esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Application of DT to Sustainable Cities under Climate Change  
### Decarbonization of the Energy Sector  
Decarbonization of the energy sector is one of the most significant approaches to the fulfilment of the goal of net-zero emissions by 2050 [17, 18], and DT has already been employed to steer a transformative path to renewable energy systems. [PERSON] et al. developed a DT-driven, autonomous energy management system (EMS), which aims at improving the energy efficiency of residential buildings and neighbourhoods [19]. This system has been applied to Rinascimento III in Rome, a neighbourhood consisting of a total of 16 eight-floor buildings, where the self-renewable energy covers 70% of the whole power consumption. The case-study outcome demonstrated that such an EMS is able to balance the trade-off between the comfortability and energy efficiency under dynamic climate conditions.  
In parallel, [PERSON] et al. looked into the deployment of a fleet of unmanned aerial vehicles (UAVs) across future smart cites as another approach to the reduction in GHG emissions [20]. To that end, a DT of a real-world metropolitan city was first established in this study, incorporating the LiDAR city model, the 3D GIS model, the origin-destination matrix of the UAVs, the utilizable air space, as well as the solar exposure profiles. Furthermore, an integrated multi-objective optimization model, which maximizes UAVs' coverage range and minimizes the total cost of energy and decarbonization was proposed. Based on such a model and the DT, a total of 12,532 daily missions were modelled across the case-study area. The results showed that the UAV fleet can play a crucial role with regard to the reduction in GHG emissions and the shift to renewable energy in large-scale cities.  
At the regional level, [PERSON] et al. established a modelling framework on the real-time operation of medium-voltage DC (MVDC) electric railway systems (ERSs) [21], which could facilitate the use of renewable power sources, energy storage systems and distributed generation units [22]. Based on the established DT model of MVDC, alongside that of the corresponding auxiliary power supply sources (including the photovoltaics plant, wind farm, and EV charging infrastructure), the Rome-Florence high-speed railway line was investigated as a real-world case study. The research revealed that the performance of the ERSs can be further improved, owing to the integration of renewable power sources, and it is therefore ready to serve as an eco-friendly, sustainable transport system in the coming years.
# Offline Payment of Central Bank Digital Currency Based on a Trusted Platform Module
## 1 Introduction  
With the rapid digitization of finance worldwide, the emergence of cryptocurrencies, such as Bitcoin, serves as a significant catalyst for change in payment and settlement systems. Traditionally, financial institutions have acted as intermediaries for payment methods, generating various revenues from payment services. However, the rise of cryptocurrencies, which operate without intermediaries, heralds a revolutionary shift in this conventional system. Furthermore, as finance continues to digitize, current electronic payment methods remain largely based on cash. Since cryptocurrencies are not tied to cash, central banks globally recognize them as competitors to cash and are closely monitoring their proliferation [1, 2]. Additionally, central banks have begun to explore the feasibility of issuing cryptocurrency like Central Bank Digital Currencies (CBDCs) [3, 4]. However, there are numerous limitations associated with the use of CBDCs. Generally, CBDCs inherit the constraints of electronic payment method, including issues related to anonymity and offline transactions [5, 6, 7]. In particular, offline environments are isolated and can be vulnerable to numerous breaches, making them risky and challenging for immediate attack detection. In this study, a CBDC model is proposed to facilitate peer-to-peer (P2P) payments in a completely offline environment. Most CBDCs currently under research require an onlineconnection, similarly to existing electronic payment systems or cryptocurrencies. Therefore, it is crucial to develop a CBDC that can operate in environments without an online network, akin to cash transactions. Our proposed model incorporates several security elements, including a Trusted Platform Module (TPM), a secure hardware device, and JSON Web Tokens (JWTs) that contain digital signatures. The remainder of this paper is organized as follows: Section 2 introduces the literature review of this study. Section 3 describes our method, notation, and the detailed protocol of our model. In Section 4, we analyze the results and discussions. Finally, we conclude in Section 5.
