esa-sceva/satcom-chunk-collection huggingface dataset:
# A Time-Varying Filter for Doppler Compensation Applied to Underwater Acoustic OFDM
###### Abstract  
This paper describes a Doppler compensation algorithm to improve the reliability of orthogonal frequency division multiplexing (OFDM). To compensate for the time-varying Doppler effect in a mobile deployment scenario, first the time-scaling factor over a wideband channel is estimated using pilot tones inserted in each OFDM symbol. Then, using a time-varying resampling technique, the Doppler effect is compensated during the reception of each OFDM symbol in the frame. To predict the performance of the system in relatively shallow waters, a software channel model is developed that is able to simulate a wide variety of dynamic shallow water deployment scenario. The performance of the algorithm was tested for two extreme frequency ranges during sea trials, the first at 2 kHz for a long-range application, and the second at 125 kHz for a short range telemetry link. For the 2-kHz system, a 16-bps mobile link in which the platform was moving at 1 m/s was demonstrated to have a bit error rate on the order of \(10^{-3}\), while, for the 125-kHz telemetry application, a 2000-bps link was enabled with a bit error rate of 0.03 at a low SNR equal to 5.5 dB.  
acoustic communication; wideband channel; channel modelling; time-scaling; doppler compensation; multicarrier modulation +
Footnote †: journal: Accepted: 25 December 2018; Published: 29 December 2018
## 2 Experimental Tests and Finite Element Simulations of Connector Performance  
### Experimental Tests  
As current Chinese specifications have no detailed requirements for a connection performance test for a honeycomb sandwich structure, the specimen in this paper is designed and tested based on the connection test procedure in \"Technical Specification for High Strength Bolt Connections of Steel Structures [22]\" and \"The Generals of Test Method for Properties of Adhesive-bonded Aluminium Honeycomb-Sandwich Structure and Core [23]\".  
The planar dimensions of a concatenated honeycomb sandwich specimen are shown in Figure 3a. The plate thickness has three specifications: 10, 15, and 20 mm. The thicknesses of the top and bottom plates are 1 mm. The length and thickness of a regular hexagon honeycomb core's side is 6 mm and 0.05 mm, respectively. The connectors include a high-strength bolt, an ordinary bolt, and a self-tapping bolt. Three specimens are made for each group with a total of 27 specimens. As the purpose of this study is to investigate a connector's failure mode and failure mechanism [24; 25; 26; 27; 28], the connector failure prior to the plate material failure (connected matrix) should be avoided. Therefore, each side only contains a single bolt connection. The test is based on a displacement load method, which evenly applies tension to a specimen according to a specified load pattern at a continuous rate of 1 mm/min until failure occurs. As aluminium honeycomb core material is relatively soft, internal pads are attached at both ends to prevent the honeycomb core at both clamps from being flattened during loading and at the bolt connection point to avoid local pressure failure when a specimen is prepared.  
Figure 3: Honeycomb sandwich specimens and connectors: (**a**) Specim dimension and finite element model; (**b**) Self-tapping bolt; (**c**) Ordinary bolt; (**d**) High-strength bolt.  
Figure 2: Concatenation test for a honeycomb sandwich structure system: (**a**) Loading site; (**b**) Buckled shape of internal surface of the sandwich box; (**c**) Partially enlarged diagram of the lateral side of the box specimen: bolt is cut off.
# Service-Oriented Cooperation Policies for Intelligent Ground Vehicles Approaching Intersections
## 2 Related Work and Literature
### Autonomous Driving Study  
Perception of the traffic environment is the cornerstone of ITS. Recently, the sensing capabilities of ITS have been largely promoted via the employment of more smart sensors, such as LiDAR, GPS, Inertial Navigation System (INS), Radar, Vision and so on, and emerging vehicular communication technologies, typically DSRC(Dedicated Short Range Communication), LTE-V, the coming 5G network, and also high-resolution maps etc.  
