esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Compressed Earth Blocks Production and Curing  
The two soils were used to produce different batches of blocks: (i) fine-textured R1 CEBs (<2 mm) and coarse-textured R2 CEBs (<12.5 mm). Both batches underwent an identical production process. The mixtures were designed on a volumetric basis. The mixing process was executed manually, combining soil, water, and 5% volume of hydraulic lime for stabilisation. Initially, soil and lime were mixed dry to ensure a uniform distribution of the stabiliser. Water was gradually added until the desired consistency specified by the manufacturer was achieved. The resulting mixture was then placed in a single ram hydraulic press (Eco Maquinas, Sao Domingos, Brazil--Eco Master 7000 Turbo II) to create blocks with standard dimensions of 300 mm \(\times\) 150 mm \(\times\) 80 mm (Figure 3). Please note that the blocks may vary in thickness by \(\pm\)7 mm.  
The produced blocks were subsequently stored in a sheltered area, covered with plastic sheets, and left to air dry. During the first week, they were hydrated twice a day to aid the maturation process. The blocks were tested at the age of 28 and 180 days.  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **R1 Soil** & **R2 Soil** & **Test Methods** & **Standards** \\  & **(\(\leq\)2.0 mm)** & **(\(\leq\)12.5 mm)** & **Test Methods** & **Standards** \\ \hline Consistency limits 1  & \(\text{w}_{\rm L}=29.5\%\), \(\text{w}_{\rm P}=18.5\%\), \(\text{IP}=11\%\) & \begin{tabular}{c} Atterberg limits \\ \end{tabular} & \begin{tabular}{c} NP-143 [18] \\ NP-83 [19] \\ \end{tabular} \\ Particle density 1  & \(\text{w}_{\rm L}=29.5\%\), \(\text{w}_{\rm P}=18.5\%\), \(\text{IP}=11\%\) & \begin{tabular}{c} Atterberg limits \\ \end{tabular} & \begin{tabular}{c} NP-143 [18] \\ NP-83 [19] \\ \end{tabular} \\ Specific heat (at 26.85 \({}^{\circ}\)C) 1,2 & \begin{tabular}{c} 883.93 / kg\({}^{\circ}\)C \\ \end{tabular} & \begin{tabular}{c} Diff. Scan. Calorim. \\ \end{tabular} & \begin{tabular}{c} ASTM E1269 [20] \\ \end{tabular} \\ Maximum dry density & 1.97 & g/cm\({}^{3}\) 2.01 & g/cm\({}^{3}\) & \
\begin{tabular}{c} Proctor test \\ \end{tabular} &
\begin{tabular}{c} E 197 (1966) [21] \\ \end{tabular} \\ Optimum water content & 12.2 & \% & 12.0 & \% & \\ Sand content & 15.34 & \% & 18.80 & \% & Sand equivalent test & NP EN933-8 (2002) [22] \\ Activity of clay minerals & 0.57 & mg/g & 0.67 & mg/g & Blue methylene test & NP EN933-9 (2002) [23] \\ Organic content & 3.90 & \% & 3.50 & \% & Loss on ignition test & ASTM D2974 [24] \\ \hline \end{tabular}
\end{table}
Table 1: Physical and geotechnical characteristics of the soil used.  
Figure 2: (a) Appearance of R1 soil (maximum particle size < 2 mm), and (b) appearance of R2 soil (maximum particle size < 12.5 mm).
# Degradation of Trace Organic Contaminants by a Membrane Distillation--Enzymatic Bioreactor
## 3 Results and Discussion  
### Overall Removal of TrOCs  
In theory, MD membranes can retain all but the volatile organic compounds. In this study, the concentration of non-volatile (pK\({}_{\rm H}\) > 9) TrOCs in the permeate of the MD-EMBR was below the limit of detection of GC/MS. This is consistent with the observation in a previous study, where an MD membrane was coupled with an activated sludge bioreactor [22]. On the other hand, the MD system achieved 90-99% removal of relatively volatile TrOCs having pK\({}_{\rm H}\) < 9 (Figure 2). This compares favorably to their previously reported moderate to high removal (54-99%) by a standalone MD system [29]. In particular, removal of octocylene (pK\({}_{\rm H}\) = 8.47), benzophenone (pK\({}_{\rm H}\) = 5.88), 4-tert-butylphenol (pK\({}_{\rm H}\) = 5.15), 4-tert-octylphenol (pK\({}_{\rm H}\) = 5.06) by the MD-EMBR was above 99%, compared to their 55-70% removal by the MD only [29]. These results suggest that the coupling of enzymatic degradation process to the MD system was favorable for achieving high TrOC removal.