## 4 Conclusions  
This study demonstrated that commercially available and inexpensive enzyme preparations containing pectinase and xyloglucanase have a synergistic effect in removing the hydrophilic pectin and hemicellulose materials from flax yams, which was confirmed by FT-IR and TGA analyses. From a microstructural point of view, the biochemical treatment resulted in a cleaning effect on the fiber surface, with an increase in thermal stability and a reduction in mechanical properties depending on the enzyme concentration and treatment duration. By taking advantage of the reduced hydrophilic behaviour and increased individualization of flax yams, an improvement in the fibre/matrix compatibility with epoxy and vinylester matrices was obtained. After exposure to enzymatic treatments, single yarn fragmentation tests highlighted smaller debonding and critical yarn length values, especially with the fully dispersive vinylester matrix. Enzymes, being relatively inexpensive, recyclable and less energy intensive, represent a green and promising surface-modifying agent for natural fibres intended for composite applications.  
Conceptualization, F.S., F.T., and L.C.-A.; methodology, F.S., A.Z., R.L. and F.T.; validation, F.S., J.T., and M.C.S.; formal analysis, M.C.S.; investigation, M.C.S. and M.P.B.; data curation, M.C.S., L.C.-A., and J.T.; writing--original draft preparation, M.C.S., J.T. and F.S.; writing--review and editing, M.P.B., A.Z., R.L., F.T. and L.C.-A.; visualization, M.C.S.; supervision, F.S., J.T., and F.T. 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 9: Representative debonding length observation by micro computed tomography. High resolution micro-CT images for the Peclyve 10 wt %/6 h treated flax/epoxy (**A**) and flax/vinylester (**B**) single yarn samples.
## Materials and Methods
### Characterization of PSPE
#### 2.5.2 UV and FT-IR Spectra  
UV spectrum of PSPE solution (1.0 mg/mL) was recorded on a double beam UV spectrophotometer (TU-1901, Beijing Purkinje General Instrument Co., Ltd., Beijing, China) in the wavelength range of 200 to 400 nm. 5.0 mg PSPE and KBr powder were mixed and then pressed into 1 mm pellets. FT-IR spectrum was measured on Fourier transform infrared spectrophotometer (ALPHA-T, BRUKER Co., Billerica, MA, USA) in the wave number region (4000-400 cm\({}^{-1}\)).
## 5 Conclusions  
The major outcomes of our analysis can be summarized in the following. (i) Fluoxetine has antioxidant capacity acting as ROS scavenging via the HAT mechanism, and is selective for hydroxyl and methoxyl radicals. (ii) Scavenging may occur also via the RAF mechanism involving the C sites of the benzene rings. (iii) Serotonin is overall a better scavenger of hydroxyl and peroxyl radicals and, thanks to the presence of the alcoholic group, as in **M2**, which is one identified metabolite of fluoxetine, displays antioxidant activity also toward peroxyl radicals. These observations support the hypothesis that the clinical evidence of improvement of oxidative damage associated to fluoxetine therapy is likely due to the enhanced concentration of free serotonin, i.e., is an indirect effect.  
Due to the seriousness of depressive disorders and their social implication, strategies to improve clinical symptoms are of considerable importance; particularly, the antioxidant capacity combined with the main therapeutic action of existing drugs is an idea that should be further investigated, and likely screened in silico as well as tested in vitro/vivo.  
The following are available online at [[http://www.mdpi.com/2076-3417/9/17/3631/s1](http://www.mdpi.com/2076-3417/9/17/3631/s1)]([http://www.mdpi.com/2076-3417/9/17/3631/s1](http://www.mdpi.com/2076-3417/9/17/3631/s1)): Tables S1-S6 (Gibbs free reaction and activation energies in the gas phase and solvents of the HAT and RAF processes here described); Cartesian coordinates of all the intermediates and transition states reported in this work.  
Conceptualization, L.O., G.Z. and C.P.; methodology, L.O.; investigation, C.M. and M.D.T.; resources, L.O.; data curation, C.M., M.D.T. and G.R.; writing--original draft preparation, L.O., C.P. and G.R.; writing--review and editing, L.O. and G.Z.; visualization, M.D.T.; supervision, L.O.; funding acquisition, L.O.  
