esa-sceva/satcom-chunk-collection huggingface dataset:
# Remote Sensing Multimodal Image Matching Based on Structure Feature and Learnable Matching Network
###### Abstract  
Matching remotely sensed multimodal images is a crucial process that poses significant challenges due to nonlinear radiometric differences and substantial image noise. To overcome these difficulties, this study presents a novel and practical template-matching algorithm specifically designed for this purpose. Unlike traditional approaches that rely on image intensity, the proposed algorithm focuses on matching multimodal images based on their geometric structure information. This approach enables the method to effectively adapt to variations in grayscale caused by radiometric differences. To enhance the matching performance, principal component analysis calculation based on the log-Gabor filter is proposed to estimate the structural feature of the image. The proposed method can estimate the structure feature accurately even under severe noise distortion. In addition, a learnable matching network is proposed for similarity measuring to adapt to the gradient reversal caused by the radiometric difference among remotely sensed multimodal images. Infrared, visible light, and synthetic aperture radar images are adopted for the evaluation, to verify the performance of the proposed algorithm. Based on the results, the proposed algorithm has a distinct advantage over other state-of-the-art template-matching algorithms.  
remotely sensed image; multimodal image; template matching; principal component analysis; structure feature +
Footnote †: journal: Medical Image Analysis  
1
Footnote 1: [[https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci)]([https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci))  
2023 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
# Treatment of Biofilm Communities: An Update on New Tools from the Nanosized World
## 6 Antibiofilm Application of Nanotechnology
### Nanoparticles or Small-Molecule Agents  
Direct effect of different types of nanoparticles on biofilm is the main investigation field, where many different approaches can be envisaged (Figure 6b). Simple and composite metallic nanoparticles are known to have effect both on planktonic and biofilm-embedded bacteria [76; 112; 113; 114; 115; 116]. The attention to further aspects besides antimicrobial efficacy is crucial for further development and translation to clinics. The use of \"green chemistry\" to produce nanoparticles without polluting and toxic reagents is crucial to improve cytocompatibility and lower toxicity of the final product. For example, AgNP were produced using pectin from citrus peel acting as both reductant and stabilizer of the nanoparticle preparation. This strategy yielded an extremely stable product that was also fully cytocompatible and able to promote wound healing in vitro, besides showing high antibacterial and antibiofilm effects [117]. The design of NDDSs in recent years has increased [9], ranging from polymeric or organic nanoparticles, that might be conjugated to targeting molecules, antimicrobial compounds or enzymes in order to degrade biofilm matrix. The delivery of antibiotics is investigated to reduce side effects and increase local concentration of the active molecule inside the biofilm [118]. Furthermore, also the conjugation with enzymes to increase biofilm penetration has been explored, as in the case of poly(lactic-co-glycolic acid) PLGA nanocarriers loaded with DNase I and ciprofloxacin [119], demonstrating increased efficacy and good biofilm inhibition, since DNA is an essential component of EPS. The use of antimicrobial peptides conjugated to nanoparticles has also been explored, since these peptides are smaller and therefore more stable and protease-resistant than entire enzymes; this approach was efficient in vitro but no reports are available in in vivo models [120; 121]. Targeting of persisters cells has been mainly achieved with free compounds [7; 57; 122; 123]. Examples of persister cells causing latent infection upon dormant survival in macrophages is well-known and described for different pathogens [57; 124; 125]. Specific targeting of bacteria [126] or of macrophage-engulfed bacteria [127] was attained with multifunctional antibiotic-loaded nanoparticles, demonstrating the principles to tackle bacteria embedded inside immune cells. However, to the best of our knowledge, there is no report of the combinatorial use of nanomaterials in conjugation to antimicrobials able to tackle persister cells in biofilm. The evaluation of the synergistic effects provided by nanotechnology and antimicrobials will probably help to tackle persisters, mainly responsible for relapsing infections.
