esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Work  
### Models Related to Natural Gas Prediction  
In the field of natural gas demand forecasting, researchers have adopted various methods to improve prediction accuracy and reliability. These methods include models that establish relationships between natural gas demand and influencing factors through statistical and econometric methods, as well as time series models that predict future demand by analyzing historical data trends. Statistical and econometric methods can effectively explain the driving factors behind demand changes. For example, [PERSON] et al. [2], in their study of Pakistan, found that the elasticity of GDP on natural gas demand is significant, while the price elasticity is relatively small. Similarly, [PERSON] et al. [10], in their study of Pakistan, found that per capita natural gas demand is positively correlated with per capita real income, the average real price of natural gas, and the real price of substitutes. Time series models, on the other hand, primarily rely on the continuity of historical data to predict future demand trends. For instance, [PERSON] et al. [11] proposed a new statistical decomposition model that can capture the demand patterns of industrial end-users' natural gas consumption. [PERSON] et al. [12] used the ARIMA to predict Turkey's natural gas demand and found that this model performs well in short-term forecasting.  
Artificial neural networks (ANNs) train nonlinear prediction models using historical data, capable of capturing complex nonlinear relationships. For example, [PERSON] et al. [6] used a two-stage system in which the first stage consisted of three different ANN predictors, while the second stage utilized a nonlinear combination predictor to forecast natural gas demand. [PERSON] et al. [8] used an MLP-trained ANN to predict natural gas consumption for residents in Szczecin, Poland, demonstrating its advantages in capturing complex nonlinear relationships. To address the limitations of individual models, [PERSON] et al. [7] proposed a method combining ANN, ANFIS, and traditional regression models for long-term natural gas demand forecasting. [PERSON] et al. [13] further improved the accuracy of natural gas demand forecasting in Pakistan by using a combination of multiple models. These hybrid methods leverage the strengths of different models, thereby enhancing the accuracy and reliability of predictions.  
Despite the widespread use of these methods in natural gas demand forecasting, each has its own limitations. Some methods struggle to handle nonlinear relationships adequately, while others fail to effectively capture changes in market and economic conditions. Additionally, certain methods are complex to implement and require large amounts of data. Overall, these methods often find it challenging to address the complexities of nonlinear relationships and multiple features simultaneously, making it difficult to achieve sufficiently accurate and robust predictions in complex market environments.
## 4 Results
### Application of the Method. Case Study of the Lojuela Castle
#### 4.1.5 Description of the Materials  
These were assessed by taking different samples from the surface of the cladding and stretches of the wall (Figure 7). The results indicate that: as regards the wall, its main body was found to be principally lime-based. It consists of mortar made by mixing lime and clay. Siliceous and carbonated aggregates were used, with the granulometry revealing a range of sizes from gravel to sand. The siliceous aggregates are comprised of quartz, muscovite, chamosite and feldspar. The carbonated aggregates are composed of dolomite and possibly, calcite [124].  
The XRD analyses carried out on the sample of the calicostrated wall mass detected that the matrix is mainly calcitic. It established that the construction material--as detailed before--is a mortar made with a mixture of lime and clay, in which siliceous and carbonated aggregates were used, with serial grain size from gravel to sand (Figure 8).  
Figure 8: X-ray diffractogram of the sample. Source: PREFORTI project and TESELA S.L.  
Figure 7: Materials used in the construction of Lojuela Castle (without scale). Source: PREFORTI project.  
In relation to the coping, its aggregates would have contained fragments of quartz-schists, schists with garnets, black graphite schists, limestone and dolomite. Siliceous aggregates have characteristics similar to those of the basal mantle in the Guajares, west of the castle. The carbonated aggregates are similar to the materials in the mantles of the Alpujarran complex. The rock fragments which were used as aggregates are congruent with the geological context of the castle [124].  
The mortars used for the coping are calcitic, with a lime/aggregate ratio of approximately 1:3. As for the masonry cladding, the mortar is similar to those mentioned previously although the mortar mix is made from calcitic lime, with a lime/aggregate ratio of approximately 1:2. The cladding was a mineralogical composition which is similar to the coping and mortar, although the grayish hue of the mortar and the cement dye test indicate the use of Portland cement in its composition [124].  