This research was funded by the Universita degli Studi di Padova, thanks to the P-DiSC (BIRD2018-UNIPD) project MAD\({}^{3}\)S (Modeling Antioxidant Drugs: Design and Development of computer-aided molecular Systems); P.I. L.O. All the calculations were carried out on Marconi (CINECA: Casalecchio di Reno, Italy) thanks to the ISCRA Grant REBEL2 (ERdox state role in Bio-inspired ELementary reactions 2), P.I.: L.O.; M.D.T. is grateful to Fondazione CARIPARO for financial support (Ph.D. grant).  
The authors declare no conflict of interest.  
Figure 6: Spin densities on (1-H) \({}^{\bullet}\) when HAT occurs from C1 (**a**) (1 OH) \({}^{\bullet}\) when RAF occurs at C1 (**b**). Level of theory: (SMD)-M06-2X/6-311+G(d,p)//M06-2X/6-31G(d).
# A Novel Approach to Short-Term Stock Price Movement Prediction using Transfer Learning
## 6 Experimental Results
### Performance Based on Different Numbers of Similar Companies  
In this subsection, we concentrate on examining the influence of the number of stocks from a field similar to the COI stock when predicting stock price movement. The number of stocks varies: \(m=\{3,5,7\}\).  
As shown in Table 7, the performance of predicting stock price movements of each company dramatically depends on the value of \(m\). Specifically, \(m=7\) displays the lowest performance at 55.93% average accuracy. However, with Hyundai Motor Co. and LG Chem, \(m=7\) achieves remarkable performance at 64.22% and 56.87% average accuracy, respectively, compared to the others.  
In addition, both \(m=3\) and \(m=5\) obtain similar performances at 57.97% and 57.62% average accuracy. In the Korean market, unlike Hyundai Motor Co. and LG Chem, the performance from stock price movement prediction for two companies (Samsung Electronics Co. and SK Hynix Inc) is the highest when \(m=3\). For instance, with Samsung Electronics Co., \(m=3\) achieves 59.42% average accuracy, compared to 56.56% and 52.39% average accuracy when \(m=5\) and \(m=7\), respectively. A similar trend is present in the US market, as shown in Table 7, particularly, for Apple Inc., with only 52.68% average predictive accuracy when \(m=7\), compared to 58.96% average accuracy when \(m=3\) (a broad difference of 6.18 percentage points).  
It should be highlighted that the value of \(m\) is considered as a hyperparameter of the prediction model and this value should be chosen carefully for each company.
## 4 Influence of 3D Printing Parameters on the Fatigue Life of FFF Prints
### Nozzle Diameter  
The diameter of the nozzle has an influential impact on the quality and mechanical strength of FFF prints. It has been shown that the print quality and tensile strength of FFF prints improve when extruders with larger orifices are used [85; 86; 87]. However, depending on the loading type and printed material, the nozzle diameter exhibits a different impact on the fatigue life of 3D-printed objects. For example, [PERSON] and [PERSON] [35] reported that under flexural fatigue loading, the number of cycles to failure for ABS samples printed with a 0.8 mm nozzle was almost double the corresponding number for samples 3D-printed with a 0.4 mm nozzle. This was mainly because a higher nozzle diameter produces prints with lower void defects, resulting in higher stiffness and less stress concentration.  
Similar studies for ABS [64], PLA [65; 66; 67], and PLA-wood composite [18] prints under rotating bending fatigue demonstrated an uncertain relationship between the nozzle diameter and fatigue performance. Increasing the nozzle diameter from 0.3 to 0.5 led to an increase in the number of cycles to failure in PLA prints from around 1500 to 1800, 1200 to 2000, and 100 to 500 cycles in ABS, PLA, and PLA-wood composite prints, respectively. The same observation was reported for ABS prints in which the signal-to-noise ratio was reported to be 17.4% for the nozzle diameter, demonstrating the significant effect of this parameter on rotating bending fatigue strength [64]. This is while an inverse correlation between the nozzle diameter and fatigue life was observed in the work of [PERSON] and [PERSON] [65]. These researchers printed PLA samples using three different nozzle diameters, i.e., 0.2, 0.4, and 0.6 mm, and studied their behaviour under rotating bending loads. A smaller nozzle size was shown to result in higher fatigue life. Although different printing conditions and materials can cause a discrepancy in results, further investigations are needed to fully understand the effect of the nozzle diameter on the fatigue behavior of FFF prints, as highlighted by [PERSON] et al. [64]. Further, it should be noted that downsizing the nozzle orifice may cause mechanical strength degradation. It was reported that the nozzle diameter should be at least 1.5 times higher than the layer height for proper filament bonding [64; 67], which was confirmed in another study by [PERSON] et al. [18].
