esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Antenna Design
### The Design of Unit Cell and Proposed Series-Fed Antenna
As \(W_{2}\) increases 0 mm, 1.2 mm, 2.1 mm, and 2.9 mm, the phase of the transmission coefficient of the unit cell decreases \(0^{\circ}\), \(-45.8^{\circ}\), \(-92.5^{\circ}\) and \(-127^{\circ}\), which are close to calculated \(\beta\) in Equation (1). The proposed antennas achieve beam tilting using a progressive phase shift, \(\beta\) in Equation (1), controlled by the phase of the transmission coefficient of the unit cell. Figure 7b shows the RHCP realized gain pattern of the proposed series-fed antennas at 5.84 GHz in the \(\phi\) = \(90^{\circ}\) plane. When \(W_{2}\) is 0 mm, 1.2 mm, 2.1 mm, and 2.9 mm in sequence, the direction of the main lobe is formed at \(\theta\) = \(0^{\circ}\), \(15^{\circ}\), \(30^{\circ}\), and \(45^{\circ}\) in the \(\phi\) = \(90^{\circ}\) plane. The RHCP realized gain patterns in Figure 7b are almost similar to the calculated and normalized array pattern in Figure 6. Beam tilting of the proposed antennas is realized by adjusting the length of the serial feeding line, so an individual antenna is implemented for each beam tilting angle. Figure 7c,d show the simulated reflection coefficients and axial ratios of the series-fed array antennas. The simulated reflection coefficients of broadside series-fed array antenna and \(15^{\circ}\), \(30^{\circ}\) and \(45^{\circ}\) beam tilt series-fed array antennas at 5.84 GHz are \(-19.35\) dB, \(-21.8\) dB, \(-35.6\) dB and \(-29.1\) dB in sequence. The simulated axial ratios of the series-fed array antennas at 5.84 GHz are 2.35 dB, 2.91 dB, 2.65 dB, and 2.69 dB in the same sequence. The designs of individual array antennas for each beam tilting angle are optimized for the low AR level required to achieve CP at the tilted angle. Figure 8 shows simulated RHCP realized gain patterns for \(W_{2}\) values at 5.84 GHz in the \(\phi\) = \(90^{\circ}\) plane, delineating the performance characteristics of two linear array antennas with a varying number of the proposed antenna's unit cells. The \(1\times 12\) series-fed array antennas shown in Figure 8a feature a sharper main lobe with higher gain and lower sidelobe levels compared to the \(1\times 6\) series-fed array displayed in Figure 8b. As the gain increases, the radiation pattern of the \(1\times 12\) series-fed array exhibits a narrower beamwidth than the  
Figure 7: Simulated results for different \(W_{2}\): (**a**) phase of the transmission coefficient of the unit cell, (**b**) RHCP realized gain patterns of the series-fed antennas at 5.84 GHz, in \(\phi\) = \(90^{\circ}\) plane, (**c**) reflection coefficient of the series-fed antennas, and (**d**) axial ratio of the series-fed antennas at each beam tilting angle. \(1\times 6\) series-fed array. Specifically, for the largest tilted angle at \(W_{2}=2.9\) mm, the HPBW for the \(1\times 12\) series-fed array is \(16.3^{\circ}\), while the \(1\times 6\) series-fed array has a HPBW of \(26.5^{\circ}\), resulting in a difference of \(10.2^{\circ}\).
