esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Photoacoustic (PA) imaging is a methodology that uses the absorption of short laser pulses by endogenous or exogenous chromophores within human tissue, and the subsequent generation of acoustic waves acquired by an ultrasound (US) transducer, to form an image that can provide functional and molecular information. Amongst the various types of PA imaging, PA tomography (PAT) has been proposed for imaging pathologies such as breast cancer. However, the main challenge for PAT imaging is the deliverance of sufficient light energy horizontally through an imaging cross-section as well as vertically. In this study, three different illumination methods are compared for a full-ring ultrasound (US) PAT system. The three distinct illumination setups are full-ring, diffused-beam, and point source illumination. The full-ring system utilizes a cone mirror and parabolic reflector to create the ringed-shaped beam for PAT, while the diffuse scheme uses a light diffuser to expand the beam, which illuminates tissue-mimicking phantoms. The results indicate that the full-ring illumination is capable of providing a more uniform fluence irrespective of the vertical depth of the imaged cross-section, while the point source and diffused illumination methods provide a higher fluence at regions closer to the point of entry, which diminishes with depth. In addition, a set of experiments was conducted to determine the optimum position of ring-illumination with respect to the position of the acoustic detectors to achieve the highest signal-to-noise ratio.  
full-ring illumination; diffused-beam illumination; point source illumination; ultrasound tomography (UST); photoacoustic tomography (PAT)
## 7 Experiment  
### Active Preference Reward Learning  
The query optimizer identifies the most optimal (a) and (b) trajectories from a given ensemble by maximizing information gain. A human user is then presented with these options, choosing between trajectory (a) or (b) based on personal preference, as illustrated in Figure 1. The belief model is updated following the user's feedback, utilizing the No-U-Turn Sampler (NUTS) method. Instead of direct human preference selection, our experiments used a softmax human model to simulate the evaluation and selection of trajectories, as shown in Figure 5. We conducted two sets of experiments to assess query optimization techniques: one using a randomly generated query optimizer and the other utilizing a mutual information-based optimizer for comparative purposes. Both optimizers integrated the NUTS method for belief model updates, complemented by the adaptive Metropolis algorithm for model refinement. The protocol was designed to iterate 40 times,with the cosine similarity between the updated belief model and the softmax-based human model calculated after each iteration, as per Equation (10).  
\[\text{Cosine Similarity}(A,B)=\frac{A\cdot B}{\|A\|\|B\|} \tag{10}\]  
This method enabled a comparative analysis of the efficacy of the two optimization methodologies. The outcomes are presented in four distinct curves, as shown in Figure 6. The results indicate that the mutual information-based optimizer surpasses the random query optimizer, and the NUTS algorithm significantly enhances the belief model's approximation capabilities. We further applied the mutual information optimizer and the NUTS update algorithm to train navigation tasks in autonomous driving systems.
## 4 Results
### Wind Energy
#### 4.1.4 Hydrogen Production from Wind Energy  
Wind energy can be easily coupled with an electrolyzer to produce green hydrogen from water splitting processes. Both the alkaline water electrolyzer (AWE) and the polymer membrane exchange electrolyzer (PEME) are commercially available in different sizes. Supplementary Table S1 shows three size classes (i.e., small, medium, and large) of these two types of electrolyzers. Furthermore, a converter with 90% efficiency was considered for the present study. The most suitable production capacity observed for the PEME electrolyzer is the medium sized one with a production of about 310.1 tons H\({}_{2}\)/year (Supplementary Table S7). Regarding the AWE electrolyzers, the large size was the most suitable with a production capacity of about 398.7 tons H\({}_{2}\)/year (Supplementary Table S7).  
The total investment cost is related to the amount of hydrogen produced, which varies according to the available energy. The energy produced by the \"Yinhe GX113-2.5 MW\" wind turbine could run three AWE\({}_{1}\) or 14 PEME\({}_{\text{m}}\) electrolyzers. The capital costs for the three AWE\({}_{1}\) and 14 PEME\({}_{\text{m}}\) electrolyzers are estimated to be $4,629,860 and $3,463,096, respectively (Table 3).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **Units** & **Values of Turbine T25** \\ \hline Specific cost of wind turbine & US\$/KW & 1600 a  \\ Life time & Year & 20 b  \\ Initial investment cost & US\$ & 4,000,000 \\ Variable capital cost (30\%) & \% & 1,200,000 c  \\ Total investment cost & US\$ & 5,200,000 \\ Interest rate of Djibouti & \% & 0.1087 d  \\ Discount rate of Djibouti & \% & 0.125 e  \\ Operation \& Maint. Cost (25\%) & \% & 1,300,000 f  \\ Capacity factor of Turbine & \% & 84.96 \\ Energy output of Turbine & KWh/yr & 18,606,641.39 \\ Present Value Cost & US\$ & 15,640,958.47 \\ LCOE & **US\$/KWh** & **0.04203** \\ \hline \hline \end{tabular}
\end{table}
Table 2: Unit cost of electricity generated by Turbine “Yinhe GX113-2.5 MW”.