The study carried out by scanning electron microscopy with EDX microanalysis and from the spectra obtained determined that the composition of the matrix of the rammed-earth crust is calcitic. Mica (Muscovite) crystals were also observed wrapped in the matrix. The presence of roots of the natural patina was verified. It generates biodeterioration in the sample since they penetrate inside the crust mortar (Figure 9). In the matrix of the rammed-earth mass, siliceous aggregates are observed enclosed within a microcrystalline matrix formed by a mixture of calcite and illite [124].
# Niching Grey Wolf Optimizer for Multimodal Optimization Problems
###### Abstract  
Metaheuristic algorithms are widely used for optimization in both research and the industrial community for simplicity, flexibility, and robustness. However, multi-modal optimization is a difficult task, even for metaheuristic algorithms. Two important issues that need to be handled for solving multi-modal problems are (a) to categorize multiple local/global optima and (b) to uphold these optima till the ending. Besides, a robust local search ability is also a prerequisite to reach the exact global optima. Grey Wolf Optimizer (GWO) is a recently developed nature-inspired metaheuristic algorithm that requires less parameter tuning. However, the GWO suffers from premature convergence and fails to maintain the balance between exploration and exploitation for solving multi-modal problems. This study proposes a niching GWO (NGWO) that incorporates personal best features of PSO and a local search technique to address these issues. The proposed algorithm has been tested for 23 benchmark functions and three engineering cases. The NGWO outperformed all other considered algorithms in most of the test functions compared to state-of-the-art metaheuristics such as PSO, CSA, GWO, Java and two improved variants of GWO, and niching CSA. Statistical analysis and Friedman tests have been conducted to compare the performance of these algorithms thoroughly.  
metaheuristic algorithm; swarm intelligence; multi-modal optimization; Grey Wolf Optimizer; niching technique; local search +
Footnote †: journal: Applied Sci. 2021  
114795
## 3 Results and Discussion
### Effect of Lap Rate on Forming Stability
#### 3.2.2 Effect of Z-Increment on Forming Stability  
Figure 9 shows cross-sectional images of the six layers with lifting amounts (\(\Delta Z\)) of 0.30 mm, 0.28 mm, and 0.26 mm, respectively. When \(\Delta Z\) is 0.30 mm, the two sides of the cross-section of the cladding layer are relatively vertical, and the theoretical height is the closest to the actual height. The height error between the actual height and the theoretical height is 0.33%, which is much lower than 6.4% (Figure 9b) and 7.6% (Figure 9c). Figure 9b,c also have defects such as irregularity and increasing cladding width, which causes inclination of the cladding side. In general, the most appropriate \(\Delta Z\) is 0.30 mm. Figure 9b,c are both in the case of \(\Delta Z\) less than 0.30 mm. Thus, the lifting amount is less than the actual \(\Delta Z\). As shown in Figure 9d, the lifting amount is determined to ensure that the area of the rectangle ABCD is equal to the area of the first cladding layer. Thus, the area of the remelted part is equal to the sum area of the area AOD and the area BQC. When the \(\Delta Z\) is relatively small, the second layer of cladding layer AMB becomes the cladding layer A'MB', and the remelting area changes from the area ONQ to the area PNR. The remelting area is much larger than the sum area of the A'PD and the B'RC. The excess cladding layer will first lead to the extension on both sides. As the number of cladding layers increases, the extension will become more obvious, forming the inclination of both sides of the cladding layer, as shown in Figure 9b,c. The second effect is to reduce the utilization rate of the powder. Therefore, there is a large amount of un-melted or micro-melting powder on the surface and edge of cladding paths, and even embossment appears, resulting in irregularities on both sides of the cladding layers in Figure 9b,c. When the \(\Delta Z\) is small, the distance from the laser head becomes smaller. Therefore, when the next layer of LC is performed, the energy density will increase. This part of the increased energy is refracted and part of it is used for remelting. If there is remaining energy, the remaining powder can be utilized, so the actual height in Figure 9b is 6.4% higher than the theoretical height. Figure 9c is considered to increase the energy consumption of the remelting area, and the utilization rate of large powder is lower, resulting in a low energy utilization rate. Therefore, the actual height is 7.6% lower than the theoretical height.  
Figure 9: Micrograph of the cross-section of the longitudinal lap.
