esa-sceva/satcom-chunk-collection huggingface dataset:
# Wavelength Conversion Enhancement Achieved by Using Resonance in an Array of Nanocylinders
## 3 Conclusions
Enhancements of the UC process by using nanostructures have been reported in other UC materials such as ZnO/Zn [33] and InAs quantum dots (QDs) [34]. In ZnO/Zn, the nanostructure made by femtosecond laser ablation enhances the UC process from 800 nm to 500 nm, with an enhancement factor of one order of magnitude. In InAs QDs, the flat bandedge property of a photonic crystal waveguide enhances the UC process, achieving lasing of 1.3 mm light from the absorption of 1.55 mm light. In contrast to such UC nanostructures that have small effective UC conversion areas of several micrometers, our UC nanocylinder array made by the lanthanide UC material can be fabricated on a wafer scale by nanostamp or nanosphere lithography techniques; thereby, the UC process increases by two orders of magnitude. This work was supported in part by the National Research Foundation of Korea through the Korean Government under grant NRF-2013M3C1A3065051, NRF-2015R1A2A1A15055998, and NRF-2016R1C1B2007007. [PERSON] performed simulations and wrote the manuscript. [PERSON] and [PERSON] designed structures and performed simulations. [PERSON] supervised all simulations and revised the manuscript. The authors declare no conflict of interest.
## 3 Blockchain-Enhanced Security and Operational Efficiency in VANETs
### Architecture Overview
Moreover, the blockchain's inherent consensus mechanisms ensure that the data are validated effectively, even in the absence of RSUs. The cryptographic primitives employed by blockchain technology guarantee the authenticity and integrity of V2V communications, thereby maintaining the trust and security of the network [73].
# Millimeter-Wave Smart Antenna Solutions for URLLC in Industry 4.0 and Beyond
## 4 Antennas for mmWave Industry 4.0 and beyond Communication
### PCB-Based Antennas  
PCB technology is cost-effective and easy to fabricate for antenna designs [65]. For mmWave antenna design, ease of fabrication and integration is of paramount importance. PCB technology is a common choice to fulfill these requirements. Moreover, the radiation properties of a particular antenna element are also an important consideration in the technology selection process. Broadside antennas are typically easier to integrate into array configurations, whereas end-fire radiating elements lend themselves best to edge integration. Microstrip patch antennas are currently among the most used radiating elements for 60 GHz mmWave arrays, despite material losses and performance limitations at this band. Various substrates are used to design such antennas, such as FR4, Rogers, liquid crystal polymers (LCP), polytetrafluoroethylene (PTFE), etc. [81; 86; 116; 117; 118]. For industrial communication, some other durable substrates are also reported in the literature,such as Arlon, but at lower frequency bands [119]. However, conductor and dielectric losses are quite high in PCB-based antennas at mmWave frequencies.  
Because of the skin effect at 60 GHz, conductor losses increase manifold. A survey on various mmWave antenna designs from 10 to 100 GHz is presented in [65]. Many conventional PCB-based antennas such as microstrip patch, dipole, monopole and slot antennas are reported in the literature [81; 85; 86; 92; 95; 97; 120; 121]. Moreover, Vivaldi antennas [122; 123; 124], dielectric resonator antennas [125; 126; 127], fractal antennas [128; 129; 130], and substrate-integrated waveguide (SIW)-based leaky wave antennas [131; 132; 133; 96; 127] are also implemented on PCB technology.  
The key to enhancing antenna gain at the mmWave band is to use array configuration. A detailed overview of various mmWave array antennas, different array geometries, and the challenges in array configuration is presented in [65; 134]. Microstrip-based array antennas at 60 GHz may suffer losses. The properties of the substrate and its thickness necessitate extra consideration. At 60 GHz, the substrate thickness is quite high when compared to sub-6 GHz microwave frequencies. This impacts the bandwidth and input impedance of the antenna. Moreover, proper feed structure is essential to be designed for accurate antenna performance [65]. Furthermore, a review of array antennas, including 60 GHz P2P and P2 MP communication, is provided in [92].
# STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional Networks for Traffic-Flow Prediction
## 4 Results and Discussion
### Baseline Models  
We compared our model to other baseline models trained on the same computer, including:  
ARIMA: a classic algorithm for time-series analysis and forecasting that uses an autoregressive integrated moving-average approach.  
SVR: a machine-learning algorithm that can capture non-linear temporal features.  
FNN: a feedforward neural network that uses multiple hidden layers to capture non-linear temporal changes.  
GRU: a type of RNN model with gated recurrent units.  
FC-LSTM: a recurrent neural network with fully connected LSTM hidden units.  
STGCN: a spatial-temporal traffic-flow prediction model that combines gated temporal convolutional networks with graph convolutional networks.  
ASTGCN: a spatial-temporal traffic-flow prediction model that incorporates attention mechanisms to capture temporal and spatial changes. The difference between our model and ASTGCN is that ASTGCN extracts both temporal and spatial features from attention mechanisms and inputs them into spatial-temporal convolutional layers, while our model uses self-attention mechanisms to capture spatial-temporal dynamic dependencies, which are input into graph convolutional networks. Therefore, the embedding of spatial-temporal attention mechanisms is different, and our model uses self-attention mechanisms, which can capture higher-dimensional spatial-temporal dynamic characteristics.
## 6 Conclusions  
The implementation of a subjective perception tool for the quantity and intensity of impacts received in rugby can indeed be a valid method for capturing the quantity and magnitude of high-intensity impacts during a rugby match.  
In cases where teams do not have access to MEMS technology or video analysis, controlling this risk factor becomes mandatory, or it serves as a complement to technology. Likewise, in lower categories, we believe that these types of tools should be included in the educational process of developing athletes. Further studies in the various forms of rugby (rugby sevens and even rugby league) would be advisable to increase the reliability of this questionnaire.  
Therefore, we consider this questionnaire as a useful aid for rugby teams in various modalities around the world.  
[PERSON] and [PERSON] served as the study coordinator. [PERSON] and [PERSON] conceivedand designed the experiments. [PERSON] and [PERSON] assisted in data collection. [PERSON] analyzed the data. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] assisted in analysis and  
be especially helpful in situations where there is no good reason to believe that the parameters should take specific values based on theory or previous studies. In our specific case, the selection of non-informative priors was due to the lack of previous works on the matter.  
**Reason for Using Bayesian Methods**  
Bayesian methods provide complete probability distributions for parameters, which can be more intuitive and useful than frequentist confidence intervals. For example, by using the posterior predictive distribution of the error, we can have easily interpretable estimates for how much surveys diverge from GPS measurements.  
Bayesian methods can often handle more complex and hierarchical models than frequentist methods, which is useful when there are multiple levels of variability or complex correlation structures. This allowed us to easily deal with the assumption of heteroscedasticity in the linear model between error and magnitude.  
Bayesian methods can more easily work with non-standard probability distributions and do not require as strict assumptions as normality, which can be an advantage in many practical contexts. In our case, the assumption of normality was not violated, but we can easily adapt the models to other distributions if necessary, which generally saves time during the data analysis process.  
6. Sampling Algorithm  
PyMC3 uses what is called the No-U-Turn Sampler (NUTS). NUTS is a type of Hamiltonian Monte Carlo (HMC) sampler. The idea behind HMC is that, instead of randomly exploring the parameter space (as the Metropolis-Hastings method would do, for example), information about the gradient of the distribution can be used to inform the exploration. In this way, HMC can move large distances across the distribution while still being efficient.
## 1 Introduction
[PERSON] et al., investigated the effect of HDR and viscous dampers to increase cable damping by theoretical analysis and field experiments [23]. In addition, [PERSON] et al., reported the field measurement for stay cable with different type of dampers. They figured out that the damping of field measurement is lower than the theoretical value [24]. Other studies on viscous dampers combined with internal devices to enhance cable damping were also proposed [25; 26; 27]. As discussed above, most of the previous studies mainly focused on the effects of single damper, two viscous dampers or viscous damper combined with another type. The model for estimating the cable damping ratio of two HDR dampers considering the cable bending stiffness has been not studied yet and their effect is also not fully understood. In this study, the performance of stay cable with two HDR dampers is investigated to obtain higher damping ratio. Particularly, the theoretical model is proposed to evaluate damping effect of the cable with two HDR dampers considering its bending stiffness. The impact of loss factor, spring factor, dampers installation positions, and bending stiffness (EJ) of stay cable on the first modal damping ratio is also elucidated. Finally, an optimization study for two HDR dampers is carried out and discussed in detail.
