esa-sceva/satcom-chunk-collection huggingface dataset:
# DPSIR Model Applied to the Remediation of Contaminated Sites. A Case Study: Mar Piccolo of Taranto
## 6 States
### Marine Sediment Characterization
PAH levels were higher than the instrument detection limit in sites 1, 7, 8, 10, 13, 14, 15, 16, 17, 18, and 19, and sites 4 and 6 for PCBs. Additionally, for organic compounds, concentrations followed a decreasing trend with sampling depth, excluding the borehole no. 7. PAHs exceed limits in several areas (i.e., S01, S02, S04, S05, S06, S07, S015, S016, and S18), reaching the maximum values of 18,000 \(\upmu\)g/kg d.w. (dry weight) and 36,000 \(\upmu\)g/kg d.w., respectively in sample S06 and S05 [45]. Furthermore, the data obtained from chemical characterization and bioassays were integrated within a Weight of Evidence (WOE) [47; 48] model in an overall quantitative risk assessment. Figure 9 shows the distributions of the Integrated Hazard Index (IHI) [49] at various depths below the seafloor. In the top layer, the integration of data identified the highest risk in areas near the naval arsenal (i.e., sites 4, 6, 7) and the central area (i.e., sites 5, 11, 16, 19). Additionally, the sites 10, 12, 14, and 19 are close to the areas of mussel-culture and fishery activities, raising concerns about environmental and health issues. However, the class of hazard tends to decrease with depth, except for stations S03 and S09. This could be due to the hydrodynamic conditions of the Navigable Channel and Citro Citterlo water spring. Concerning eco-toxicological analyses, [PERSON] et al. [50] applied a multi-organism and multi-endpoint approach, exposing organisms from different trophic levels to elutriate and whole contaminated sediment. The battery of bioassays considered consisted of a microalgal growth inhibition test (_Dunaliella tertiolecta_), acute and sublethal assays on crustaceans' larvae and juveniles, and rotifers (_Amphibalanus amplititrie_, _Artemia salina_, _Corophilum insidiosum_ and _Brachionus plicatilis_), and embryotoxicity test on echinoderms (_Paracentrotus lividus_). Despite the high levels of sediment contamination, an unexpectedly very low toxic effect was observed in the biological compartment, even considering the sublethal end-point (larval swimming speed alteration). In line with the findings of [PERSON] et al., [PERSON] et al. [46] performed toxicity bioassays on _Vibrio fischeri_, _algae Phaedactyllum tricornutum_, and shellfish _Mytilus galloprovincialis_. Even in this case, the obtained biological response unexpectedly highlighted that the level of contamination seems not to affect the biological compartment in a considerable manner. Figure 9: Area of investigation for the First Bay in the Mar Piccolo of Taranto in the sampling campaign in 2016 and spatial distributions of the Integrated Hazard Index (IHI): (**a**) 0.0–1.5 m below seafloor; (**b**) 1.5–3.0 m below seafloor. (Class of hazard: • Absent (IHI \(<\) 20); • Sib Tight (20 \(<\) IHI \(<\) 40); • Moderate (40 \(<\) IHI \(<\) 60); • Major (60 \(<\) IHI \(<\) 80); • Severe (IHI \(>\) 80). In red, the mussel-culture areas [46]).
## 2 Data Processing and Network Description
### Relation Network
#### 2.3.1 Network Structure  
The main distinction of the relation network from other metric learning models lies in its ability to compute similarity scores between each test sample and each class by learning an adjustable similarity metric. This enables more efficient and accurate classification. The relation network consists of two core components: the feature embedding module and the relation metric module.  
The feature embedding module is responsible for mapping signal samples into a feature metric space. This mapping process aids in extracting key features from TSSG, providing richer information for subsequent relation metric computation. Then, the relation network concatenates the extracted feature vectors of the test signal sample with the support set. Subsequently, the relation metric module computes similarity scores between the test signal and each class's signal from the support set. Based on these similarity scores, the relation network can classify the test signal sample.