# A Machine Learning Method to Estimate Reference Evapotranspiration Using Soil Moisture Sensors
## 1 Introduction
The advent of unmanned aerial vehicles (UAVs) offers an opportunity to develop remote sensing-based methodologies for precision irrigation [26; 27]; they are more affordable than the costly systems based on manned aircrafts, and they provide higher spatial and temporal resolutions than those normally offered by satellites. Various sources of remotely sensed imagery, with differences in spectral, spatial, radioactive, and temporal characteristics, are applied to different purposes of vegetation mapping [28]. Soil moisture sensors are also used to measure the content of water in the soil and provide an estimation of ETc. For example, [PERSON] et al. [29] applied two different types of sensors based on time-domain reflectometry and capacitance, to estimate the actual evapotranspiration of a greenhouse crop of chili peppers. The final purpose was to reduce the amount of water needed, achieving a reduction of 30%. Other works used soil moisture sensors as a direct way to define irrigation decisions, for example, in crops of tomato [30], turfgrass [31], citrus orchards [32], and other kinds of vegetables [33]. All these facts suggest that it is recommended to combine the FAO-56 methodology with other techniques based on remote images and measurements of the soil water state [34]. Efforts should focus on developing new methods that are more robust, reliable, and sustainable [35; 36]. In this paper, the feasibility of estimating ETo using remote sensing techniques based on soil moisture sensors is analyzed. The experiment was performed in a plot in the southeast of Spain, which is an arid zone with a great shortage of water. The proposed methodology integrates different types of inexpensive sensors: meteorological data (daily temperature and rainfall), soil moisture sensors, and irrigation volumes. In order to estimate ETo from the sensor data with high accuracy, a comparison of some advanced pattern recognition techniques is presented. The results of these models are analyzed in detail, selecting the most accurate algorithm. Finally, this estimation of ETo is integrated with an existing methodology for the computation of Kc using remote image sensing [37; 38; 39], thereby obtaining the daily water balance to adopt the most adequate irrigation decision.
# Pipeline Leakage localization Based on FBG Hoop Strain Sensors Combined with BP Neural Network
## 4 Leakage Localization Based on BP Neural Network
### Method Validation
The work detailed in this paper opens the door to many potential avenues of research for leakage detection in pipelines. Additional pipeline leakage experiments or even real pipeline applications, including buried pipelines, overhead pipelines and even subsea pipelines, still need to be conducted to evaluate the performance of the neural network using hoop strain variations. Another possible next step for this research is the transition from the leakage detection and localization of single pipelines to the more general case of a branched network of pipelines.
# An NDN Cache Management for MEC
###### Abstract  
To enhance network performance, the named data networking architecture (NDN) caches data-packets in the network nodes on a downstream network path. Then it uses such cached requested data-packets to respond to new request-packets. Hence, a cache management scheme (CMS) is the essential point of NDN. CMS generally considers two main factors. One is a short response time and the other is storage efficiency. To rapidly respond to requests, CMS generally tries to cache data-packets near users as much as possible. To efficiently manage storage, it uses the popularity of the data. That is, proportionally to the popularity of the data, it increases the number of nodes caching data-packets and manages the lifetime of caches. However, few data objects are as popular as many users globally enjoy in the real world. Hence, if the assumptions about content- usage are practically changed, CMS can waste cache storage and not significantly improve network efficiency. We show that many caches have expired and are not used at all. To improve such inefficiency of CMS, this paper propose to simultaneously apply two cache decision factors, the expected frequency of a cache hit and the popularity of data. That is, it proposes to gradually cache transmitted data in nodes in which their expected cache-usage frequency is relatively high. To show the effectiveness of our proposal, we implement LdC (a limited domain cache policy) and evaluate the performance of LdC. The evaluation result shows that it can enhance the cache-storage efficiency by up to 65% compared with existing CMS without degrading the network efficiency.  
P2P; MEC; ICN; NDN; cache management scheme +
Footnote †: journal: Applied  
Article An NDN Cache Management for MEC
# Susceptibility of _Staphylococcus epidermidis_ to Argon Cold Plasma Jet by Oxygen Admixture
###### Abstract  
Cold atmospheric pressure sterilization is one of the nominated and efficient techniques to prevent the spread of diseases. Reactive species such as O and OH and other radicals play a major role in the mechanism of plasma sterilization. Therefore, in this work, oxygen was mixed with different parentage from (0.2 to 1.2%) to argon to enhance the generation of the reactive species and increase the argon atmospheric pressure plasma sterilization efficacy. The emission spectra from the jet increase the radiole line intensities by increasing the percentage admixture of O\({}_{2}\) with the argon gas to reach a maximum power at 0.8; then, it gradually decreases with a higher O\({}^{2}\) percentage. The OH band intensity decreases with increasing the admixture of O\({}_{2}\). The jet with different O\({}_{2}\) percentages was tested against Gram-positive _S. epidermidis_, which is the causal agent of nosocomial infections. The maximum reduction in colony-forming units (CFU) was observed at 0.2% O\({}_{2}\). No bacterial growth was observed at the later concentration applied for 8 min and the same case was detected at 0.4% O\({}_{2}\) applied to 16 min.  