Surrounding these developing technologies, the theories and mechanisms of vehicular smart perception have been studied recently [17; 18; 19; 20; 21; 22; 23; 24; 25]. With the ability of precise perception, the foundation of autonomous driving has been getting better and better. Especially, decision-making, autonomous control, path-planning and behavior policies are several vital aspects that have been studied and experienced [26; 27; 28; 29; 30; 31]. For instance, [PERSON] et al. [32] studied a two-stage real-time decision-making method to improve road safety in city traffic systems, and then optimized the real-time decision-making method for autonomous city vehicles to select the most appropriate maneuver. [PERSON] et al. [33] presented an online-capable Partially Observable Markov Decision Process (POMDP) framework for autonomous driving in different environment situations. It provides near optimum solutions for the behavior generation on intersections. [PERSON] [34] formulated a Model Predictive Control (MPC) problem to generate a feasible trajectory for one vehicle, and further proposed several constraints and rules to guarantee coordination safety. [PERSON] et al. [35] proposed a predictive trajectory guidance and control framework that enables the safe operation of autonomous and semiautonomous vehicles considering the constraints of operating in dynamic public traffic. [PERSON] et al. [36] and [PERSON] et al. [37] also did similar work. [PERSON] et al. [38] designed a two-stage nonlinear nonconvex control approach, including an outer-loop nonlinear MPC and a model based on an inner linear feedback controller, for autonomous vehicles driving during highway cruise conditions. [PERSON] et al. [39] proposed a human-like decision-making algorithm for simple intersections without signals in the presence of another vehicle. All these autonomous driving studies make intelligent ground vehicles traveling on roads increasingly possible.
## 3 Results and Discussion
### Comparative LCA of Hydrogen Production: Biogas Reforming vs. Agricultural Residue
#### 3.2.6. Water Consumption and Land Use  
A unique finding of this study is the water consumption required for both processes. While agricultural residue gasification requires significantly more water (5.3737 m\({}^{3}\)) than biogas reforming (0.0485 m\({}^{3}\)), the overall environmental benefits of gasification still outweigh this drawback. Additionally, the land use (LU) impacts are lower in gasification (0.0116 m\({}^{2}\) a crop eq) compared to biogas reforming (0.0358 m\({}^{2}\) a crop eq), making gasification more sustainable in terms of land requirements. According to [PERSON] et al. (2012) [PERSON] et al. (2012) [PERSON] et al. (2012), biomass gasification systems often require substantial water input for gas cleaning and cooling, though advanced technologies, such as dry gas cleaning, could mitigate this impact. Meanwhile, the land use advantage of gasification aligns with other studies highlighting that agricultural residue utilization reduces pressure on arable land compared to energy crops used for biogas production.  
The superior GWP gasification performance emphasizes that carbon-neutral biomass feedstocks offset emissions from thermochemical processes. The lower fossil resource scarcity linked to biomass-based systems reduces the dependency on non-renewable catalysts and infrastructure. Gasification requires a higher water demand for biomass pretreatment, and gas cleaning indicates that it involves water-intensive stages. Though lower than biogas reforming, land use impacts highlight the need for sustainable agricultural residue sourcing to avoid competition with food production. The reduced toxicity in gasification is associated with fossil-based reforming, with higher heavy metal leaching. While gasification's water use remains a challenge, its overall environmental profile positions it as a more sustainable alternative to both biogas reforming and conventional steam methane reforming (SMR), particularly when paired with renewable energy integration. Thesefindings underscore the importance of process optimization and feedstock management in advancing low-carbon hydrogen economies.
## 1 Introduction
### Integration of Enabling Technologies
This complexity necessitates comprehensive approaches addressing multiple sustainability dimensions, enhancing environmental sustainability and urban resource management efficiency. To enhance the explanatory capabilities of the approach, an extension is proposed through the integration of key enabling technologies derived from the Industry 4.0 and 5.0 paradigms. Among these are advanced systems for route optimization, dynamic urban access regulation, and real-time parking management.
# Block Recovery Rate-Based Unequal Error Protection for Three-Screen TV
## 4 Experimental Results and Discussion
### H.264 SVC Unequal Error Protection Using Raptor Codes with Layer Switching  
This subsection explains the experimental results of H.264 SVC-based UEP with layer switching. The implemented codes were based on 'OpenSVCDecoder', and the Raptor FEC codes with UEP method were added on the decoder. The implementation included RSSI measurement module and layer switching module with the IDR picture in it. First, for verifying the benefit of the scalable video layer-switching method, Figure 12 shows the reactions of the proposed method according to the measured link quality (RSSI) in real moving experimentation.  