# Optimal Deployment of Container Weighing Equipment: Models and Properties
## 1 Introduction
### Literature Review
The IMO has addressed the safety of containerized maritime transport within its legal framework [26], specifically through the International Convention for the Safety of Life at Sea (SOLAS Convention) [27]. In September 2012, the 17 th IMO DSC meeting [28] revised SOLAS VI/5 and introduced a draft amendment to SOLAS VI/2 (verification of the gross mass of a packed container) [29]. The amendment also requires cargo owners to ensure that the verified container weight is accurately documented in the transport papers. Subsequently, in 2014, the IMO added the requirement for weight verification of loaded containers prior to loading on board the ship to the SOLAS Convention, resulting in the SOLAS VI/2 (Cargo Information) Amendment (Revised SOLAS Convention), which came into effect on 1 July 2016, through a resolution adopted by the MSC 94 th Meeting [30]. Some researchers have also analyzed the problem of overweight containers. [PERSON] [31] discussed the dangers associated with overweight containers and how this issue affects maritime safety. [PERSON] et al. [32] conducted a comprehensive assessment of the verified gross mass (VGM) implementation at Tg. Priok Port in 2017, utilizing a qualitative descriptive methodology. Their findings revealed significant disparities between the pre- and post-regulation periods, highlighting that the enforcement of VGM has notably influenced the port charges associated with shipping activities at Tg. Priok Port. [PERSON] et al. [33] gathered input from 50 stakeholders, then performed a content analysis to inductively build a case study examining the influences of port community systems (PCS) on the implementation of the VGM regulations. [PERSON] and [PERSON] [34] examined the legal implications of container security, with a particular focus on the issue of liability in the event of a security failure. From reviewing these existing studies, it can be seen that optimizing the weighing plans of containers has not been studied. This involves making strategic decisions practically about how to allocate the number of weighing machines in each port and how to determine the optimal locations for weighing containers. Therefore, this paper aims to address this research gap by proposing a mathematical programming model that aims to maximize the safety benefits of weighing containers to the shipping system. To the best of our knowledge, this is the first study to present a mathematical programming model that optimizes container weighing decisions. We aim to maximize the benefits of weighing containers to the safety of the maritime system. Furthermore, we analyzed the properties of this model in detail and designed computational experiments to obtain managerial insights.
## 4 Monitoring and Measurement Results and Analysis of the Bifurcated Tunnel Construction Process
### Analysis and Evaluation of the Reasonableness of Construction Methods  
The reasonableness of the construction of the large cross-section tunnel can be verified by determining whether the tunnel deformation is within the allowable range [29]. The allowable values for crown sinking and displacement span ratio in highway tunnels can be calculated using the Pusch formula and the French standards for crown sinking. The formula for calculating the allowable crown sinking value \(\delta\) is as follows:  
\[\delta=12\frac{b_{0}}{f^{1.5}},\]  
where \(f\) and \(b_{0}\) denote Pratt's coefficient and the cavity span, respectively.  
Table 2 lists the maximum crown sinking displacement and allowable values at the monitoring sections of the Liantang bifurcation tunnel. The statistical analysis shows that both the crown sinking and convergence displacement results are smaller than the allowable displacements and are within the safe allowable range. The monitoring data validates the rationality of the tunnel construction method.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Excavate Section**} & **Monitoring** & **Cumulative** & \multirow{2}{*}{\begin{tabular}{c} **Ratio of** \\ **Displacement**/**mm** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **Alllowable** \\ **Displacement** \\ **to Span/\%** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Robustness** \\ **Displacement/mm** \\ \end{tabular} } \\  & & & & & **Factor (\(f\))** \\ \hline two-lane tunnel & K1+870 & 8.5 & 0.067 & 18.09 & 4.14 \\ five-lane tunnel & K1+890 & 23.7 & 0.091 & 42.74 & 4.14 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Statistical analysis of extremum and admissible value of settlement.  
Figure 22: Pressure–time history curve between the initial support and the second lining at five-lane K1+890.
## 3 Results
### Binding of 2-FAL to MIP by Batch Equilibration  
Batch equilibration is the most widely used method to characterize the sorption of a molecule on a solid. Here it has been applied to obtain the sorption isotherms in the concentration range from 5 \(\times\) 10\({}^{-5}\) M to 90 \(\times\) 10\({}^{-5}\) M. This is the range in which UV measurement at 275 nm can be used for 2-FAL concentration determination. Typical binding isotherms of 2-FAL on MIP-2 FAL and on the corresponding NIP are reported in Figure 1.  