cold plasma; argon; _Staphylococcus epidermidis_; bacterial susceptibility
# Security Risk Analysis of LoRaWAN and Future Directions
## 5 Security Threat and Risk Assessment of LoRaWAN v1.1
### LoRaWAN v1.1 Threat Catalog
#### 5.2.8. Rogue End-Device Attack  
To be part of the network, an end-device needs access to key materials that should not be accessible to malicious users. One way to do this is by capturing a device and replacing its firmware such that it reuses key materials in the captured device (as discussed in physical-capture-attack, refer Section 5.2.5). End-devices are data sources and are not authorized to reach information at servers. Therefore, any rogue end-device with legitimate authentication information will not able to access or leak data from the network. The most harm can be done by injecting false data to the application server.  
End-devices can also be exploited by the attackers to be used as jammers in the network. This might cause the LoRaWAN network to be not available for legitimate end-devices (DoS). However, this will be a restricted area in the vicinity of the Rogue end-device, and the rest of the network continues regular operation.  
Rogue end-devices can be also used to perform replay attacks (refer to Section 5.2.11). Packets being transmitted by the neighbors can be captured and replayed later on, which generally will be detectable due to the use of different nonce values (e.g., DevNonce, JoinNonce). However, this might cause waste of available resources in the network and decrease the availability of the \(GW\) for the legitimate end-devices.
###### Abstract  
This study examines the usefulness of both geometric and volumetric measurements of orbital soft tissues on CT scans to provide quantitative diagnostic guidance in image reading of thyroid eye disease (TED). Computed tomography (CT) images were obtained from 92 orbits and were classified as impaired motility (TED-IM) and normal motility (TED-NM). The TED-IM group was further divided into dysthyroid optic neuropathy (DON) and non-DON groups. There were 5 volumetric, 2 angular, and 3 ratio parameter measurements acquired from CT images to examine their feasibility in TED classification. We found that the mean volumes of extraocular muscle and retroorbital fat and their ratio to the orbital volume were significantly different between the two motility groups. The mean ratio of extraocular muscle volume in orbital apex and orbital apex volume (EMV-OA/OAV) was significantly larger in DON than non-DON patients (\(p<0.05\)). The population distribution among TED-NM, non-DON, and DON groups significantly varied for different angles between the optic nerve and medial rectus and lateral rectus. In conclusion, geometric and volumetric measurements using CT scans help to quantitatively classify TED.  
thyroid eye disease; computed tomography; dystrophyoid optic neuropathy; orbital structures; volumetric measurement; geometric measurement
## 4 Results
### Contrast Experiment
#### 4.2.2 Qualitative Comparison  
This section primarily presents the experimental results of qualitative comparison, focusing on the visualization effects of four comparison methods. Figure 11a-d showcases four representative samples from the LEVIR-CD dataset, where different colors are used to distinguish error-detected change areas (FP) highlighted in red and no change areas (FN) highlighted in green, aiming to enhance visualization.  
Representative images from the dataset were carefully chosen and compared visually. The method introduced in this paper clearly shows fewer false boundary detections in the change region and effectively identifies change-intensive regions. Among the four methods compared, the proposed method exhibits the lowest rates of missed and false detections in the detection area, indicating its superior accuracy. Overall, the results highlight that  
Figure 11: Visualizations of different methods in the sample tested on the LEVIR-CD dataset. Rows (**a–d**) showcase four representative samples from the dataset. The first column is the label of the samples. The 2 nd to 4 th columns are the results of this comparison method on the samples, and the last column is the results of ours.  
this method surpasses others in achieving optimal change detection performance on the LEVIR-CD dataset.