Figure 12a-c shows the measured network conditions such as RSSI, ABW, and PLR during user movements. As the mobile TV client was getting farther from the wireless AP, the value of RSSI was decreasing and it increased again when the mobile TV was coming towards the AP. From 50 to 90 s, the ABW was decreased and PLR was increased. Thus, the implemented server decreased SVC layers that have to be transmitted from three layers (BL + two ELs) to BL only by the 110 s point and increased the layers again based on the network quality feedback from the mobile TV client. The Raptor overhead adaptation was applied from 20% to 52% during the period. With these adaptive features of the proposed system, most of the packet losses were recovered, as shown in Figure 12f. The layer switching occurred on IDR pictures only when there were severe network condition changes, and all decoded pictures were upscaled for full resolution. Thus, the switching did not make a noticeable inconvenience.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Coding Structure**} & \multirow{2}{*}{**Methods**} & **Overhead 5\% with Base** & **Overhead 10\% with** \\  & & **PLR 12\%** & **Base PLR 17\%** \\ \hline \multirow{2}{*}{RA} & Uniform & 17.80 & 15.16 \\  & Proposed & 18.28 & 23.72 \\ \hline \multirow{2}{*}{AI} & Uniform & 20.03 & 17.44 \\  & Proposed & 21.28 & 29.48 \\ \hline \multirow{2}{*}{LDB} & Uniform & 15.44 & 14.64 \\  & Proposed & 16.20 & 22.60 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Y-PSNR results with Raptor overhead 5% and 10%.  
Figure 12: Reactions and adaptations of the proposed system according to the measured link quality in real moving experimentation. (**a**) RSSI changes; (**b**) ABW changes; (**c**) PLR changes; (**d**) SVC layer switching; (**e**) Raptor overhead adaptation; (**f**) Packet loss recovery.
# Antimicrobials in Dentistry
## 2 Antimicrobials Used in Dentistry
### Tetracyclines  
Antibiotics are commonly prescribed by dentists to either prevent infection or to treat infections, which also adds to the burden of antibiotic resistance. Most antibiotics are prescribed for systemic use; however, local delivery of tetracyclines as an antimicrobial and cationic chelating agent has been explored. Tetracyclines, a family of broad-spectrum antibiotics with cationic chelating properties, have shown collagenase- and gelatinase-inhibiting properties [56; 57; 58]. In addition to their antimicrobial activity, tetracyclines can chelate the catalytic zinc ions found within MMP enzymes [59; 60]. Of the tetracyclines and their semi-synthetic analogues doxycycline and minocycline, doxycycline is the most potent, due to its greater affinity for zinc ions, which led to the incorporation of this antibiotic into restorative materials [61; 62]. Although results demonstrated successful antibiotic films, bacterial resistance against tetracyclines is common, and due to their photo-oxidative potential, tetracyclines can cause purple staining of teeth, limiting their use clinically [57; 63]. However, their anti-inflammatory, antibacterial, anticollagenase, and immunosuppressive properties have seen the use of doxycycline in bone scaffolds to promote bone growth and reduce peri-implantitis [64,65].
# Tuning of Graphene-Based Optical Devices Operating in the Near-Infrared
## 3 Graphene-Based Optical Devices and Tuning
### Wavelength Tuning  
In the previous sections, several parameters such as the scattering rate (\(\Gamma\)), the graphene electrode thickness (\(t_{G}\)), the distance between graphene electrodes (\(D_{G}\)) for the GIG structure, or the insulator thickness (\(t_{I}\)) for others, and the applied voltage (\(V_{G}\)) were analysed. Table 2 compares the analysed devices (all the devices are fabricated except for Reference [15]) showing that the wavelength shift \(\Delta\lambda\) (last column) can vary from tens to thousands of picometers (last column in the table).  
Wavelength shift can also be related to the variation of the refractive index using Equation (5).  
The greatest influence on the tuning of the operating wavelength is exerted by a modulator based on planar photonic crystals, based on a nanocavity in combination with an electrolyte or ion-gel [7; 19; 20]. It should be borne in mind that in these structures, with an increase in the applied voltage, small changes in the transmission spectra can be observed until the breakdown of the device is achieved. The behavior of the device beyond this point is associated with the destruction of graphene, while the effect of plasma dispersion is still continuing. However, no further spectral shift is observed anymore, which confirms that the phase shift is mainly due to the electro-refractive effect of graphene. Although the plasma dispersion effect of doped silicon still exists, given that the doped region is relatively small and the plasma dispersion effect is weak in nature, the contribution of doped silicon is negligible [9].  