## 2 Materials and Methods  
### Raw Material  
The raw material used in this study is a residue waste obtained after the transformation of the Luffa (_L. cylindrica_) seeds (LS--Figure 1D). This residue is often considered waste and is called Luffa seed press cake (Figure 1E). _L. cylindrica_ seeds (LS) were collected by hand upon full maturity of the Luffa fruit (Figure 1A). The luffa fruits were grown to full maturity in the Gourbeyre commune, located in Guadeloupe (French West Indies) and harvested in February 2024. The LS was washed with distilled water, peeled to obtain the LS kernels and then dried at 50 \({}^{\circ}\)C for five hours in a food drier (Biosec, Tausereus, Camisano Vicentino, Italy). The dried seeds were ground to obtain oil, while the seed press cake was a byproduct. The seed press cake of _L. cylindrica_ seeds was spread on a tray and dried for 24 h at room temperature in a closed, ventilated oven under controlled conditions. To ensure food safety, good processing practices were applied to promote effective dehydration. Microbiological analysis confirmed compliance with European safety standards, indicating that water activity and moisture levels were sufficiently low to prevent microbial growth and toxin formation. The dried seed press cake (LP) was vacuum-packed and stored for a maximum of 3 weeks.  
Figure 1: The global _L. cylindrica_ plant (**A**); unripe fruit (**B**); ripe fruit (**C**); seeds (**D**); and the seed press cake (**E**).  
Blends were prepared by combining LP and tapioca flour (TF) (Planteon, Borkow Stary, Poland) at ratios of 30%/70%; 50%/50% and 70%/30% of LP to TF.  
Characterization of Seed Press Cake of L. cylindrical Seeds Powder (LP), Tapioca flour (TF) and Their Blends
# Application of OCT in the Gastrointestinal Tract
## 3 OCT Applications in the GI Tract
### Colon  
Colorectal cancer (CRC) remains a major cause of death in the US and the second leading cause of cancer death with an estimated 145,600 new cases and an estimated 51,020 deaths for 2019 [71]. The survival rate from GI cancers can be improved by 5- to 10-fold if diagnosed at an early stage [5]. The current recommendation in the US is to screen all individuals at age 45 or earlier if deemed at higher risk for CRC based on certain conditions or family history using specific stool tests, radiological exams or direct visualization by colonoscopy [72]. Colonoscopy allows for the removal of suspect adenomatous lesions but can be time-consuming and has miss rates in the range of 17 to 28% [73]. Thus, advanced imaging modalities could help improve detection. OCT has been demonstrated to differentiate colorectal cancer from adenomatous polyps [74; 75], and its ability to reveal the submuc may allow more nuanced polyp treatments. For example, OCT showed normal submuc underneath a rectal polyp near the dentate line and altered its management from a full thickness resection to a less invasive endoscopic mucosal resection (EMR) [76]. High-resolution en face colon images from OCT are analogous to the traditional magnified endoscopic view, but do not require contrast agents; they also yield clinically powerful multi-depth visibility [77]. Thus, OCT has the potential to improve polyp detection and management.  
Besides neoplastic lesions, 3D-OCT was also able to detect changes in inflammatory conditions of the colon. For example, [PERSON]'s disease could be distinguished from ulcerative colitis by demonstration of changes in deeper structures not confined to the mucosa, which are hallmarks of Crohn's Disease [78].  
Moreover, OCT was able to demonstrate submucosal fibrosis, with loss of layering, loss of columnar architecture, and superficial edema, which is associated with more severe ulcerative colitis [79].
# Decentralized Public Transport Management System Based on Blockchain Technology +
## 3 System Design and Implementation
### Description of the Operation of the Compression Algorithm  
Compression algorithms are commonly used to reduce data size for more efficient transmission and storage. In the context of IoT sensors, the amount of data generated can be substantial. Thus, the use of compression algorithms can be particularly important. The theorem being discussed, Theorem 3, provides a mathematical formula for determining the amount of data that can be placed in a container for sending, given various volumes and compression ratios. Specifically, the theorem defines the relationships between the amount of data placed in the container (V\({}_{1}\)), the volume of primary data from the IoT sensors (V\({}_{2}\)), the volume of serialized primary data from the IoT sensors (V\({}_{3}\)), the amount of uncompressed data placed in the container (V\({}_{4}\)), the volume of compressed data placed in the container (V\({}_{5}\)), and the compression ratios (K\({}_{1}\), K\({}_{2}\), and K\({}_{3}\)) associated with serialization, container placement, and the compression operator, respectively. One can optimize compression algorithms for IoT data transmission and storage by understanding these relationships.  