# Preprocessing for Multi-Dimensional Enhancement and Reconstruction in Neural Video Compression
## 2 Materials and Methods
### Multi-Dimensional Enhancement and Reconstruction (MDER)
Among them, RLFB is used to extract features through feature distillation. With the gradual stacking of RLFB, redundant information is effectively filtered and removed, and high-level semantic information that is critical to subsequent coding is retained. Second, Spatial Channel (SC) convolution integrates and refines features across spatial and channel dimensions, which improves the discrimination of features and enhances their discriminative qualities. Skip connections within MDFRNet enrich deep features, whichcompensates for potential information loss in high-level abstract features. Furthermore, these skip connections also mitigate vanishing gradients, improve signal backpropagation efficiency, and reduce computational resource utilization. Finally, a sub-pixel convolution layer [19] facilitates spatial up-sampling of the feature maps with minimal computation overhead. This method avoids artifacts and detail loss common in conventional interpolation techniques, ensuring that predictive outcomes retain semantic content and refined spatial details. **LOSS. ** Discrete Cosine Transform (DCT) is a widely used mathematical transformation that converts an image from the spatial domain to the frequency domain, which enables it to separate the low-frequency components of an image from its high-frequency components. However, DCT often results in the loss of critical high-frequency structural details, which are essential for image quality. To address this issue, we introduce the Adaptive Discrete Cosine Transform (ADCT) loss algorithm, an advance over the traditional Discrete Cosine Transform (DCT), which is utilized to incorporate adaptive threshold adjustment and detail-preserving quantization techniques. This algorithm effectively retains critical high-frequency details in images while achieving a high compression ratio. By reducing spatial redundancy in video content without compromising image quality, it ensures that compressed video closely resembles the original in terms of visual characteristics. When optimizing the MDER preprocessing method, we need to consider both the amount of video data and the visual quality of the video. In our paper, we optimize the parameters of the model by jointly minimizing the LDCT, the reconstruction loss function LR, and the perceptual loss function LP. Additionally, we integrated a Multi-Scale Structural Similarity Index (MS-SSIM) as a perceptual loss function to preserve luminance, contrast, and structural integrity in high-frequency image regions.
## 4 POD with Ambiguity Resolution
### Mathematical Models
#### 4.1.3 Double Difference Ambiguity Resolution  
With regard to the DD ambiguity, both receiver and satellite FCBs can be removed. The WL and NL DD ambiguities are theoretically integers according to Equations (5) and (6). The DD IF ambiguity can be reconstructed by:  
\[\Delta\
abla\overline{N}_{r_{1},r_{2},IF}^{s_{1},s_{2}}=\frac{f_{1}f_{2}}{f_{1 }^{2}-f_{2}^{2}}\Delta\
abla N_{r_{1},r_{2},WL}^{s_{1},s_{2}}+\frac{f_{1}}{f_{1 }+f_{2}}\Delta\
abla N_{r_{1},r_{2},NL}^{s_{1},s_{2}} \tag{10}\]  
where \(\Delta\
abla\) is double difference operator, \(r_{1}\) and \(r_{2}\) denote a receiver pair. The DD IF ambiguity then is also treated as a pseudo-observation to constrain the undifferenced IF ambiguities.  
\[\Delta\
abla\overline{N}_{r_{1},r_{2},IF}^{s_{1},s_{2}}=\overline{N}_{r_{2}, IF}^{s_{2}}-\overline{N}_{r_{2},IF}^{s_{1}}-\overline{N}_{r_{1},IF}^{s_{2}}+ \overline{N}_{r_{1},IF}^{s_{1},s_{2}},W_{r_{1},r_{2}}^{s_{1},s_{2}} \tag{11}\]  
\(W_{r_{1},r_{2}}^{s_{1},s_{2}}\) is the weight of the pseudo-observation. The precision of the DD and SD IF ambiguities is set to be \(1\times 10^{-4}\) L1 cycles (about 0.02 mm) to impose strong constraints.