## 2 Challenges in the Market Structure
### Approach to Active System Management (ASM) and Regulatory Framework  
A crucial question that needs to be answered is to find ways to integrate the offered flexibility services in the energy market via these actors and new assets. Then, we will be able to use them for balancing and congestion management, ensuring the efficient and reliable system operation. This is due to the enormous growth of distributed generation from renewable sources and storage as well.  
Figure 5: Visualization in a high level of the pilot project in Greece.  
Congestion management and balancing are first supported by network codes and guidelines. Additionally, it is anticipated that the Clean Energy Package will allow DSOs the ability to acquire non-frequency auxiliary services and manage grid congestion. This is the most economical option, since DSOs must buy these services.  
Ancillary services are those that DSOs and TSOs receive in order to maintain the grid's operation within reasonable limits for the security of supply. These services are typically provided by outside or by the TSOs and DSOs themselves [53]. Ancillary services are as follows:  
1. frequency ancillary services (mainly for balancing);
2. services for congestion management;
3. non-frequency ancillary services (e.g., voltage control).  
Active power management is examined in the Active System Management (ASM) study from the standpoint of a close partnership between TSOs and DSOs. When such services are offered using a market-based approach by flexibilities owned and operated by outside companies [53], the congestion management in both distribution and transmission grids is also examined. The modification of generation injection and/or consumption patterns in response to an external signal (price signal or activation) to provide a service inside the energy system is referred to as flexibility in the context of the Greek demo [54]. The regulatory framework to these issues is:  
1. Article 32.1 of (EU) 2019/944 Directive [5].
2. System Operation Guide Lines (SOGL) [10].
3. Electricity Balancing Guideline (EBGL) [9].
4. Guideline on Capacity Allocation and Congestion Management (CACM) [11].
5. Network Code on Requirements for Generators [54].
6. Demand Connection [34].
## 2 Materials and Methods
### Measurements  
Intraoral scans were taken for every patient using a standardized protocol and the same device, the TRIOS scanner (3 Shape, Copenhagen, Denmark), generating three digital models: Pre-treatment (T1), outcome predicted by the planning software (T2), and post-treatment (T3). The scanning protocol followed the manufacturer's guidelines to ensure consistent and accurate capture of the dental arch anatomy for all patients. Analysis of dental movements was conducted through dental superimpositions using the protocols developed by [PERSON] et al. [27] and [PERSON] et al. [28]. These protocols involved aligning the region of the palatal rugae on the hard palate, which serves as a stable reference for superimposition. Additionally, specific points on the teeth that were confirmed to remain stationary during treatment were selected as supplemental references to ensure accurate alignment and minimize error.  
The following measurements were recorded in mm at each time point: upper and lower intercaline widths, inter-first premolar, and inter-second premolar widths, both at the vestibular cusps and at the middle lingual gingival level. All measurements were performed using OrthoAnalyzer 1.7 analytical software (3 Shaphe, Copenhagen, Denmark). Only canines and premolars were included in the analysis because the GT system primarily targets these teeth for transverse expansion. Molars were excluded because the GT system uses them as an anchorage, and they do not receive active force application. This selection aligns with the study's objective of evaluating the clinical effectiveness and predictability of the systems in areas where both devices exert biomechanical forces.  
The effectiveness of expansion was assessed by calculating the percentage of width achieved by treatment (T3-T1 %). The predictability of expansion was assessed by calculating the percentage of the observed expansion relative to the predicted expansion (T3-T1 \(\times\) 100/T2-T1).