# Optical Technology for NFV Converged Networks
## 3 Silicon Photonics Devices in Optical Transport: Challenges and Opportunities
### Coupling and Polarization Control Issues in Silicon Photonics Devices  
There are two techniques commonly used to connect a silicon photonic component to an optical fiber: edge coupling and surface grating coupling [18]. An edge coupler adapts the spot size of the light beam in optical fiber to the smaller spot size in the silicon circuit. Edge couplers have high coupling efficiency (i.e., low coupling loss), large bandwidth and are independent of the polarization state of the input light. However, since the polarization state of the input light is unknown in many applications, a dual polarization design for the photonic circuitry is often necessary, enabled by a polarization splitter and rotator [19]. In a Grating Coupler (GC), a diffraction grating is realized by periodically notching a silicon waveguide, so that light within a certain wavelength range is diffracted off in the direction of the connected optical fiber [20; 21]. This mitigates the need for accurate alignment between silicon chip and fiber, facilitating the testing of the circuit and, consequently, its fabrication process. The combination of GCs and micro-lenses has been proposed [22] to further decrease the required precision to alignment and bonding, that adds significant cost to the packaging. Several GC designs exist, some of them able to deal with an arbitrary input polarization state. An example is the Polarization Splitting Grating Couplers [21], where input light in two orthogonal linear polarization states is directed into two different orthogonal waveguides in the silicon photonic circuit. These may commonly have insertion losses in a range of 3-5 dB but state of the art components may reach values close to 2 dB [23; 24].  
Active polarization alignment, based on silicon photonics polarization controllers, was also proposed as alternative to the dual polarization design, e.g., based Mach-Zehnder interferometers with phase shifters [25]. However, no \"endless\" operation, i.e., the capability to deal with any arbitrary polarization variation without causing service interruption, was demonstrated so far with practical system configurations. Moreover, fiber Polarization Mode Dispersion (PMD) makes impossible for a single controller to simultaneously recover the polarization of all channels in a WDM system.
## 1 Introduction
While many studies have investigated droplet breakup with shock wave interactions through experiments and numerical simulations, there remains a notable gap in the understanding of the dynamic mechanisms governing sub-millimeter droplets generated after secondary fragmentation. Particularly, there is an absence of quantitative analysis concerning instability development at the sub-millimeter droplet-shock wave interface, as well as a dearth of accurate three-dimensional numerical simulations regarding the evolution of sub-millimeter droplets when the airflow environment is in a supersonic state after a shock wave interaction. Therefore, this study first conducted experiments on the aerodynamic fragmentation of sub-millimeter liquid droplets with an initial diameter of 0.42 mm under various shock wave impacts, based on the experimental designed by [PERSON] [16]. Quantitatively, we investigated the impact of sub-millimeter droplet initial diameter and Weber number on the development of the R-T and K-H instabilities following the extraction of spatiotemporal parameters for the fragmentation evolution of liquid droplets. Subsequently, a three-dimensional numerical simulation study was conducted to investigate the characteristics of the aerodynamic breakup of sub-millimeter liquid droplets in a supersonic gas velocity environment behind a Mach 2.12 shock. The VOF method was employed to capture the deformation of the liquid droplet interface and the evolution of the flow field. Moreover, adaptive grid refinement technology was employed to improve the accuracy and efficiency of the simulation. The numerical simulation result exhibited good qualitative agreement with the experimental data. These findings serve as a reference for further investigations into the development of interface instability and the dynamic mechanisms governing sub-millimeter liquid droplets generated after secondary fragmentation due to shock wave actions.
# Green Communication for Wireless Body Area Networks: Energy Aware Link Efficient Routing Approach
## 3 Green Computing for WBANs
### ELR-W: Operational Steps
#### 3.3.1 Initialization Phase  
In this phase of ELR-W protocol, BNC broadcasts a hello packet (HP) to convey its status and position on the body. All BSNs receive and store the position information of the BNC. Then each BSN broadcasts HP containing node ID, its energy status, location information, number of hops, and distance to the BNC. Thus, all BSNs update their neighbor's information in their NT.