**Theorem 3**.: _Let: \(V_{1}\)--the amount of data placed in the container to be sent in bytes; \(V_{2}\)--the volume of primary data from the IoT sensors in bytes; \(V_{3}\)--the volume of serialized primary data from the IoT sensors; \(V_{4}\)--the amount of uncompressed data placed in the container; \(V_{5}\)--the volume of compressed data placed in the container; \(K_{1}\)--compression ratio for the serialization of primary data from the IoT sensors (conversion to binary format); \(K_{2}\)--compression ratio when placing data in a container; \(K_{3}\)--the compression ratio in the data container after applying the compression operator (algorithm). Then, the amount of data placed in the container for sending can be determined as follows:_\[V_{1}=V_{2}(K_{1}*K_{2}*K_{3}) \tag{5}\]  
\[V_{3}=V_{2}*K_{1} \tag{6}\]  
\[V_{4}=V_{3}*K_{2} \tag{7}\]  
\[V_{5}=V_{4}*K_{3} \tag{8}\]  
\[V_{1}=V_{5}=V_{4}*K_{3}=(V_{3}*K_{2})*K_{3}=(((V_{2}*K_{1})*K_{2})*K_{3})=V_{2}*K _{1}*K_{2}*K_{3} \tag{9}\]  
In conclusion, Theorem 3 provides a formula for determining the amount of data that can be placed in a container for sending, given various volumes and compression ratios. This theorem highlights the importance of using compression algorithms for IoT data transmission and storage, where the volume of data generated can be substantial. By optimizing the use of compression algorithms, one can improve the efficiency and effectiveness of IoT systems.  
**Theorem 4**.: _Let: \(L\)--the useful amount of data from IoT sensors in bits, with a 1-bit data transfer rate/sec; \(C\)--the transfer rate of containers (SBD packets); \(T\)--the data transfer time. Then, we obtain the following:_  
\[L=C*T \tag{10}\]
## 3 Discussion
### Roles of Hormone Biosynthesis Genes in Resin Yield  
Plant hormones are key players involved in the biosynthesis of secondary metabolites [71, 72]. Jasmonates (JAs), as an important endogenous signaling molecule of hydroxyl lipids, are widely involved in plant growth and development, metabolic regulation, stress response, and defense response [73, 74]. When plants are injured, JAs will respond quickly and induce the expression of defense genes and the biosynthesis of secondary metabolites to obtain defense against pests and diseases [75]. In the current study, we observed that JAs (including JA, JA-ILE, MEJA, and OPDA) levels were greatly decreased in high resin yield comparison with those in the common one. (Figure 3). Consistent with the changes in JA levels, many key genes that participated in JA biosynthesis were significantly down-regulated at the protein level (including _AOS_, _AOC_, _OPR_, _ACX_, and _JMT_) (Figure 8B), strongly indicating their involvement in the regulation of resin yield. We supposed that there might be a negative feedback regulation of JA-dependent resin biosynthesis in the formation of resin yield. The resin biosynthesis capacity was stronger in the high resin yield than that in the common one, so the lower JAs levels could maintain the normal resin biosynthesis, which might be the explanation for the lower JAs levels in high resin yield. _COI1_ and _JAZ_ play a crucial role in JA signaling, notably, _JAZ_ acts as a'suppressor' in JA signaling pathway [76, 77]. In this study, _COI1_ and _JAZ_ were greatly down-regulated at the transcript level, indicating that _COI1_ and _JAZ_ might negatively regulate rein yield in masson pine.  
In addition to JAs, it is noteworthy that other hormones such as SAs and GAs are also involved in secondary metabolism [78, 79]. In this study, SA level demonstrated a decreased tendency in the high resin yield, despite no statistically significant difference being investigated between them. Several genes involved in phenylalanine metabolism, including _PAT_, _AOC3_, and _HPD_, were significantly decreased at the protein level, in accord with the decrease of SA and SAG levels. These results indicated the possible involvement of SA in the regulation of resin yield. The GA and terpenoid biosynthesis both use GGPP as a common precursor [80]. In the present study, GAs levels were dramatically different between high and common resin yields. It is worth noting that GA1 content was the highest among all GAs measured, and its content greatly declined in high resin yield. Consistent with the decrease of GA levels, the transcripts of several key genes referred to as GA biosynthesis (including _CPS1_ and _KO1_) were obviously down-regulated. Our results demonstrated that high resin yield could provide more substrates (GGPP) for resin terpenoid biosynthesis by down-regulating GA biosynthesis. Together, these findings revealed that JA, SA, and GA might play an important role in the regulation of resin yield in masson pine.