# EGSDK-Net: Edge-Guided Stepwise Dual Kernel Update Network for Panoptic Segmentation
## 3 Method
### Real-Time Edge Guidance Module
After edge enhancement, \(R_{\text{S}}^{low}\) participates in the subsequent processes as described in Section 3.1. The other branch of RTEGM mainly supervises and continuously optimizes edge features through backpropagation. This branch consists solely of a \(1\times 1\) convolution, functioning as an edge prediction head, which produces a feature map with dimensions \(R^{1\times\text{ }H\times W}\). After activation with the sigmoid function, this output is sent to \(L^{edge}\) for supervision and guidance, which helps eliminate potential noise and enhance the quality of edge features. To provide accurate edge guidance without spending too much time in the generation process of edge ground truth, we use the widely used and validated Canny [26] to generate edge predictions for the training images. Although the Canny algorithm is a traditional edge detection method, it effectively classifies edge pixels based on the physical properties of the image and significantly reduces noise through processes such as filtering, non-maximum suppression, and double thresholding, thereby yielding stable and reliable edge detection results. Given its robustness, we consider that using the output of the Canny algorithm as the ground truth for \(L^{edge}\) is a valid and practical approach. Backpropagation directly affects the \(1\times 1\) convolution and the convolution processing \(R_{2}\) that is connected to it. The benefit of this approach is that backpropagation bypasses \(R_{mix}\), allowing the optimization to focus directly on the edge feature map instead of \(R_{mix}\), which is more similar to an edge attention map, thus improving edge prediction performance.
# A Trip Purpose Inference Method Considering the Origin and Destination of Shared Bicycles
## 7 Discussion  
When compared to global studies, the findings exhibit both alignment and innovation. For instance, [PERSON] et al. [19] utilized bike-sharing data and POI information to infer trip purposes and similarly reported notable accuracy improvements for low-frequency activities. [PERSON] et al. [1] validated the importance of temporal and spatial factors in trip purpose inference by integrating the gravity model with Bayesian rules. However, this study distinguishes itself by introducing the environmental factors at trip origins and incorporating time probability distributions, which further enhance the model's applicability and precision in more complex scenarios.  
Despite these advancements, certain limitations remain. The model's performance in predicting high-frequency purposes such as shopping and life services was less robust, potentially due to the greater variety and density of related POIs, which complicates the identification of critical features. Additionally, this study relied on a limited dataset that excluded other influential factors, such as weather conditions and socioeconomic attributes, which have been shown to significantly impact travel behavior in relevant American research [4]. These limitations highlight potential areas for further model refinement and expansion.  
Future studies could extend the applicability of the GMOD model to different cities and cultural contexts to explore its adaptability and performance across diverse settings. Incorporating dynamic data, such as real-time traffic flow and weather conditions, alongside individual attributes like age and gender, would likely improve the model's capability to handle complex scenarios. Furthermore, integrating multi-modal travel data, such as public transit card transactions and metro passenger flows, could verify the model's scalability for inferring purposes in multi-modal transportation systems.
## 2 Red-Colored Foods and Bioactive Compounds
### Biological Activities of Flavonoids
#### 2.1.2 Anthocyanins  
Anthocyanins are one of the most commonly used water-soluble phenolic compounds and principally represent natural pigments from red to purple. Anthocyanin is found in various tissues of plants, such as flowers, fruits, stems, and roots, and has proven to be protective against many cardiovascular risk factors [67; 68].  
Most types of anthocyanins are based on cyanidin, delphinidin, and pelargonidin along with methylation, methoxylation, hydroxylation, and glycosylation. The most important physical parameter of anthocyanins is color, which depends on pH. They turn red under acidic conditions and blue under basic conditions. The degree of hydroxylation, methylation and glycosylation also affects color [69; 70].  