Conversely, the structures of the Mach-Zehnder graphene modulator and the microring resonator allow the achievement of a wavelength tuning in the range of 100-200 pm. In Reference [9], when simulating the chemical potential in the range <0.4 eV, a redshift of about 173 pm is observed. By adjusting the arm voltage, the modulation mode can be switched to a phase-dependent mode, when the chemical potential is in the range from >0.5 eV, leading to a blueshift of 385 pm (it can be achieved in this range with practically no amplitude fluctuations). The experiment showed a deterioration of these values down to 66 pm and 185 pm, respectively (due to the quality of graphene). The use of a planar photonic crystal modulator based on a nanocavity extends the tuning range up to 1-2 nm [19; 20].
###### Abstract  
Mobile edge computing networks (MECNs) based on hierarchical cloud computing have the ability to provide abundant resources to support the next-generation internet of things (IoT) network, which relies on artificial intelligence (AI). To address the instantaneous service and computation demands of IoT entities, AI-based solutions, particularly the deep reinforcement learning (DRL) strategy, have been intensively studied in both the academic and industrial fields. However, there are still many open challenges, namely, the lengthening convergence phenomena of the agent, network dynamics, resource diversity, and mode selection, which need to be tackled. A mixed integer nonlinear fractional programming (MINLFP) problem is formulated to maximize computing and radio resources while maintaining quality of service (QoS) for every user's equipment. We adopt the advanced asynchronous advantage actor-critic (A3C) approach to take full advantage of distributed multi-agent-based solutions for achieving energy efficiency in MECNs. The proposed approach, which employs A3C for computing offloading and resource allocation, is shown through numerical results to significantly reduce energy consumption and improve energy efficiency. This method's effectiveness is further shown by comparing it to other benchmarks.  
deep reinforcement learning; advanced asynchronous advantage actor-critic (A3C); multi-agent system; mobile edge computing; cloud computing; computational offloading; energy efficiency 2023
## 2 Materials and Methods
### Crop Variables Estimation Using Remote Sensing Data
#### 2.4.1 Phenological Metrics Extraction  
The phenological metrics extracted in this study included the start of the season (SOS), length of the season (LOS), peak of the season (POS), and end of the season (EOS). These metrics were derived from the Normalized Difference Vegetation Index (NDVI) [59; 60] time series of the study area. A Savitzky-Golay filter [61] was applied to minimize noise in the time series. The phenological metrics were determined based on the temporal evolution of the NDVI time series [25] and percentile extraction: The NDVI maximum was identified as the POS, the SOS was defined as the 10 th percentile of NDVI values preceding the maximum, and the EOS was defined as the 10 th percentile of NDVI values following the maximum. LOS was calculated as the difference in days between the EOS and the SOS. These derived phenological metrics were then compared with the phenological calendars recorded during the experiment, and any discrepancies were noted.  
In addition to these phenological metrics, the accumulated growing degree days (\(GDD_{accum}\), Equation (4)) were also considered to provide a more comprehensive understanding of crop development in the study area. \(GDD_{accum}\) is a measure of heat accumulation, which directly influences the timing of key phenological stages such as germination, flowering, and maturity [62]  
\[GDD_{accum}=\sum_{d=SOS}^{EOS}\left(\frac{T_{max}+T_{min}}{2}\right)-T_{base}0 \tag{4}\]  
where \(T_{max}\), \(T_{min}\), and \(T_{base}\) are the maximum, minimum, and base temperatures, respectively. In the case of winter wheat, the \(T_{base}\) is 0 \({}^{\circ}\)C. By considering the cumulative temperature exposure throughout the growing season, \(GDD_{accum}\) provides a more accurate prediction of phenological events than calendar days alone [63]. Once the phenological metrics were calculated, the accumulation of GDD began from SOS and continued until EOS. This approach allowed temperature data to be integrated throughout the growing season, providing a normalized evolution for crop development. The \(GDD_{accum}\) between SOS and EOS allowed us to quantify the heat accumulation required for the progression of phenological stages, thereby providing insight into the relationship between temperature and vegetation dynamics. This \(GDD_{accum}\), in conjunction with the previously derived phenological metrics, was compared with the Zadock (Z) crop development recorded in the experiment.