## 4 Performance Evaluation  
We implemented DRDT using C++ to evaluate its performance. Table 3 lists the main parameters. The radio model that reflects MICA2 motes is implemented with several adjustable parameters. 2,500 sensor nodes with 40 m radio range are randomly distributed in a network over an area of 300 \(m\)\(\times\) 300 \(m\). A sink is positioned at the center of the field, and each node transmits a data packet to the sink over multiple hops, using different routing protocols. We use Original Greedy Forwarding (termed GF-HOP) [13] and PRR \(\times\) Distance Greedy Forwarding (termed GF-ETX) [11] as baseline routing schemes. DRDT is implemented as extension layer for each baseline routing scheme. We compare these schemes before and after applying CBF [19] and DRDT.  
\begin{table}
\begin{tabular}{|l|} \hline Input: sender id (\(s\_id\)), receiver id (\(r\_id\)) \\ Output: retransmission task on behalf of sender node \\ \hline TRANSMISSION PHASE (\(s\_id\), \(r\_id\)) \\ \hline / When a node is selected as a helper node, it starts transmission phase \\
1 \(flag\gets 0\) \\
2 **if** receiving CTS packet from receiver node \\
3 **then** TRANSMIT(control, \(s\_id\)) \\
4 **TRANSMIT(data, \(r\_id\))** \\
5 **else** drop the data packet \\ \hline TRANSMIT (\(packet\_type,\ node\_id\)) \\
1 **if**\(packet\_type=data\) \\
2 **then**\(flag\gets 1\) \\  // If \(flag\) value is 1, it means that the data packet is transmitted \\  // from helper node add flag bit to packet header \\
3 **transmit packet to**\(node\_id\) until receiving ACK packet \\
4 **return** 0 \\ \hline \end{tabular}
\end{table}
Table 2: Pseudo-code of transmission phase.
## 3 Results
### Fading Correction and Cobbles Ages  
By applying the well-known equation age [6], the cobble burial ages were simply derived by dividing the cobbles surface absorbed dose values by the dose rate at the surface of the cobbles. However, the luminescence signal from feldspars could be unstable: this phenomenon is known as 'anomalous fading' and can be taken into account by the conventional g value measurement [21]. For the samples Pat12 and Pat15, we have quantified the fading rate as a percentage of IR signal loss  
Figure 4: Luminescence depth-profiles (a) 1/2016 sample; (b) 3/2016 sample.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Sample Code**} & \multirow{2}{*}{**Sample Type**} & \multirow{2}{*}{**Technique**} & **Absorbed** & **Dose Rate** & \multirow{2}{*}{**Date**} \\  & & & **Dose (Gy)** & **(mGy/a)** & \\ \hline
1/2016 & ROCK & OSL & \(24.5\pm 3.5\) & \(5.15\pm 0.15\) & 2760 BCE \(\pm\) 500 \\ US178 & ROCK & OSL & \(20.8\pm 3.5\) & \(2.95\pm 0.20\) & 2675 BCE \(\pm\) 500 \\ US178 & SEDIMENT & OSL & \(15.4\pm 0.5\) & \(2.95\pm 0.07\) & 3220 BCE \(\pm\) 330 \\
3/2016 & ROCK & IRSL & \(42.3\pm 7.5\) & \(10.75\pm 0.30\) & 1920 BCE \(\pm\) 250 \\ Pat12 & ROCK & IRSL & \(30.5\pm 5.0\) & \(4.20\pm 0.12\) & 5240 BCE \(\pm\) 600 \\ Pat12 & SEDIMENT & OSL & \(17.2\pm 0.4\) & \(2.40\pm 0.08\) & 5090 BCE \(\pm\) 360 \\ Pat15 & ROCK & IRSL & \(22.9\pm 4.0\) & \(6.50\pm 0.25\) & 2470 BCE \(\pm\) 500 * \\ Pat15 & SEDIMENT & OSL & \(12.8\pm 0.4\) & \(3.00\pm 0.05\) & 2270 BCE \(\pm\) 260 \\ \hline \hline \end{tabular} \({}^{*}\)Fading-corrected date.  
\end{table}
Table 3: Cobbles and sediments calculated ages.  
with storage time after irradiation. Three aliquots from each sample were bleached in the reader using an IR stimulation (for 500 s at 50 \({}^{\circ}\)C repeated after 60 s); a known dose has been imparted, and then the absorbed dose were measured, both immediately after irradiation and after a delay time of 6 h, 1 day, 19 days and 33 days. For the sample Pat12, the ratio between the imparted dose and the dose measured after the time delay are indistinguishable from unity, (Figure 5), thus, it possible to deduce that the phenomenon of anomalous fading is negligible. The cobble Pat15 is in a different condition: its signal fades by 10% in about a month. Therefore, we evaluate the fading rate with a \(g\) value of \(2.4\pm 0.5\%\), and in Table 3, the fading-corrected date is reported.