In particular, berries such as cranberry, strawberry, and red raspberry are good sources of anthocyanins, and red apple, red currant, cherry, and plum are also rich in anthocyanins [71]. Cranberry flavonoids may have several distinct effects on the development of atherosclerosis. Monomers and oligomer flavonoids, for example, can be absorbed and metabolized and have postabsorptive effects on the development of atherosclerosis and cardiovascular diseases such as LDL protection against oxidation by arterial endothelial cells, arterial smooth muscle cells, and intimal macrophages; inhibition of the inflammatory response of these cells to modified LDL and direct effects on immune cells involved in the inflammatory process; vasodilation and improved blood flow; and inhibition of platelet aggregation and thrombosis [72].  
Additionally, [PERSON], [PERSON], et al. [26] revealed that cranberry reduces lipid oxidation and increases plasma antioxidant capacity in women with metabolic syndrome, and [PERSON], [PERSON], et al. [27] showed that cranberry improved several risk factors for cardiovascular disease in adults, including circulating triglycerides, CRP, glucose, insulin resistance, and diastolic blood pressure.  
Numerous in vitro and in vivo studies have suggested that strawberry supplementation reduces the risk of CVDs. In other animal models (obese and lean C57 BL/6 mice), strawberry supplementation decreased overall blood glucose concentrations independent of the content of dietary fat and reduced plasma CRP, supporting a potential protective effect against cardiovascular risk.  
Intervention studies have reported many cardiometabolic disease outcomes affected by cherry. [PERSON], [PERSON], et al. [29], [PERSON], [PERSON], et al. [30], [PERSON], [PERSON], et al. [31], and [PERSON], [PERSON], et al. [32] showed significantly lower levels of blood pressure, lipid-related markers, and adhesion molecules and evidence of cardiovascular-related outcomes (FMD, nitrate and nitrite, PRX1) after consumption of cherry. Short-term strawberry supplements improved the risk factors for selected atherosclerosis, including dyslipidemia and adhesion molecules in subjects with metabolic syndrome [34].
# Practical Performance Analysis of Interference in DSS System
## 4 DSS Interference and Solutions
### Buffer Setting  
For DSS neighbor interference, we can use the common buffer method to solve it, that is, set a buffer. Taking the 2.1 GHz intra-frequency networking environment as an example, the LTE of the DSS cell will cause strong interference to the NR of the neighbor DSS cell. If two circles of disturbing base stations near the disturbed base station are closed, the coverage of the area near the disturbed base station will be discontinuous. Therefore, eNodeBs in a non-2.1 GHz band (e.g., 1.8 GHz) can be considered to replace the base stations that need to be turned off to play the role of a buffer, thereby mitigating the intra-frequency interference in neighbors. The schematic diagram of buffer setting is shown in Figure 7. Points 1 to 6 are the test point in our paper. The darker the color, the stronger the interference.  
We conducted a simulation analysis for a buffer setting solution to mitigate the interference caused by LTE to NR downlink, and the results are shown in Figure 8.  
As can be seen from Figure 8, when the isolation of LTE increases, the rate of NR is getting higher and higher, indicating that the buffer has a significant mitigation effect on interference. When the LTE isolation is 15 dB, the downlink performance of NR can reach up to 32 Mbps. Compared with without buffer, the downlink performance of NR can be improved by 40-60%. Therefore, if the downlink interference level of LTE to NR is reduced, it is better to set the isolation of LTE to 15 dB or more. Considering the irregularity of the field network, it can be increased by 5 dB, that is, the isolation of 20 dB can be set, which is equivalent to the situation of closing two base stations in the field network.  
In Section 5, we conduct a field test analysis to verify the conclusions of the theoretical analysis of the interference mitigation effect produced by buffer setting.  
Figure 7: Schematic diagram of the buffer.
## 3 Result and Discussion  
### Analysis of Physicochemical Properties  
As shown in Table 1, L* and b* values increased significantly from 48.2 to 57.0 and from 5.28 to 10.25 (\(p<0.05\)), respectively. Although the a* value decreased in the early stage of LTS, it was not significantly changed by the end of LTS. Additionally, the moisture content of bacon decreased significantly from 69.9% to 39.2% (\(p<0.05\)) during LTS, which was similar to the results reported by [PERSON] et al. [23]. Textural parameters such as hardness, adhesion, chewiness, and elasticity of bacon samples also increased significantly during LTS compared to 0 d (\(p<0.05\)).  