# Potential and Limitations of Open Satellite Data for Flood Mapping
## 4 Results
### Semi-Automatic Mapping of the Flooded Area
#### 4.2.2 Multispectral Data Analysis
The 2016 Po basin flood, south Turin area: (**B**) Proba-V 26 November 2016, **(C)** Sentinel-2 1 December 2016. Alessandria area: (**D**) Proba-V 26 November 2016; (**E**) MODIS-Aqua 26 November 2016; (**F**) Sentinel-2 8 December 2016; (**G**) the 2017 Arahal Flood with Sentinel-2. (II) In the case of the 2016 Po basin flood (Figure 9), we also calculated the NDVI\({}_{\text{var}}\) and the VIS\({}_{\text{var}}\) to extract the flooded area automatically. The areas affected by floods show a negative variation of NDVI most likely related to a decrease of vegetation activity due to the deposition of silt layers or damages (e.g., broken stems of the crop). This effect is particularly evident in the wheat fields outside the flooded areas, showing an increase of NDVI. Moreover, for the NDVI\({}_{\text{var}}\) method, the capability to detect flooded areas decreases with the time elapsed from the flood peak. This decreasing trend is independent of the spatial resolution of the satellite. The NDVI\({}_{\text{var}}\) made by using the MODIS-Aqua images collected on 30 November 2016 and 12 November 2016 at a spatial resolution of 250 m/pixel shows a clear pattern of the flooded area for both the Po (Figure 9E) and Tanaro areas (Figure 9D). Moreover, the high-resolution NDVI\({}_{\text{var}}\) based on Sentinel-2 data continues to shows a pattern of negative variation both in the South Turin area with an image acquired on 1 December (Figure 9B) and in the Alessandria area with the 8 December images (Figure 9A,C). The VIS\({}_{\text{var}}\) shows a clear pattern of positive variation only for the area flooded by the Tanaro River nearby Alessandria (Figure 9B) due to the widespread deposition of silt sediments covering the area two weeks after the inundation. The areas flooded by the Po and other rivers showed less evidence of sediment; accordingly, the VIS\({}_{\text{var}}\) analysis is less performant.
# Seismic Assessment and Strengthening of a Load-Bearing Masonry Structure Considering SSI Effects
## 3 Materials and Numerical Modeling
### FE Models
The rationale for adopting an isotropic approach probably arises from practical modeling factors and the constraints of existing material property data for historical masonry. Assessing the complete anisotropic material properties of century-old masonry would necessitate comprehensive and possibly destructive testing, which may not be practical for a functioning museum structure. Furthermore, the intricate geometry and diverse construction methods employed throughout the building could complicate the establishment of uniform directional properties. However, the mechanical contribution of the embedded timber frames is not explicitly modeled; only their self-weight is taken into account in the structural analysis. The geometric data for both models were derived from the architectural plans provided in [25]. To facilitate the modeling process and reduce computational complexity, a series of simplifications and assumptions were adopted:  
* Architectural details were simplified and elements (e.g., openings) were moved by 5-10 cm in order to reduce the number of structural nodes. Decorative elements on the facades were not simulated. * The roof was not modeled, but its loads were applied at the points of contact between the roof trusses and the masonry. * Interior and exterior staircases, as well as permanent operational loads associated with the building's function as a museum, were not included in the simulation. * The marble balcony on the main facade was not modeled; however, its loads were applied as pairs of forces and moments at its four support points. * The masonry walls were modeled with finite shell elements. The eccentricity of the masonry at each floor was taken into account--since the ground floor walls are thicker than those of the upper floors--and was modeled using the 'Area Thickness Overwrites' command. * All timber elements (roof and floor joists and ties), steel IPE beams and the RC bond beam at roof level were modeled as linear frame elements, with frame releases applied at their ends to reflect realistic connection behavior. * The 'Insertion Point' command was used on all frame elements to accurately model their eccentric positioning relative to the global geometry. * The reinforced concrete floor slab was modeled using shell finite elements. * Timber floorboards were not modeled; however, the weight of the timber floors was applied as distributed loads on the joists. * The discretization of shell elements was performed using the 'Divide Areas' command with a maximum element size of 0.5 \(\times\) 0.5 m. Frame elements were meshed using Assign Automatic Frame Mesh.