# Multi-Feature Fusion with Convolutional Neural Network for Ship Classification in Optical Images
## 3 Proposed Ship Classification Method
### Multi-Feature Fusion  
In order to obtain more comprehensive ship image feature representation, the high-level features extracted by the improved CNN and handcrafted features of HOG and LBP were considered to be fused. The improved CNN can extract the structure and semantic information of ship images. Based on the low-level features obtained from the first convolution layer, CNN learns features through layer-by-layer propagation, which may lose some important low-level information. Therefore, handcrafted features such as HOG and LBP were fused to supplement edge features and spatial texture features to obtain more comprehensive feature representation.  
After feature extraction according to Algorithms 1, 3 and 4, in the last fully connected layer these three types of features were concatenated into a composite vector with the weight of 1:1:1 and fed into the Softmax layer for final classification. The procedure of multi-feature fusion strategy is shown in Figure 11.
# Effect of Local Cyclic Loading on Direct Shear Strength Characteristics of Shear-Zone Soil
## 3 Materials and Methods  
### Soil Properties  
The shear-zone soil used in the cyclic direct shear test was from the third test tunnel of the No. 1 riverside landslide accumulation of the Huangtupo landslide. Laboratory tests were performed to determine the basic physical and mechanical properties of the shear-zone soil (Table 1). The particle size distribution curve of the shear-zone soil is shown in Figure 3. According to a plasticity chart of the unified soil classification system of ASTM D-2487, because the plasticity index and liquid limit are 18.51 and 36.02%, respectively, the soil classification of the shear-zone soil is CL. Based on the particle size distribution curve, the sizes \(d_{\text{60}}\), \(d_{\text{50}}\), and \(d_{\text{10}}\) are 4.96 mm, 1.54 mm, and 0.03 mm, respectively. As the coefficient of uniformity \(\text{C}_{\text{u}}\) is 146.93, the shear-zone soil is poorly graded.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Natural Moisture** & **Natural Density** & **Specific** & **Liquid Limit** & **Plastic Limit** & **Plasticity** & **Deformation** \\
**Content _w_/\%** & \(\rho\)**/(fg.cm\({}^{-3}\))** & **Gravity Gs** & _w\({}_{\text{L}}\)_/\%** & _w\({}_{\text{P}}\)_/\%** & **Index** & **Modulus E/MPa** \\ \hline
13.85 & 2.15 & 2.67 & 36.02 & 17.51 & 18.51 & 25.66 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Basic physical and mechanical properties of the shear-zone soil.  
Figure 3: Particle size distribution curve of shear-zone soil from the Huangtupo landslide.  
Figure 2: Flowchart for the whole work process.
# Development of Multimodal Physical and Virtual Traffic Reality Simulation System
## 5 Case Studies
### Case Study II
#### 5.2.3 Pedestrian--Driver Interaction Hypotheses  
In this study, we tested two hypotheses regarding pedestrian behavior and physiological response to approaching vehicles.  
**Hypothesis 1:**: _Effect of Vehicle Speed on Pedestrian Gap Acceptance._  
* **Null Hypothesis (H\({}_{01}\)):** Vehicle speed does not affect pedestrian gap acceptance.
* **Alternative Hypothesis (H\({}_{11}\)):** Higher vehicle speeds lead to more conservative pedestrian gap acceptance behavior.  
The null hypothesis assumes that pedestrians make crossing decisions independent of vehicle speed, meaning they accept gaps of similar size whether the vehicle is traveling at 30 mph or 50 mph. However, in real-world scenarios, pedestrians often base their crossing decisions on perceived risk and available reaction time. Faster vehicles provide shorter time windows for crossing, potentially leading to more cautious decisions and longer accepted gaps. The alternative hypothesis suggests that higher speeds increase perceived danger, making pedestrians less likely to accept small gaps and more inclined to wait for larger gaps before crossing.  
Figure 9: Relationship between critical moment, distance, and heart rate in Case Study II: definition of before and after the critical moment.  
**Hypothesis 2:**_Effect of Vehicle Speed on Pedestrian Heart Rate._  
* **Null Hypothesis (H\({}_{02}\)):** Vehicle speed does not influence pedestrian heart rate during the trial.
* **Alternative Hypothesis (H\({}_{12}\)):** Higher vehicle speeds cause an increase in pedestrian heart rate, indicating a physiological stress response.  
The null hypothesis assumes that vehicle speed does not induce significant physiological stress in pedestrians and that their heart rate remains stable regardless of approaching vehicle speed. However, research on risk perception suggests that higher speeds may be subconsciously interpreted as more dangerous, leading to increased physiological arousal. The alternative hypothesis proposes that faster vehicles generate a stronger stress response, which can be captured through elevated heart rate levels before and after the critical moment.  