The color and texture of bacon depends on many factors. [PERSON] et al. found that the degree of oxidation of myoglobin in meat significantly affected meat color, with meat color changing from bright red to brown as the degree of oxidation increased. [PERSON] et al. (2018). The considerable enhancement in L* and b* during LST (\(p<0.05\)) in this study indicates that myoglobin in bacon is exposed to oxygen in the air, resulting in a color change. Furthermore, studies have indicated that the texture of meat is influenced by changes in water holding capacity as well as the strength of intermolecular binding of side chains between proteins and the degree of protein hydrolysis [PERSON] et al. (2018). The results of the present study are comparable to those of previous studies, which have demonstrated that a reduction in the moisture content of bacon is accompanied by a significant increase in texture parameters (\(p<0.05\)).
# Testing an \"IoT\" Tide Gauge Network for Coastal Monitoring
## 2 IoT Tide Gauge Network Design
### Design of IoT-Enabled Tide Gauge  
The monitoring system architecture (see Figure 1) comprises a number (depending on the location) of individual tide gauges, all of which communicate with one or more base stations. The base stations then relay the data messages to the \"cloud\" on a regular basis. Once in the cloud infrastructure, the data can be pushed or picked up by other data servers for postprocessing. For example, the data could consist of 40-s averages of pressure data representing water level, and other statistics of the 10-Hz data, such as burst maximum, minimum and standard deviation, which can be used as a proxy for wave conditions.  
The IoT-enabled tide gauge developed here is based on the off-the-shelf Arduino MKR micro-controller. The controller is available with a variety of communications formats, including Sigfox (MKR FOX 1200), LoraWan (MKR WAN 1300), and GSM (MKR GSM 1400).  
Figure 1: Monitoring system architecture.  
For this project, we chose the MKR FOX 1200 as it has an established subscription-based backend communication infrastructure, and each unit comes with one year's free subscription. The cost of the MKR FOX 1200 controller is around \(\epsilon 40\).  
The GSM version was excluded because it was twice the price of the others and had relatively high running costs. The LoraWan and Sigfox controllers are very similar in characteristics and cost, but to use the MKR WAN 1300 requires access to a LoraWan base station.
# Review of Structural Health Monitoring Techniques in Pipeline and Wind Turbine Industries
## 3 Health Monitoring in Corrosion
### Point OFS for Corrosion  
It can be considered that point corrosion OFS is an optical version of corrosion coupons. At a particular section of optical fibers, the point OFS generally consists of coated sensing layers. Generally, the optical fibers are metallic films. It can be seen in Figure 6 that as there is corrosion of the metallic films at the ends of the fiber, there is a reduction in the reflected light, and at the other end of the fiber, this light is detected [84; 85]. On the other hand, there is a coat of Fe-C film over a particular section of the fiber, and accordingly, there is an increment in the transmission of light along the optical fiber as the corrosion of Fe increases [86]. The long-period grating (LPG) is an alternative method to design a point sensor that allows the interaction of light and the neighboring medium with the help of cladding modes. The periodicity of LPG (\(\Lambda\)) ranges from 100 to 1000 \(\mu\)m, and this is greater than the periodicity range of fiber Bragg grating (FBG), and light from the guided mode is coupled into the core, which then moves toward the forward propagating cladding modes at particular values of wavelengths. Due to this, there is an evident dip in the transmission spectrum, as can be seen in Figure 7. Resonant wavelengths show strong changes toward even smaller changes in the temperature and strain of the cladding modes [87; 88]. In a comparison between FBG and LPG, it is found that LPG exhibits higher  
Figure 4: Ultrasonic texting that can discriminate between internal and external mass loss.  
Figure 5: The principal of a magnetic flux leak sensor that can measure the flux passing through and interpret it to give meaningful results [83]. (**a**) A ferromagnetic material only has all the lines inside it. (**b**) Hall-effect sensor.  
magnitudes of spectral shifts and thus, owing to the larger values of periodicity, fabrication becomes simpler [87]. Various studies have been carried out that are focused on LPG sensors consisting of an Fe-C coat, and the studies have been carried out to observe the loss of mass due to corrosion [89; 90].