## 3 Results and Discussions
### Damage Mechanisms  
Simulation analysis was conducted using the validated mesoscale closed-cell foam aluminum finite element model to study its deformation patterns under impact loads. As shown in Figure 18, the results indicate that as the compressive strain gradually increases, deformation bands begin to appear on the cross-section of the foam aluminum. These deformation bands are initially sparsely distributed, but as the compressive strain further increases, the range of the deformation bands gradually narrows and eventually converges to form a concentrated deformation band. This process reflects the characteristic of foam aluminum transitioning from initial uniform deformation to localized concentrated deformation under impact loads.  
Figure 16: Mechanisms of deformation of closed-cell aluminum foam.  
Figure 17: Experimental results are compared with numerical simulation results.  
The finite element model is sliced as shown in Figure 19 to analyses the different stages of deformation of closed cell aluminum foam. Initial stage: At lower compressive strains, the pore structure of the foam aluminum is in a state of uniform deformation as a whole, and no obvious local deformation characteristics have yet appeared. Deformation band formation stage: As the compressive strain increases, stress begins to concentrate in some weak areas of the foam aluminum (such as the connections of pore walls or the edges of pores), and these areas gradually form deformation bands. At this time, the distribution of deformation bands is relatively scattered, but a trend of local deformation has already appeared. Deformation band contraction stage: Further increasing the compressive strain, the stress concentration effect becomes more significant, and the range of the deformation bands gradually narrows. This is because the stress is further concentrated in a smaller area, resulting in relatively weaker deformation in other areas. Concentrated deformation band formation stage: Finally, at higher compressive strains, the deformation bands converge to form a concentrated deformation band. At this time, the deformation of the foam aluminum is mainly concentrated in this area, showing obvious localized deformation characteristics.  
This deformation pattern reflects the complex mechanical behavior of foam aluminum under impact loads, revealing its transition process from overall deformation to localized concentrated deformation, and provides an important basis for understanding the energy absorption characteristics and failure mechanisms of foam aluminum.
# Outage Performance of SWIPT-D2D-Based Hybrid Satellite-Terrestrial Networks
## 1 Introduction
Reference [21] investigates the performance of a two-hop AF MIMO relay network with an energy-constrained relay node adopting TS schemes. However, most existing literature around SWIPT schemes is focused on the performance of terrestrial relaying networks, and little considers the scenario of heterogeneous HTSNs. Motivated by the above, we consider the HSTNs in which an energy-constrained terrestrial UT cooperates with a shadowed terrestrial IoT device in a D2D communication. Both PS-based and TS-based SWIPT-D2D schemes are adopted by the energy-constrained UT to obtain sustainable energy for delivering information to the shadowed IoT device. We investigate the impact of the proposed SWIPT-D2D schemes by deriving the closed-form expressions for the outage probability (OP) of both the UT and the IoT device. The main contributions of this paper are summarized as follows: (1) we propose the framework of the HSTNs with PS-D2D and TS-D2D schemes; (2) we characterize the probability density function (PDF) and cumulative distribution function (CDF) of the signal-to-noise ratios (SNRs) over the hybrid satellite-terrestrial links; (3) we derive the closed-form expressions for the OP by adopting the PS-D2D and TS-D2D schemes. The rest of this paper is organized as follows: The PS-D2D-based and TS-D2D-based HSTN models are presented in Section 2. The theoretical derivation of the OP expressions is investigated in Section 3. Monte Carlo simulations are provided in Section 4. The conclusion is given in Section 5.
## 4 Discussion
### Analysis Regarding Devices Working with a Fixed Input Power to ARCM  
#### 4.1.1 ARCM Parameters  
The obtained simulation results show differences of up to 5 times in antenna gain and up to 5% in S11 parameter values within all the APD exposure scenarios, normalized to the anatomical [A] chest case (linear scale), as shown in Figure 5. In the case of the CWED exposure scenarios, differences in values of up to 11 times and 35%, respectively, were found.  