It can be seen that a linear relationship between the bound ([RA]) and free ([A]) concentration is obtained approximately only up to 4 \(\times\) 10\({}^{-4}\) M, while the slope decreases at higher concentration indicating that the polymer is approaching saturation [29]. Practically the same curve is obtained for MIP and NIP, which is an evidence that at these concentration levels the adsorption is not driven by the interaction with the imprinted sites. By applying the Langmuir model (Equation (2)) in the Scatchard form (Equation (3)), a single straight line is obtained indicating that only one kind of binding sites can be detected in the considered concentration range. \(K_{\rm A}\) has been found to be 3.9(7) \(\times\)10\({}^{2}\) M\({}^{-1}\) with a maximum adsorbable amount (\({}_{\rm CR}\)) of 0.053(20) mmol/gMIP. Because the prevailing adsorption mechanism seems not to involve imprinted sites, it is expected that furanic compounds with molecular structure similar to that of 2-FAL are adsorbed as well. Actually, it has been found that furanic compounds as 5-hydroxymethyl-2-furaldehyde (HMF) and furfuryl alcohol (FA) are adsorbed on MIP-2 FAL. At the considered concentration, i.e., around 8 \(\times\) 10\({}^{-4}\) M, the bound-to-free  
Figure 1: Binding isotherms of 2-FAL on MIP and NIP from water, at 75 mL\({}_{\rm sol}\)/gMIP.  
ratio (B/F, expressed as amount of polymer bound and solution free compound at equilibrium) is 0.21 for 2-FAL, 0.12 for HMF and 0.58 for FA. Notice that one non-template molecule as FA has a higher bound-to-free ratio than the template 2-FAL, which shows that interactions different from those with the imprinted sites prevail at the considered conditions [40]. It can be guessed that the carboxylic groups from MAA present at the polymer surface not structured in any imprinted site are responsible for the binding of the considered furanic compounds.
# Design of True Time Delay Millimeter Wave Beamformers for 5G Multibeam Phased Arrays
###### Abstract  
Millimeter wave (mm-Wave) technology is likely the key enabler of 5G and early 6G wireless systems. The high throughput, high capacity, and low latency that can be achieved, when mm-Waves are utilized, makes them the most promising backhaul as well as fronthaul solutions for the communication between small cells and base stations or between base stations and the gateway. Depending on the channel properties different communication systems (e.g., beamforming and MIMO) can accordingly offer the best solution. In this work, our goal is to design millimeter wave beamformers for switched beam phased arrays as hybrid beamforming stages. Specifically, three different analog beamforming techniques for the frequency range of 27-33 GHz are presented. First, a novel compact multilayer Blass matrix is proposed. Second, a modified dummy-ports free, highly efficient Rotman lens is introduced. Finally, a three-layer true-time-delay tree topology inspired by microwave photonics is presented.  
5G; early 6G; hybrid beamforming networks; millimeter waves; switched beam phased arrays; Blass matrix; Rotman lens; tree beamformer +
Footnote †: journal: Electronics Letters
# Three-Dimensional Dead-Reckoning Based on Lie Theory for Overcoming Approximation Errors
## 4 Experiments and Results
### Speed Results  
The calculated velocity errors in the ENU coordinate frame were compared with the previously used DR errors. The reference velocity was obtained using the speed output from the GPS. Figures 16-23 graphically compare the errors in velocity prediction based on Table 3. Similar to the position results, the proposed method shows mostly smaller or similar results in mean error, standard deviation, and RMS values compared to the previously widely used DR. Additionally, the proposed method shows improved results in terms of velocity prediction accuracy as the data reception cycle becomes longer. Unlike the previously widely used DR, the proposed method performs accurate calculations in nonlinear space. However, the previously widely used DR considers attitude as a variable in linear space. Therefore, the previously widely used DR employs typical arithmetic operations. These operations lead to approximation errors. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Stat**} & \multirow{2}{*}{**Ti.**} & \multirow{2}{*}{**Md.