# Multi-Templates Based Robust Tracking for Robot Person-Following Tasks
## 3 Method  
### Framework  
Figure 2 presents the flow chart of our approach. The base tracker part is the common steps of Siamese-based trackers where for each frame; the features of the template image and search image are extracted using a shared-weight deep convolutional backbone. The two extracted features then cross-correlate and produce a score map that consists of the probabilities of similarity between the template and the search image. Usually, Siamese-based trackers employ non-maximum suppression to the scores and choose the corresponding regressed bounding box with the highest value as the tracking result, but these methods do not work well in some situations such as occlusion and appearance change.  
Figure 2: The framework of our approach. The base tracker part is the common framework of Siamese-based trackers. For each frame, the features of the template image and the search image are extracted using a shared-weight network. Then, a score map is generated by the cross-correlation of the two features. To further exploit the information from the score map, we take the scores as a whole and process them using our scene analysis module. The objects with highly similar responses are collected as negative templates. Next, we estimate the tracking reliability leveraging the outcomes of the SAM and collect confident tracking results as positive templates. Finally, the scores of the ground truth, negative, and positive are fused and the tracking box is regressed from the fused score map.  
To improve tracking robustness, we take the scores as a whole and further exploit the information provided by the score map using our scene analysis module (SAM). The SAM analyzes the score map by estimating the score densities and segmenting the scores into instance-aware clusters. The SAM provides two contributions: first, a tracking reliability criterion is proposed using the statistical characteristics of the score distribution. If the tracking is determined to be reliable, the tracking target is extracted and collected as positive templates. Second, because of the limitation of the backbone networks, objects that are similar to the tracking target also respond with high values in the score map, which strongly interferes with tracking accuracy. Since the SAM segments scores into instance-aware clusters and each cluster represents a potential tracking target, the targets except for those being tracked are determined as false positive targets and collected as negative templates.  
Finally, the score maps of the ground truth and negative and positive templates are fused together and the tracking box is regressed from the fused score map. The positive templates provide more recent information, enhancing the responses of the target-tracking. The negative templates are in charge of suppressing the interference due to similar objects.
# Evaluation of VoIP QoS Performance in Wireless Mesh Networks
###### Abstract  
The main focus of this research article is the evaluation of selected voice over Internet protocol (VoIP) solutions in wireless mesh network (WMN) scenarios. While WMNs have self-healing, self-forming, and dynamic topology features, they still pose challenges for the implementation of multimedia applications such as voice in various scenarios. Therefore, various solutions to make WMN more suitable for VoIP application have been proposed in the scientific literature. In this work, we have extensively explored a set of applicable scenarios by conducting experiments by means of a network simulator. The following scenarios were selected as the most representatives for performance evaluation: first responders, flooded village, remote village, and platoon deployment. Each selected scenario has been studied under six sub-scenarios corresponding to various combinations of the IEEE 802.11g, 802.11n, 802.11s, and 802.11e standards; the G.711 and G.729 codecs; and the ad hoc on demand distance vector (AODV) and hybrid wireless mesh protocol (HWMP) routing protocols. The results in terms of quality of service (measured with the mean opinion score rating scale), supported by the analysis of delay, jitter and packet loss, show that 802.11g integration with both VoIP codecs and AODV routing protocol results in better VoIP performance as compared to most other scenarios. In case of 802.11g integration with 802.11s, VoIP performance decreases as compared to the other sub-scenarios without 802.11s. The results also show that 802.11n integration with 802.11e decreases VoIP performance in larger deployments. We conclude the paper with some recommendations in terms of combinations of those standards and protocols with a view to achieve a higher quality of service for the given scenarios.  
wireless network; VoIP communication; mesh; QoS; MOS; delay; jitter; packet loss Article
## 4 Biosensor Application of Ramified or Dendritic Electrodeposited Structures
### Nanostructures Described as 'Flower-Like', Irregular, of Unusual Morphology
Electrodeposition from 6.8-mM HAuCl\({}_{4}\) and one mM of Pb(CH\({}_{3}\)COO)\({}_{2}\) resulted in the formation of nanospikes, which were characterized by their spacing, height, cap radius, base radius, surface density, and roughness. Increasing deposition time at 0.05 V (versus Ag/AgCl) over 260 s, 540 s, 720 s, and 900 s resulted in increases in all of the geometric parameters, but a decrease in the surface density. At the longest deposition time, the nanospikes were 555 \(\pm\) 214 nm in height and had a 103 \(\pm\) 82 cap radius. For the nanospikes deposited at a time of 540 s, a near 90% efficiency for killing _P. Aeurunginosa_ bacteria was observed.