from images with few samples, small targets, and weak features. The inclusion of a Omni-Dimensional Dynamic Convolution module and a Bi-Level Routing Attention mechanism enhances the model's adaptability to complex scenes and improves its ability to capture fine details of small targets. Furthermore, the optimized loss function boosts the robustness and distinctiveness of the features, leading to more accurate retrieval.  
In the comparative experiments, the AugODNet_BRA algorithm demonstrated superior performance over baseline and other classic retrieval algorithms across multiple metrics. On the SubCATHR-DET dataset, it achieved a precision of 82.3%, a recall of 79.1%, an F1 score of 80.7%, and a mAP of 78.7%, representing respective improvements of 10.7%, 18.9%, 15.3%, and 8.6% over the baseline AugNet method. These results highlight the algorithm's significant advantages in handling small-target and weak-feature data. Additionally, ablation experiments confirm the effectiveness of each component: the Omni-Dimensional Dynamic Convolution module enables the model to adaptively process diverse target features and enhances feature extraction; the Bi-Level Routing Attention mechanism strengthens the model's ability to capture key features and optimizes the distinguishability of weak features, thereby improving retrieval accuracy and generalization; and the optimized loss function aids in extracting more distinctive and robust features.  
In future research, we aim to further refine the existing model and enhance the algorithm's real-time and scalability to accommodate a broader range of applications and higher real-time demands. Moreover, we plan to apply the algorithm to the recognition of carrier-based aircraft tail hooks and arresting gear engagement states with the goal of achieving human-machine collaborative guidance during aircraft landing. This work is expected to contribute to technological advancements in related fields.  
Conceptualization, A.L.; methodology, A.L., Z.L., Y.L., P.L., and K.W.; software, P.L.; validation, P.L.; investigation, Z.L.; writing--original draft preparation, A.L.; writing--review and editing, Z.L., Y.L., and K.W.; supervision, K.W.; project administration, K.W. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the China Postdoctoral Science Foundation (No. 2020M682348) and the Innovation Foundation of Ocean Defense Technology (JJ-2022-709-01).  
The data will be made available by the authors on request.  
The authors declare no conflicts of interest.
###### Abstract  
The extracts of _Glaucium grandiflora_ have been used to treat neurodegenerative diseases. Nonetheless, no former study has investigated whether the alkaloid extracts of _G. grandiflora_ have antioxidative effects against oxidative stress. The aim of the present study was to determine the antioxidative effects of the alkaloid extracts of _G. grandiflora_ with a variety of targets and probable mechanisms. First, we used spectrophotometry to investigate alkaloid extracts with respect to their alkaloid amounts. Then, we determined the alkaloid extracts' impact on thiol/disulfide homeostasis, total oxidant status/total antioxidant status/oxidative stress index, and antioxidant enzyme activities. Finally, the effects of alkaloid extracts on the genes in the NRF2-KEAP1 pathway were determined via qRT-PCR. We conducted molecular docking analyses to determine the potential binding of isoquinoline alkaloids found within the alkaloid extracts with target proteins. We observed the best results from chloroform alkaloid extract and methanol alkaloid extract. Chloroform alkaloid extract was prominent in DPPH radical scavenging and metal ions chelating, and methanol alkaloid extract showed significant hydroxyl radical scavenging, lipid peroxidation, and superoxide anion radical scavenging activity. Alkaloid extract groups substantially increased in total thiol activity, native thiol activity, disulfide activity, total antioxidant status level, antioxidant enzyme levels, and gene expression levels (GCLC, HO-1, NRF2, and NQO1) compared to the H\({}_{2}\)O\({}_{2}\) group. Also, alkaloid extract groups led to a significant drop in total oxidant status level, oxidative stress index level, and KEAP1 gene expression level relative to the H\({}_{2}\)O\({}_{2}\) group. According to our study results, oxidative stress brought about by H\({}_{2}\)O\({}_{2}\) was regulated by alkaloid extracts. As a result, a phytochemical-based therapeutic that regulates H\({}_{2}\)O\({}_{2}\)-induced oxidative stress was brought to the neurochemical field.  
Keywords:antioxidant effect; hydrogen peroxide; neurodegenerative diseases; molecular docking; oxidative stress; thiol/disulfide homeostasis +
Footnote †: journal: Applied Sciences
# Numerical and Experimental Analysis of Labyrinth Seals with Rhomboidal Cells
## 2 Numerical Analysis
### CFD Analysis on Test Article Geometry  
As described in [14, 18], the Test Article replicates one stage and the next stator of an aeronautical Low Pressure Turbine (LPT), properly scaled. Within the Test Article (TA) (Figure 9), there are three different mass flow rates. Two of the three mass flow rates stream into the lower chamber: the main mass flow, i.e., the Flow Path (FP) and the Cooling (Coo), while the last mass flow rate, the Active Clearance Control, flows into the separate upper chamber.  