# CFD Simulation of Solid Suspension for a Liquid-Solid Industrial Stirred Reactor
###### Abstract  
The present study examines the possibility of using an industrial stirred chemical reactor, originally employed for liquid-liquid mixtures, for operating with two-phase liquid-solid suspensions. It is critical when obtaining a high-quality chemical product that the solid phase remains suspended in the liquid phase long enough that the chemical reaction takes place. The impeller was designed for the preparation of a chemical product with a prescribed composition. The present study aims at finding, using a numerical simulation analysis, if the performance of the original impeller is suitable for obtaining a new chemical product with a different composition. The Eulerian multiphase model was employed along with the renormalization (RNG) \(k\)-\(c\) turbulence model to simulate liquid-solid flow with a free surface in a stirred tank. A sliding-mesh approach was used to model the impeller rotation with the commercial CFD code, FLUENT. The results obtained underline that 25% to 40% of the solid phase is sedimented on the lower part of the reactor, depending on the initial conditions. It results that the impeller does not perform as needed; hence, the suspension time of the solid phase is not long enough for the chemical reaction to be properly completed.  
stirred tank; CFD; three-phase flow; liquid-solid; Eulerian +
Footnote †: journal: Applied Sciences
## 3 Investigation of Resilience Investment Strategies
### DER Management  
DER management is a long-term investment strategy that is applied shortly before or during an event. This study explores the following two cases of DER management:  
**Case 4**: Doubling of DER capacity (both WTGs and BESS) at each point throughout the network.
**Case 5**: Case 4 + Case 1, i.e., a hybrid investment approach.  
Table 1 shows the EENS obtained from the study for the overall system and for the critical loads. A comparison of Case 4 with the base case shows that even with doubling the investment in DER capacity across the network, the resulting improvement in resilience metrics is modest. The overall system EENS decreases by 2.08%, and the reduction for critical loads is 5.68%. A major limitation of DER-based investments lies in their reliance on the integrity of the infrastructure that connects the DERs to the loads. If this infrastructure succumbs to an extreme event, the effectiveness of DERs in enhancing resilience diminishes.  
To overcome this limitation, Case 5 explores a hybrid investment strategy. This yields a significant improvement in resilience, as seen in Table 1. The overall system EENS decreases by 11.07% and by 43.87% for critical loads compared to the results for the base case. Table 1 includes the results from Case 1, as DER investment in Case 5 is made to the system hardened in Case 1. The table shows that the hybrid strategy in Case 5 yields only a 2.82% reduction in system EENS, which is still minimal, when compared to the infrastructure hardening scenario in Case 1. However, the EENS for the critical loads experiences a substantial reduction of 17.25%, highlighting the effectiveness of the hybrid approach in significantly improving resilience for critical segments of the network.  
Table 2 presents the EOD and NDLH values for the base case, Case 4, and Case 5. Both metrics show improvement with increased investment, following a trend similar to that observed for EENS. Case 5, in particular, demonstrates a notable enhancement in system performance as a result of the hybrid investment strategy. An important observation is that the gap between EOD and NDLH widens with higher levels of investment. The difference between these two metrics increases from 3.98% in Case 4 to 6.04% in Case 5. This growing gap highlights the increasing relevance of the NDLH index as system resilience investments become more substantial.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Case**} & **EENS for Overall System** & **EENS for Critical Loads** \\  & **(Mwhr/int)** & **(Mwhr/int)** \\ \hline
**Base case** & 16.44 & 0.75 \\ \hline
**Case 4** & 16.10 & 0.71 \\ \hline
**Case 5** & 14.62 & 0.42 \\ \hline
**Case 1** & 15.05 & 0.51 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of EENS for Case 4 and Case 5.
## 3 LWE-CP-ABE Scheme
### Security Model  
The proposed CP-ABE scheme is selectively secure under linear independence restriction in the random oracle model if the LWE assumption holds. To prove this assumption, the hybrid security game contains a challenger and an adversary. The challenger simulates the system and answers the adversary's inquiries. The hybrid game starts as follows.  
(1) Setup phase. The reduction algorithm receives a security parameter \(1^{\lambda}\) and an access control policy \((\mathbf{M},\rho)\) from the challenger and invokes an adversary. The challenger runs the **Setup** algorithm to generate the system **PK** and send it to the adversary.  