## 2 Materials and Methods
### CIELAB Colour System  
Colour measurements were performed using a Konica Minolta CR-400 Chroma Meter (Minolta Camera Co., Marunouchi, Chiyoda, Japan). Fresh samples were assessed at the beginning and end of each trial and each medium renewal, with the entire sensor surface pressed carefully onto the seaweed, which had been pre-dried with paper towels. Tristimulus colour coordinates (CIELAB-system) were used to measure the degree of lightness, which stands for perpetual lightness ranging from black to white (L* = 0: black; L* = 100: white); redness (\(\alpha\)*), which represents the coordinate along the red to green (+a* = red, \(-\)a* = green); and yellownes (\(b\)*), which is the coordinate along the yellow to blue (+b* = yellow, \(-\)b* = blue). All measurements were made in triplicate.  
These values were used to calculate chromaticity (C*), which is the saturation of the colour (Equation (3)), and hue (\({}^{\circ}\)\(h\)), which is the tone of the biomass Equation (4) [55]:  
\[C^{*}=\sqrt{a^{*2}+b^{*2}} \tag{3}\]  
\[{}^{\circ}h=arctg\ (b^{*}\div\ a^{*}) \tag{4}\]  
Finally, to assess the effect of the different treatments (nutrients and wavelength) on seaweed colour, the total colour difference was calculated using Equation (5) [55]:  
\[\Delta\mathrm{E}=[(\mathrm{L}^{*}-\mathrm{L}_{0}{}^{*})^{2}+(\mathrm{a}^{*}- \mathrm{a}_{0}{}^{*})^{2}+(\mathrm{b}^{*}-\mathrm{b}_{0}{}^{*})^{2}]^{1/2} \tag{5}\]  
where \(\Delta\mathrm{E}\) quantifies the overall colour difference in a sample (L*, a*, b*) when compared to wild biomass used at the beginning of the trial (L0*, a0*, b0*).
_applied_  
_sciences_  
_Article_  
**Artificial Neural Network-Derived Cerebral Metabolic Rate of Oxygen for Differentiating Glioblastoma and Brain Metastasis in MRI: A Feasibility Study**  
**[PERSON] 1, [PERSON] 1, [PERSON] 2,3, [PERSON] 4, [PERSON] 2, [PERSON] 1 and [PERSON] 2,**  
1 Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany; [EMAIL_ADDRESS] (H.B.); [EMAIL_ADDRESS] (S.H.); [EMAIL_ADDRESS] (L.R.S.)  
2 Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany; [EMAIL_ADDRESS] (M.E.M.); [EMAIL_ADDRESS] (A.E)  
3 Department of Biomedical Informatics at the Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany  
4 Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany; [EMAIL_ADDRESS]  
5 Correspondence: [EMAIL_ADDRESS]  
**Featured Application: MR-derived cerebral metabolic rate of oxygen in contrast-enhancing and peritumoral non-enhancing regions, as calculated by an artificial neural network, allows for robust differentiation of glioblastoma and brain metastasis.**  
**Abstract** Glioblastoma may appear similar to cerebral metastasis on conventional MRI in some cases, but their therapies differ significantly. This prospective feasibility study was aimed at differentiating them by applying the quantitative susceptibility mapping and quantitative blood-oxygen-level-dependent (QSM + qBOLD) to these entities for the first time. We prospectively included 15 untreated patients with glioblastoma (_n_ = 7, median age: 68 years, range: 54-84 years) or brain metastasis (_n_ = 8, median age 66 years, range: 50-78 years) who underwent preoperative MRI including multi-gradient echo and arterial spin labeling sequences. Oxygen extraction fraction (DEF), cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO\({}_{2}\)) were calculated in the contrast-enhancing tumor (CET) and peritumoral non-enhancing T2 hyperintense region (NET2), using an artificial neural network. We demonstrated that OEF in CET was significantly lower (_p_ = 0.03) for glioblastomas than metastases, all features were significantly higher (_p_ = 0.01) in CET than in NET2 for metastasis patients only, and the ratios of CET/NET2 for CBF (_p_ = 0.04) and CMRO\({}_{2}\) (_p_ = 0.01) were significantly higher in metastasis patients than in glioblastoma patients. Discriminative power of a support-vector machine classifier was highest with a combination of two features, yielding an area under the receiver operating characteristic curve of 0.94 with 93% diagnostic accuracy. QSM + qBOLD allows for robust differentiation of glioblastoma and cerebral metastasis while yielding insights into tumor oxygenation.  