By testing these hypotheses, our study aims to determine whether vehicle speed significantly influences pedestrian gap acceptance and stress responses while validating the ability of our simulation system to provide an accurate and immersive 3D environment for pedestrian safety research. This ensures that future studies can reliably use the setup to assess real-world pedestrian decision-making under different traffic conditions.
# Rethinking Modbus-UDP for Real-Time IIoT Systems
###### Abstract  
The original Modbus specification for RS-485 and RS-232 buses supported broadcast transmission. As the protocol evolved into Modbus-TCP, to use the TCP transport, this useful feature was lost, likely due to the point-to-point nature of TCP connections. Later proposals did not restore the broadcast transmission capability, although they used UDP as transport and UDP, by itself, would have supported it. Moreover, they did not address the inherent lack of reliable delivery of UDP, leaving datagram loss detection and recovery to the application layer. This paper describes a novel redesign of Modbus-UDP that addresses the aforementioned shortcomings. It achieves a mean round-trip time of only 38% with respect to Modbus-TCP and seamlessly supports a previously published protocol based on Modbus broadcast. In addition, the built-in retransmission of Modbus-UDP reacts more efficiently than the equivalent Modbus-TCP mechanism, exhibiting 50% of its round-trip standard deviation when subject to a 1% two-way IP datagram loss probability. Combined with the lower overhead of UDP versus TCP, this makes the redesigned Modbus-UDP protocol better suited for a variety of Industrial Internet of Things systems with limited computing and communication resources.  
embedded systems; real-time communication networks; industrial communication; Modbus; industrial IoT 202517 356  
Istituto di Elettronica e di Ingegneria dell Informazione e delle Telecomunicazioni (IEIT),  
Consiglio Nazionale delle Ricerche (CNR), 10129 Turin, Italy; [EMAIL_ADDRESS]
# 3D Stress Analysis of Multilayered Functionally Graded Plates and Shells under Moisture Conditions
## 2 Fick Moisture Diffusion Equation  
This model relies on a decoupled solution, which means that the moisture content is evaluated separately and enters the elastic part of the problem as a known term. The essential hypothesis to obtain exact closed-form solutions is that all the problem variables have a harmonic form. For what concerns the moisture content, this means  
\[\mathcal{M}^{k}(\alpha,\beta,z)=M^{k}(z)sin(\bar{\alpha}\alpha)sin(\bar{ \beta}\beta)\, \tag{1}\]  
\(M^{k}(z)\) indicates the moisture content amplitude. Referring to Figures 1 and 2: \(m\) and \(n\) are the half-wave numbers in the two in-plane directions \(\alpha\) and \(\beta\), respectively. \(a\) and \(b\) are the shell dimensions referred to the mid-surface \(\Omega_{0}\); they allow calculating the terms \(\bar{\alpha}=\frac{m\pi}{a}\) and \(\bar{\beta}=\frac{m\pi}{b}\). Note that the harmonic form of the moisture content reduces its assessment to its profile along with the thickness direction \(z\). What happens in \(\alpha\) and \(\beta\) directions is already defined through the sinusoidal functions.  
The hygrometric boundary conditions are the moisture content amplitudes at the bottom and the top of the shell, \(M_{b}\), and \(M_{t}\), respectively. Three approaches exist to evaluate the moisture content profile; this solution implements all three, allowing a homogeneous comparison among them and with other methods. The solution is accomplished in analogy with what the authors achieved in [21] concerning the temperature field. Indeed, the Fourier heat conduction equation, regulating the thermal phenomenon, features the same mathematical expression of the Fick diffusion law, which applies to the moisture diffusion problem. The three approaches are here listed:  
* the moisture content profile is defined by solving the 3D Fick diffusion law; the hygro-elastic model considering it takes the name of 3D(\(\mathcal{M}_{c}\)3D);
* the moisture content profile is defined by solving the 1D version of the Fick diffusion law; the hygro-elastic model considering it takes the name of 3D(\(\mathcal{M}_{c}\)1D);
* the moisture content profile is \"a-priori\" assumed as linear along with the thickness direction; the hygro-elastic model considering it takes the name of 3D(\(\mathcal{M}_{a}\)).  
Figure 1: Geometrical data and coordinate system for plates and cylinders. The figure also shows the stacking sequence used in Benchmarks 1 and 2.  
All the acronyms report the term 3D: it states that the elastic part of the shell model relies on a three-dimensional solution. Instead, the part of the acronym inside the parentheses defines how the moisture content profile has been quantified. \"c\" means calculated, either via the 3D or the 1D Fick diffusion laws; \"a\" means linear assumed.