**} & \multicolumn{5}{c}{**Distance Error (m)**} \\ \cline{4-7}  & & & **(I)** & **(2)** & **(3)** & **(4)** \\ \hline \multirow{8}{*}{Mn} & \multirow{2}{*}{0.1 (s)} & Conv. DR & 57.7120 & 26.1833 & 17.1059 (B) & 67.9617 (W) \\  & & Proposed & 57.6346 & 26.1902 & 17.2910 & 58.1539 \\  & & Conv. DR & 88.5603 & 82.2978 & 46.8934 & 255.4870 (W) \\  & & Proposed & 59.5332 & 37.0723 & 21.3908 (B) & 95.7408 \\  & & Conv. DR & 396.2126 & 355.2294 & 107.9019 & 433.2224 (W) \\  & & Proposed & 223.9200 & 76.5151 & 56.8564 (B) & 146.5781 \\ \hline \multirow{8}{*}{Std} & \multirow{2}{*}{0.1 (s)} & Conv. DR & 23.0549 & 12.2213 & 10.0197 (B) & 29.9314 (W) \\  & & Proposed & 23.0563 & 12.9547 & 10.3032 & 19.1637 \\ \cline{1-1}  & & Conv. DR & 44.6968 & 71.2740 & 42.1647 & 194.0085 (W) \\ \cline{1-1}  & & Proposed & 28.8588 & 27.1759 & 11.7212 (B) & 60.7879 \\ \cline{1-1}  & & Conv. DR & 236.6208 & 245.9355 & 94.0146 & 305.5643 (W) \\ \cline{1-1}  & & Proposed & 125.8985 & 50.2558 & 25.2438 (B) & 78.2221 \\ \hline \multirow{8}{*}{RMS} & \multirow{2}{*}{0.1 (s)} & Conv. DR & 62.1466 & 28.8951 & 19.8243 (B) & 74.2609 (W) \\ \cline{1-1}  & & Proposed & 62.0753 & 29.2190 & 20.1280 & 61.2301 \\ \cline{1-1}  & & Conv. DR & 99.2005 & 108.8710 & 63.0623 & 320.8004 (W) \\ \cline{1-1}  & & Proposed & 66.1591 & 45.9662 & 24.3917 (B) & 113.4084 \\ \cline{1-1}  & & Conv. DR & 461.4909 & 432.0558 & 143.1139 & 530.1427 (W) \\ \cline{1-1}  & & Proposed & 256.8863 & 91.5435 & 62.2085 (B) & 166.1441 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Analysis of the distance error in the ENU coordinate frame.
# Adjustable Structure for Feedback Active Headest System Using the Virtual Microphone Method
###### Abstract
These variations influence the performance of VS methods to varying degrees [19; 23]. In addition, all of the aforementioned studies have only been verified to be effective for selected participants. When the targets were switched to various users who have not been measured in advance, their performance was not quantitatively evaluated. To solve the above problems, this paper presents a multichannel feedback active headrest system in combination with the VMM and a headrest structure that can be manually adjusted by the users. The secondary loudspeakers and the corresponding microphone are integrated into a single unit in the proposed headrest structure. The user can freely adapt each unit to maintain the relative distances between the ears and each unit constant. A series of real-time experiments were conducted to demonstrate the attenuation performance of the proposed active headrest system with respect to multi-sinusoidal machine noise. The necessity and superiority of the proposed headrest structure over two conventional structures [4; 22] was confirmed using the three VS methods. This validation considered the variations in the distances from the secondary loudspeakers to the ears and the case of head movement as well. Subsequently, comparisons were carried out between the VS methods to deal with primary source variations. In addition, the applicability of the three VS methods when utilizing the proposed adjustable headrest structure was verified through the aforementioned experiments. Furthermore, the robustness of the proposed system in response to user variations was validated by involving 10 volunteers of various statures using comparisons with different structures. The remainder of this paper proceeds as follows. Section 2 describes the proposed adjustable structure. The adaptive feedback algorithm and the VS methods are briefly analyzed in Section 3. The experimental setup is explained in Section 4. In Section 5, the noise cancellation performance and robustness of the proposed active headrest system are validated through numerous experiments. Finally, Section 6 concludes the paper.
## 2 Materials and Methods  
The 40 plaster models (maximly and mandibular jaws) with a different degree of crowding were selected among 313 dental models of subjects undergoing orthodontic treatment in private practice from March 2016 to August 2019.  
Dental crowding was preliminary assessed by a specialist clinician (L.R.) and five groups were defined following the Discrepancy Index of the American Board of Orthodontists (ABO): from \(\geq\)0 to \(\leq\)1 mm = group \"A\"; from \(>\)1 to \(\leq\)3 = mm group \"B\"; from \(>\)3 to \(\leq\)5 mm = group \"C\"; from \(>\)5 to \(\leq\)7 mm = group \"D\"; and \(>\)7 mm = group \"E\". Finally, 8 models were randomly recruited from each group by using web-based software (www.randomizer.org).  
A power calculation was preliminary performed using a specific research toolkit (DSS Research, Washington, USA), which indicated that a minimum of 6 models were necessary for each subgroup to register 0.3 mm of difference between the analogic and digital measurements, setting the confidence level at 95% and the Beta error at 15%.  
The inclusion criteria were selected as follow: patient's age under 16 years old, no previous orthodontic treatment, fully erupted maxillary and mandibular teeth, and LII \(>\) 4 mm.  