## 7 Conclusions  
In this work, a numerical-experimental investigation into the mechanical behaviour of a fastened hybrid composite-metal stiffened panel has been presented. For numerical predictions, the fasteners have been simulated by using a tie approach and ABAQUS connectors. Both the numerical models take into account the damage behaviour of composite sub-components by Hashin failure criteria while plasticity has been considered for the metallic sub-components.  
The numerical results have been correlated to data recorded from an experimental tensile test for a first preliminary validation of the adopted numerical approach. From this comparison, the fastener-based numerical model was revealed to be more accurate, if compared to the tie-based model, in predicting the experimental response in terms of deformations. Actually, tie constraints introduce excessive bonding between the sub-components without allowing the expected relative displacements between them. This preliminary numerical-experimental study demonstrated that the investigated hybrid panel does not experience any damage in composite sub-components up to a tensile load of 300 kN; while, at this loading level, some metallic sub-components experience extensive plastic deformation.  
An additional sensitivity numerical analysis has been performed to assess the influence of omega stringer joints on the inter-laminar damage evolution in composite sub-components. Indeed, the virtual crack closure technique has been used to investigate the effect of the omega stringer joints on the evolution of an artificial debonding inserted between composite skin and stringers under tensile loading conditions. Numerical analysis demonstrated that the omega stringer joints are able to arrest the skin-stringer debonding growth avoiding a drastic reduction of the load-carrying capability of the panel.  
All authors equally contribute to this work. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest.  
Figure 27: Omega joint configuration—delaminated area: load = 161 kN.
# Mg-Based Hydrogen Absorbing Materials for Thermal Energy Storage--A Review
## 3 Different Types of Mg-Based Materials for Thermal Energy Storage
### Different Heat Storage Systems of Mg-Based Materials
#### 3.1.4 The Mg-Co-H System  
Mg-Co-H were studied for heat storage material by different researchers with various thermodynamics data reported [64; 65; 66; 67; 68]. [PERSON] et al. [64] reported a value of 86 kJ/mol H\({}_{2}\) upon the hydrogen dissociation and 60 kJ/mol H\({}_{2}\) for the hydrogen absorption for the Mg\({}_{2}\)CoH\({}_{5}\) phase. Lower values were published by [PERSON]'s group. [66]. During the experiment process, they found two Mg-Co-H phases after a series of hydrogen desorption measurements and delivered 70 kJ/mol H\({}_{2}\) for Mg\({}_{6}\)Co\({}_{2}\)H\({}_{11}\) and 79 kJ/mol H\({}_{2}\) for Mg\({}_{2}\)CoH\({}_{5}\) to the heat of formation. In [PERSON] et al.'s work [67], they successfully fabricated nanostructured Mg\({}_{2}\)CoH\({}_{5}\) and Mg\({}_{3}\)CoH\({}_{5}\) by hydrogen plasma metal reaction and gave the formation enthalpy values of 82.27 kJ/mol H\({}_{2}\) and 73.16 kJ/mol H\({}_{2}\), respectively. Nevertheless, according to researchers' experimental results, it is obvious that the Mg-Co-H system has large hydrogen absorption enthalpy to become a suitable chemical heat storage candidate. The sample was prepared with a mixture of Mg and Co powder with a ratio of 2:1 to test cyclic stability and showed a more than 3.1 wt % hydrogen capacity after 1000 cycles. In addition,  
Figure 5: Heat storage demonstration unit on the basis of Mg\({}_{2}\)FeH\({}_{6}\). Reproduced with permission from [63], Copyright Elsevier, 2017.  
the experimental results of energy density are about 1472 kJ/kg for Mg\({}_{6}\)Co\({}_{2}\)H\({}_{11}\) and 1260 kJ/kg for Mg\({}_{2}\)CoH\({}_{5}\) in a temperature range of 450-550 \({}^{\circ}\)C [41].  
Figure 6: (**a**) Conceptual design of the tube bundle heat storage reactor. (**b**) Tube bundle reactor with welded components. (**c**) Flow of molten salt as directed between the baffles. Reproduced with the permission from [63], Copyright Elsevier, 2017.