**Keywords: brain metastasis; glioblastoma; machine learning; oxygenation; tumor infiltration**
# Enhancing Real-Time Kinematic Relative Positioning for Unmanned Aerial Vehicles
## 6 Conclusions  
This paper presents effective techniques that improve the RTK performance of moving UAVs. These include measurement time synchronizations and cycle slip detectors for low-cost GNSS receivers on flying vehicles. In addition, the causes of ratio test failure in a typical KF filter-based RTK owing to newly included satellites are discussed, and dual KF structures that overcome these drawbacks are presented. The effectiveness of the proposed algorithms was confirmed using data from 45 UAV flight tests. Without synchronized measurement times, both the conventional and dual Kalman filters exhibited notably low average ratio test pass rates, about 16.21 percent. However, implementing the proposed synchronization method for measurement times, the average ratio test pass rates for the conventional and dual Kalman filters improved significantly by 545 and  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Flight Test Idx**} & \multicolumn{2}{c}{**3D RMSE [cm]**} & \multicolumn{4}{c}{**Percentage of Epochs**} \\  & \multicolumn{2}{c}{**(Position Error)**} & \multicolumn{2}{c}{**3D RMSE**} & \multicolumn{2}{c}{**That Passing the Ratio Test [\%]**} & \multicolumn{2}{c}{**Increase Rate in**} \\ \cline{2-7}  & **Conventional KF** & **Dual KF** & & **Conventional KF** & **Dual KF** & **Passing the Ratio Test [\%]** \\ \hline
1 & 2.79 & 2.03 & 27.40 & 96.98 & 100.00 & 3.12 \\
2 & 8.29 & 2.34 & 71.80 & 85.93 & 10  
421 percent, respectively. Also, the appropriate cycle slip detection metrics and thresholds were introduced, tailored to the measurement characteristics of small UAVs. Through the implementation of these proposed cycle slip detection thresholds, our flight test data showed the prevention of false exclusions of two to six satellites. By employing the suggested measurement time synchronization and cycle slip detection techniques, the dual Kalman filter demonstrated significant enhancements in both the ambiguity fix ratio and 3D RMSE of position errors. Specifically, compared to the conventional KF, the dual KF showed average improvements of 23.54 percent and 65.31 percent, respectively, in these metrics. Overall, the proposed algorithms can be used to improve the RTK solutions of dynamic platforms with low-cost GNSS receivers.  
Conceptualization, E.K. and Y.S. Experiments, C.L., Y.S., Software, C.L., Y.S. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Unmanned Vehicles Core Technology Research and Development Program through the National Research Foundation of Korea (NRF) and the Unmanned Vehicle Advanced Research Center (UVARC) funded by the Ministry of Science and ICT, Republic of Korea (No. 2020M3C1C1A01086407). This work was also supported by Future Space Navigation & Satellite Research Center through the National Research Foundation funded by the Ministry of Science and ICT, Republic of Korea (2022M1A3C2074404).  
Data used for the paper are currently unavailable.  
The authors declare no conflicts of interest.
# RMCSat: An F10.7 Solar Flux Index CubeSat Mission
## 3 RMCSat Mission  
The mission of the RMCSat is to demonstrate the feasibility of measuring solar flux density from a nanosatellite platform in LEO. The mission seeks to develop, design, and build the first CubeSat mission of RMC, with an overall purpose of training highly qualified personnel in the general areas of space mission analysis and design, integration and assembly, satellite operations, space weather, and solar activity. The primary objectives of the mission in Table 1 must be achieved while the secondary objectives in Table 2 are desirable outcomes.