The exclusion criteria were selected as follow: presence of missing teeth or agenesis (except for third molar), form anomaly, interproximal restorations and unrestored carious cavities.  
After collecting the plaster models, they were blindly coded for de-identification process, scanned using a 3D laser scanner (3 Shape D500, 3 Shape A/S, Copenaghen, Denmark) and then rendered into a 3D stereolitographic digital model (.stl) through specific software (ScanIttm Orthodontics, 3 Shape A/S, Copenaghen, Denmark). Then, both the digital and plaster models were collected together in order to perform the measurements. Afterwards, Little's index was calculated according to the ABO's guidelines [8].  
In this contest, manual measurements were performed on dental casts by using a digital caliper (Figure 1) and registered to the nearest 0.1 mm [1; 15].  
On the other hand, digital measurements were carried out on digital models using a specific software from a 3D scanner manufacturer (OrthoAnalyzerTM 3D software, version 1.6.1.6, 3 Shape A/S, Copenhagen, Denmark) on a calibrated flat 22\" monitor with a mouse, which were both set and checked (Figure 2).  
In order to assess the intra- and inter-operator accuracy and reliability, analogic and digital measurements were repeated after two weeks by two specialized operators ([PERSON] and [PERSON]) working independently with 5 years of orthodontic experience [9; 16; 17]. Only seven sets of casts per day were measured, in order to avoid eye fatigue and to minimize the possibility of subjective errors.
# Native Smartphone Single- and Dual-Frequency GNSS-PPP/IMU Solution in Real-World Driving Scenarios
## 4 Results Analysis  
In Section 4.1, the dead-reckoning performance behaviour is first demonstrated, followed in Section 4.2 by the assessment and analysis of proposed processing strategies. The findings are then further summarised with statistics presented in Section 4.3. Finally, in Section 4.4, single- and dual-frequency PPP/IMU solutions under different scenarios are investigated.
## 3 Results and Discussion
### Kakadu Plum Suppress Elevated Levels of ROS in HepG2 Cells  
In normal conditions, ROS generation and their destruction by the cellular antioxidant system are balanced in our bodies. Alcohol administration causes oxidative stress along with an accumulation of intracellular ROS in hepatic cells, which play a vital role in the development of alcoholic liver disease [54]. In this study, alcohol exposure increased intracellular ROS generation in HEpG2 cells.  
The Kakadu plum (_T.ferdinandiana_) exerts potential ROS-scavenging activity in Caco-2 and KERTr cells [55]. To examine whether the protective ability of KKD is associated with EtOH metabolism-mediated ROS formation in the hepatic cell culture models, we further quantified the cellular levels of ROS in the HepG2 cells. The ratio of NADH/NAD+ can be drastically changed by ethanol metabolism causing the ROS formation. As indicated in (Figure 5), 4% EtOH notably increased ROS production compared to the control. As expected, the ethanol-mediated intracellular accumulation of ROS in the cells was abolished in a dose-dependent manner by KKD-NT and KKD-WA treatment. It is known that antioxidants can neutralize free radicals by giving up some of their own electrons and our sample has potential antioxidant properties. These results provide evidence of the inhibitory effect of KKD-NT and KKD-WA on ethanol-induced ROS production because of the higher antioxidant capacity of the fruits. Overall, the results show that KKD-NT inhibits ROS production in cells more significantly than KKD-WA as the antioxidant activity of KKD-NT exceeds KKD-WA.  
Figure 4: Measurement of cell viability of HepG2 following ethanol treatment. (**a**) Cells were treated with selected concentration of ethanol (EtOH) for 24 h; (**b**) cells were incubated with indicated concentrations of KKD-NT and KKD-WA in the presence of EtOH for 24 h. Cell survival percentage was assessed using MTT assay as mentioned in materials and methods section. Values are means of three independent experiments \(\pm\) SD (\(n\) = 3 \(\#\)\(p\) < 0.05, \(\#\)\(p\) < 0.01, \(\#\)\(\#\)\(p\) < 0.001 indicate differences from the ethanol-treated group. ***\(p\) < 0.001.
# Robust Structural Damage Detection Using Analysis of the CMSE Residual's Sensitivity to Damage
## 4 Numerical Simulation  
In this section, the numerical robustness of the proposed damage identification scheme against measurement noise is demonstrated by considering a truss structure. A comparative study is conducted between the CMSE method with and without the sensitivity analysis. For convenience, the classical CMSE method without sensitivity analysis is still called the CMSE method, but the one with sensitivity analysis is called the robust CMSE (RCMSE) method.