Since there are no rotating parts in the TA, the pressure drop dictated by the blade on the FP is reproduced thanks to the introduction of a flow restrictor below the blade tip. This restrictor (Figure 10) was designed to obtain a fixed pressure drop (blade upstream-downstream) \(\beta\) = 1.1.  
The area of the TA (Figure 9) in which the restrictor, the tip of the blade and, in front, the labyrinth seal are positioned is the one considered to perform the CFD analysis on the TA geometry.  
The CFD analysis was carried out reproducing the rhomboidal pattern R3 (see Table 3), which shows the greatest reduction in the discharge coefficient in the CFD model. For the numerical simulations, only the FP was considered because it is only on this mass flow rate that the labyrinth seal acts to minimize leakages.  
The aim of this analysis is to use the validated numerical models to predict the leakage behavior of this alternative pattern. Figure 11 shows the boundary conditions, while for the setup settings, we can refer to Table 4, except for the total inlet temperature.  
Figure 10: Flow restrictor [14].  
Figure 9: Main components and mass flow rates [14].  
The inlet temperature to perform the CFD simulation has been set at 873 K, as this temperature is the maximum temperature to which the FP can be heated. The pressure drop \(\beta\), due to the rotating blade, was set equal to 1.1 in accordance with what happens in the TA.  
Figure 12 represents the area under the labyrinth seal and reports the three mass flow rates of interest. In Figure 12, \(\dot{m}_{FP}\) is the total FP mass flow rate, while \(\dot{m}_{restr}\) and \(\dot{m}_{leak}\) are the mass flow rates flowing through the restrictor and labyrinth seal, respectively.  
Both \(\dot{m}_{FP}\) and \(\dot{m}_{restr}\) were calculated in the CFD model. The first one is calculated at the inlet of the CFD domain and the second at the inlet of the flow restrictor holes. The leakage flow rate \(\dot{m}_{leak}\) was calculated by subtraction. The simulation performed shows that 73% of the mass flow rate passes through the restrictor, while the remaining 27% flows above the fin tip. This leakage flow is lower than the one previously calculated [14] using honeycomb cells, which was equal to 29.4%. This result is in agreement with the results reported in the previous paragraph, obtained by performing the CFD analyses on the test model.
## 2 Materials and Methods
### Statistical Analysis  
Two-way independent analysis of variance (ANOVA) and Tukey-Kramer multiple comparison test were used for statistical analysis. \(p\) values \(<\) 0.05 were considered significant and \(<\)0.001 were considered extremely significant. To investigate the correlation between the distribution of the size of the cells and the size of the nuclei, the irradiated and sham cells were analyzed (counted) over the same number of subgroups (Table 1). Pearson's correlation coefficient was calculated using the Excel (Microsoft Office Professional pus 2016) built-in package.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \begin{tabular}{c} **Number of** \\ **Subgroup** \\ \end{tabular} & \
\begin{tabular}{c} **Nucleus Area** \\ **(\(\mu\)m\({}^{2}\))** \\ \end{tabular} & **Content of Interval** & **Form of the Nucleus** &
\begin{tabular}{c} **\% of Total Number in** \\ **Population** \\ \end{tabular} \\ \hline
**1–2** & 50–150 & Interphase-G0-G1 & round or oval & \(30\pm 3.7\%\) \\
**3–4** & 150–200 & Interphase-G1-S & round or oval & \(46\pm 5.1\%\) \\
**5–6** & 200–250 & Interphase-S-G2 & round or oval & \(20\pm 2.9\%\) \\
**6–7** & 200–300 & Mitosis’s & dividing nuclei & \(9\pm 1.9\%\) \\
**8–9** & 300–400 & “Monsters”/huge & multi-lobed & \(4\pm 1.3\%\) \\
**10** & 500–600 & Polyploid & poly-nuclear & \(1\pm 0.67\%\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Distribution of H1299 cell population based on nucleus area, size, and nuclear morphology. Subgroups formed are represented as percent of population.
## 4 Experiments and Analysis
### Prototype Fabrication and Experimental Setup  
Two prototypes were fabricated and tested under different vibration conditions, as shown in Figure 5. The \"S\"-shaped power-generating beam of the harvester is embedded in the middle of the limiting module, with PVDF Piezoelectric Film (IPS-17020) attached to the surface of a steel piece (Steel Model: 301), which has a thickness of 0.1 mm. PMMA (Polymeric Methyl Metachrylate) is used as the material for the base, column, and limiting module in the prototype production. The U-shaped torsional beam in the up-and-down vibration energy harvester is made of 301 steel with a thickness of 0.5 mm, and the end mass block's weight is 10 g. Additionally, the design of the blocking fluid in the cylindrical flow retarder (\(\Phi\)60 \(\times\) 150 mm), made of Polystyrene foam, is vital for absorbing wind field energy by VIV, thus being the key to the successful design of a wind-induced vibration energy harvester.  