The above variability in antenna parameters was observed because the human body acts as part of the antenna when the antenna is located very close to the body--as reported in many studies [7; 20]. In particular, the antenna gain and the S11 parameter are among the key parameters regarding various functionalities of the wearable WIT device equipped with an ARCM, e.g., battery life and operating range or data rate, as well as eirp and electromagnetic impact on the user (SAR) [6; 34]. The observed increase (up to 2 times) in the gain values and decrease (up to 30%) in S11 in the CWED exposure scenarios compared to APD result in increased device functio  
Figure 5: The relative values of antenna parameters (gain, S11: linear scale), calculated in the cases of WIT used near the head, arm, forearm, and chest in APD and CWED 245 GHz exposure scenarios and 100 mW (20 dB) input power to the ARCM (all values as in Table 5; *—reference case: the APD exposure scenario with anatomical [A] model of chest; relative gain [linear scale] = \(10^{0.1\text{(gain[dB]-reference\_gain[dB])}}\); relative S11 [linear scale] = \(10^{0.05\text{(S11[dB]-reference\_S11[dB])}}\); whiskers—standard uncertainty of relative values determination \(\pm\) 35%).
## 2 Data  
### In Situ Data  
The REMEDHUS network [40] is located at the central part of the river Duero basin in Spain. It covers a semi-arid continental-Mediterranean agricultural region of 35 km \(\times\) 35 km (41.1-41.5\({}^{\circ}\) N, 5.1-5.7\({}^{\circ}\) W), with an area of approximately 1300 km\({}^{2}\). REMEDHUS is a member of the International Soil Moisture Network (ISMN) and includes 21 permanent stations providing hourly SM and LST measurements in the top 5 cm of the soil [44; 45]. Both are acquired with Hydra Probes that measure with an accuracy of 0.003 m\({}^{3}\)/m\({}^{3}\) for SM and 0.6 \({}^{\circ}\)C for LST [46]. The main land uses in this area are vineyard (stations E10, F6, H7, K6, J3, and L3), rainfed cereals or fallow (stations F11, H13, J12, J14, K9, K10, K13, L7, M5, M9, N5, and O7), and forest-pasture (stations H9 and M13). During the study period, station K4 changes its land use from vineyard (2011) to rainfed cereals or fallow (2012, 2013 and 2014). The SM and LST measurements of REMEDHUS from a particular year corresponding to stations over irrigated crops (K9 during 2012, K13 during 2013 and 2014) have been removed from the dataset. The reason for filtering irrigated crops is the quick SM fluctuations related with the high frequency of water supply (less than 12 h, specially during the summer), which are not captured by the SMOS 3-day repeat. Stations with corrupted LST (J12 during 2011) or corrupted SM (M13 during 2014) have also been discarded. In REMEDHUS there are also four automatic weather stations that measure air temperature, relative humidity, precipitation, solar radiation, reference or potential evapotranspiration (\(ET_{0}\)) and wind speed. The monthly accumulated \(ET_{0}\) and the daily mean precipitation have also been used in this study. Figure 1 (left) shows a land use map of the REMEDHUS region, including the 21 SM and LST stations and the 4 weather stations, depicted with black triangles and white dartboards, respectively.
# Sustainable Cold Chain Management: An Evaluation of Predictive Waste Management Models
## 5 Discussion
### Comparative Analysis of ARIMA and MLR Results  
The ARIMA and MLR models offer complementary strengths in addressing the unique challenges of cold chain logistics. ARIMA is particularly effective for strategic planning, capturing seasonal and temporal trends to reduce waste and align inventory with high-demand periods. On the other hand, MLR excels in capturing short-term demand fluctuations driven by multivariable factors, such as promotions and product-specific preferences.  
For example, ARIMA's ability to predict cyclical demand patterns supports proactive inventory management and long-term planning. In contrast, MLR's sensitivity to short-term variability enables real-time operational adjustments. However, both models faced limitations due to the absence of IoT-enabled metrics, highlighting the need for real-time data integration to improve accuracy. Together, these models provide a robust framework for optimizing cold chain logistics, reducing spoilage risks, and ensuring timely delivery of perishable goods.