(2) Secret key queried by an adversary. For each key query, the adversary sends a set of attributes \(\mathbf{U}\in\mathbb{U}\), but these attributes do not satisfy the access control policy \((\mathbf{M},\rho)\). The challenger runs the **KeyGen** algorithm and sends the generated user attribute SK to the adversary.  
(3) Challenge phase. To generate the challenge ciphertext, the challenger selects a random bit \(b\leftarrow\{0,1\}\) and runs the **ENC** algorithm to encrypt it using the access control policy. Consequently, the challenger provides that to the adversary.  
(4) Repeat step (2).  
(5) Guess phase. The hybrid game terminates with an adversary outputting its guess \(b^{\prime}\leftarrow\{0,1\}\) for the bit \(b\) encrypted within the challenge ciphertext.  
The advantage of the adversary \(\mathcal{A}\) in this game is:  
\[\mathrm{Adv}^{\text{LWE-CPABE, SEL-CPA}}_{\mathcal{A}}(\lambda)\triangleq \left|\Pr\left[b=b^{\prime}\right]-1/2\right| \tag{15}\]  
**Definition 2**.: _If there exists a negligible function **negl**\((\cdot)\) for any PPT adversary \(\mathcal{A}\), for all \(\lambda\in\mathbb{N}\), there is \(\mathrm{Adv}^{\text{LWE-CPABE, SEL-CPA}}_{\mathcal{A}}(\lambda)\leq\textbf{negl}( \lambda)\). The LWE-CP-ABE scheme proposed in this paper is selectively secure under linear independence restriction._
# Three-Dimensional-Bioprinted Liver Chips and Challenges
## 2 Material  
**Bioinks:** The most commonly used natural polymeric hydrogel-based bioinks for 3D bioprinting are dECM, agar (or agarose), alginate, silk, gelatin, collagen, hyaluron, fibrinogen, and chitosan [79]. The bioink should be selected based on the proposed 3D bioprinting method (e.g., photo-curable bioink for light-induced printing and bioink with shear-thinning ability for extrusion-based bioprinting). Hybrid bioinks are introduced to modify the mechanical properties of current bioinks. For example, pure alginate, although widely used, biocompatible, and readily processable, has poor pattern fidelity and printability. However, the combination of it with cellulose nanocrystals (CNCs) (whisker/rod-shaped nanoparticles obtained from the crystalline regions of cellulose fibers and characterized by high mechanical strength, renewability, low cytotoxicity, and low density) results in a strengthened bioink with shear-thinning capability, which can be printed through a 100 \(\upmu\)m nuzzle without clogging [49]. Using this hybrid bioink, a liver-memetic construct was printed with high cell viability, demonstrating the superior protection ability of hybrid bioinks to protect encapsulated cells from the mechanical stress of the extrusion process [49]. **Microfluidic chips:** PDMS is an intriguing candidate for the fabrication of microfluidic chips. PDMS can be plasma-treated, which allows manipulation of surface properties as well as the interconnection of multiple layers to fabricate complex 3D microfluidic structures suitable for OOC applications. In addition, PDMS is deformable, which enables programmed transport of fluids (e.g., reagents) through pneumatically controllable deformation of microchannels [6]. Moreover, as a consequence of the elasticity of PDMS, the natural cyclic stretching of organs (e.g., lungs and heart) can be mechanically mimicked on PDMS microchannels to create more realistic models of organs on a chip. In addition to the transparency of PDMS, which enables optical microscopy, PDMS is biocompatible and gas-permeable (e.g., oxygen), allowing biological experiments to be performed. However, the flexibility of PDMS may lead to undesirable distortions, while the gas permeability can lead to bubble formation in channels and evaporation of fluids due to the high surface-to-volume ratio. Furthermore, PDMS can absorb and leach hydrophobic drugs/compounds used in the culture chamber. Polyurethane elastomers, thermoplastics, and styrene-ethylene/butylene-styrene are alternatives to PDMS for OOC applications that are not widely used, although they are castable, flexible, and drug-inert [80]. Moreover, coating PDMS with paraffin or parylene can attenuate the drug absorption of PDMS while compromising cell attachment [6]. Poly(ethylene glycol) (PEG) is a widely used ink for the construction of spatially heterogeneous and complex structures such as hollow-shaped frameworks, as it is a tunable