As shown in Figure 5, the SA-SG030 model signal generator is employed to output waveform signals to the SA-JZ020 model shaker to conduct up-and-down vibration excitation on the energy harvester. Moreover, the FD500-20C model ring return wind tunnel experimental platform provides the test environment for the other energy harvester. The Data Acquisition Instrument (DH5922 model) and the Laser Displacement Meter  
Figure 4: Design sketches of the energy harvester at different excitation conditions: (**a**) The up-and-down vibration excitation; (**b**) The wind-induced vibration excitation.  
(HG-C1200 model) are responsible for obtaining voltage output signals and movement displacement signals, respectively, during the energy harvester test process.
## 3 Methods for Precise Relative Orbit Determination  
Independent precise relative orbits of TH-2 were generated by NDT and CHS with different software and strategies. The following briefly introduces the methods of PROD of NDT and CHS. The strategy of NDT and CHS software packages for baseline determination are displayed in Table 2.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Item** & \begin{tabular}{c} **Global Positioning** \\ **System Satellites (GPS)** \\ \end{tabular} & \begin{tabular}{c} **Medium Earth Orbit** \\ **Satellites (MEO)** \\ \end{tabular} & \
\begin{tabular}{c} **Inclined Geosynchronous** \\ **Orbit Satellites (IGSO)** \\ \end{tabular} &
\begin{tabular}{c} **Geostationary Earth** \\ **Orbit Satellites (GEO)** \\ \end{tabular} \\ \hline L1\textbackslash{}B1 (m) & 0.26 & 0.39 & 0.21 & 0.22 \\ L2\textbackslash{}B3 (m) & 0.20 & 0.15 & 0.13 & 0.14 \\ carrier phase & 4.7 & 3.8 & 4.0 & 2.6 \\ fitting residuals (mm) & & & & \\ \hline \end{tabular}
\end{table}
Table 1: Average value of the daily root mean square (RMS) of multipath error and carrier phase fitting residuals.  
Figure 3: Variation in code multipath error with elevation angle for different satellites: (**a**) GPS satellites, (**b**) BDS2 Medium Earth Orbit satellites (MEO) satellites, (**c**) BDS2 Inclined Geosynchro-nous Orbit satellites (IGSO) satellites, and (**d**) BDS2 Geostationary Earth Orbit (GEO) satellites.
## 2 Materials and Methods
### Satellite Imagery
#### 2.3.2 Optical Data  
While multiple sources of optical imagery are available, Landsat and Sentinel-2 images were selected for this study due to several advantages these systems offer for updating CHS charts:  
1. Spectral resolution: Landsat-8 [33] and Sentinel-2 [34] contain spectral bands which will assist with image classification and interpretation for land cover.  
2. Historical data: The historical archive of Landsat data [33] will help evaluate land cover changes and the rate of change.  
3. Large swath: The 180 and 290 km swath widths for Landsat-8 [33] and Sentinel-2 [34] respectively reduce required image processing time and the number of images that need to be acquired.  
4. Free data: Both Landsat-8 and Sentinel-2 represent freely available imagery sources, allowing project costs to be reduced.  
Since historical data were required, Landsat imagery was primarily used for this study. Sentinel-2 imagery was acquired to extract the most recent shoreline. Table 2 summarizes the images used to detect the rate of change.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Acquisition Date** & **Acquisition Time (UTC)** & **Beam Mode** & **Polarization** & **Water Level (m)** \\ \hline October 8, 2014 & 15:39:39 & FQ15 & HH, HV, HV, VV & 12.125 \\ \hline September 7, 2016 & 15:39:45 & FQ 25 & HH, HV, HV, VV & 11.482 \\ \hline October 19, 2015 & 02:31:31 & Spottight 15 & HH & 11.075 \\ \hline October 9, 2017 & 15:39:45 & Fine 23 & HH, HV & 11.337 \\ \hline \hline \end{tabular}
\end{table}
Table 1: RADARSAT-2 metadata with water level [22]. All images were obtained in Single Look Complex format.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Source** & **Bands** & **Acquisition Date** & **Water Level (m)** \\ \hline Landsat-1 & G, R, NIR & September 4, 1972 & N/A \\ \hline Landsat-3 & G, R, NIR & July 14, 1982 & 11.635 \\ \hline Landsat-5 & B, G, R, NIR, SWIR & July 25, 1992 & 12.297 \\ \hline Landsat-5 & B, G, R, NIR, SWIR & August 9, 2003 & 12.224 \\ \hline Landsat-5 & B, G, R, NIR, SWIR & August 31, 2011 & 11.741 \\ \hline Sentinel-2 & B, G, R, NIR & June 13, 2018 & 12.896 \\ \hline Landsat-8 & B, G, R, NIR, SWIR & July 28, 2017 & N/A \\ \hline \hline \end{tabular}
\end{table}
Table 2: Optical data summary including red (R), green (G), blue (B), near infrared (NIR) and short-wave infrared (SWIR) band usage and acquisition dates and associated daily water level [32].