_Applied_  
_sciences_  
_Article_  
**The Impact of Temperature on the Removal of Inorganic Contaminants Typical of Urban Stormwater**  
**[PERSON] 1,*\({}^{\text{\text{\tiny{*}}}}\) and [PERSON] 2**  
1 Faculty of Civil and Environmental Engineering, Warsaw University of Life Sciences--SGGW, Nowouvensynowska 166, 02-787 Warsaw, Poland  
2 Department of Chemical Engineering, The University of Melbourne, Parkville, VIC 3010, Australia; [EMAIL_ADDRESS]  
* Correspondence: [PERSON]_ADDRESS]; Tel.: +48-22-5935207 check for updates  
Received: 25 February 2019; Accepted: 21 March 2019; Published: 27 March 2019  
**Featured Application: (1) reactive material selection for implementation in stormwater infiltration devices; (2) design of the dimensions and maintenance frequency for treatment zones operated in cold regions.**  
**Abstract: Appropriate management of urban stormwater requires consideration of both water quantity, resulting from flood control requirements, and water quality, being a consequence of contaminant distribution via runoff water. This article focuses on the impact of temperature on the efficiency of stormwater treatment processes in permeable infiltration systems. Studies of the removal capacity of activated carbon, diatomic, halloysite, limestone sand and zeolite for select heavy metals (Cu and Zn) and biogenes (NH\({}_{4}\)-N and PO\({}_{4}\)-P) were performed in batch conditions at 3, 6, 10, 15, 22, 30 and 40 \({}^{\circ}\)C at low initial concentrations, and maximum sorption capacities determined at 3, 10, 22 and 40 \({}^{\circ}\)C. A decrease in temperature to 3 \({}^{\circ}\)C reduced the maximum sorption capacities (\(Q_{max}\)) of the applied materials in the range of 10% for diatomic uptake of PO\({}_{4}\)-P, to 46% for halloysite uptake of Cu. Only the value of \(Q_{max}\) for halloysite, limestone sand and diatomic for NH\({}_{4}\)-N uptake decreased slightly with temperature increase. A positive correlation was also observed for the equilibrium sorption (\(Q_{e}\)) of Cu and Zn for analyses performed at low concentrations (with the exception of Zn sorption on limestone sand). In turn, for biogenes a rising trend was observed only in the range of 3 \({}^{\circ}\)C to 22 \({}^{\circ}\)C, whereas further temperature increase caused a decrease of \(Q_{e}\). Temperature had the largest influence on the removal of copper and the smallest on the removal of phosphates. It was also observed that the impact of temperature on the process of phosphate removal on all materials and ammonium ions on all materials, with the exception of zeolite, was negligible.**  
**Keywords: runoff; heavy metals; nutrients; permeable treatment zone; removal efficiency**
## 3 Results
### BSN Promoted ROS Production and Inactivated STAT3 in HCC Cancer Cells  
Enzymatic reactions in cells released ROS. ROS increased apoptosis in cancer cells [26]. HepG2 and C3A cells treated with BSN (0-200 \(\upmu\)mol) for 30 min had dramatically increased intracellular ROS levels (Figure 3A). There was a significant increase in DCF fluorescence after treatment with BSN (200 \(\upmu\)mol) in both cells. An ROS inhibitor, NAC, was used to incubate HepG2 and C3a cells for 30 min with BSN (200 \(\upmu\)mol) to test whether ROS contributed to BSN-mediated cell death. The results showed that NAC stopped the production of ROS considerably (Figure 3B). By treating HepG2 and C3A cells with BSN and NAC, we measured the levels of \(p\)-STAT3 protein to observe whether ROS was involved in STAT3 phosphorylation. Pre-treatment with NAC significantly reduced \(p\)-STAT3 levels and its downstream targets, such as Bcl-2 and caspase-3 caused by BSN (Figure 3B), suggesting that ROS hindered STAT3 activity in HepG2 and C3A cells. Notably, apoptosis was inhibited by NAC and BSN, and the cell death that had been mediated by BSN was reversed (Supplementary Figure S2C,D). Based on these findings, BSN caused intracellular ROS to be generated, leading to apoptotic cell death in HCC cells.  
Figure 3: In hepatic carcinoma cells, BSN induced apoptosis through ROS. **(A)** The ROS levels in HepG2 and C3A cells were measured after pre-treatment with NAC (N-acetylcysteine) (1 mM) for 1 h and then treated with BSN (0–200 \(\upmu\)mol for 2 h). **(B)** NAC (1 mM) for 1 h, followed by BSN (0 and 200 \(\upmu\)mol) for 4 h, and then STAT3, Bcl-2, caspase-3, and PARP activation for 48 h. The \(p\)-STAT3, Bcl-2, caspase-3, and PARP expressions were monitored by Western blotting. [PERSON]’s post hoc test was used in this study to analyze the data. \(p\) < 0.05 was considered significant. Graph Pad prism was used. Experiments were conducted in triplicate. Data are presented as the mean \(\pm\) SD. Furthermore, * \(p\) < 0.05 vs. control. # \(p\) < 0.05 vs. BSN treatment.