## 5 Experimental Evaluation
### Comparative Results  
We compare Edge-FLGuard+ against three baseline approaches:  
* Centralized Model (C-AE): A GRU-based autoencoder trained on all data centrally.
* Local-Only Model (L-AE): Edge nodes train independently without collaboration.
* Vanilla Federated Model (F-AE): FL with no optimizations or privacy layers. To evaluate the effectiveness of Edge-FLGuard+, we compare its performance against centralized, local-only, and vanilla federated baselines using key metrics such as accuracy, F1-score, latency, and communication overhead. These results are presented in Table 2.  
To visually highlight performance differences across baseline and proposed models, we present a comparison of accuracy, F1-score, and false positive rate in Figure 3.  
Edge-FLGuard+ demonstrates superior trade-offs between accuracy and overhead compared to both isolated and centralized models.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Model** & **Accuracy** & **F1-Score** & **FPR** & \
\begin{tabular}{c} **Latency** \\ **(ms)** \\ \end{tabular} &
\begin{tabular}{c} **Comm. Overhead** \\ **(MB/Round)** \\ \end{tabular} \\ \hline C-AE (Centralized) & 97.1\% & 0.962 & 2.3\% & — & — \\ L-AE (Local Only) & 88.4\% & 0.871 & 6.2\% & 6.7 & 0 \\ F-AE (Vanilla FL) & 95.2\% & 0.946 & 3.5\% & 7.1 & 3.8 \\ Edge-FLGuard+ & 96.4\% & 0.954 & 2.6\% & 6.8 & 2.1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparative performance of Edge-FLGuard+ against centralized (C-AE), local-only (L-AE), and standard federated (F-AE) baselines. Edge-FLGuard+ demonstrates a favorable balance between detection accuracy and communication efficiency in 5G-enabled smart home environments.  
Figure 3: Performance comparison of Edge-FLGuard+ with centralized (C-AE), local-only (L-AE), and standard federated (F-AE) models. Edge-FLGuard+ offers a balanced trade-off between detection performance and resource efficiency.
###### Abstract
However, most prior studies focus on single-variable prediction, and few have assessed the impact of multi-variable, AI-based forecasts on NMPC performance. In parallel, real-time NMPC is often hindered by the computational burden of repeatedly solving large-scale, constrained nonlinear optimization problems. Warm-start techniques, which leverage previous solutions to accelerate convergence, have shown significant promise in other application domains [6], but their practical impact in greenhouse NMPC--especially when coupled with advanced disturbance prediction--remains largely unexplored. While progress has been made, there is still no systematic study that jointly evaluates the control and computational performance of NMPC under different disturbance forecasting strategies. To address these limitations, this study proposes an AI-enhanced NMPC framework in which a single multi-output LSTM network is trained to jointly forecast all major external disturbances--outdoor temperature, humidity, CO\({}_{2}\) concentration, and solar radiation--relevant to greenhouse climate control. By capturing temporal dependencies and nonlinear relationships among these variables, the LSTM model delivers comprehensive, realistic forecasts for proactive climate regulation. Furthermore, to provide a thorough and fair assessment, this work conducts a unified comparative study of three NMPC configurations: (1) feedback-only NMPC, assuming constant disturbances; (2) LSTM-based predictive disturbance NMPC, utilizing joint multi-variable AI-based disturbance prediction; and (3) ideal predictive disturbance NMPC, using true future disturbance profiles as an upper-bound benchmark. The practical value of warm-start optimization is also systematically investigated across all configurations. Utilizing a detailed lettuce greenhouse model [7] and extensive 40-day simulations, the effectiveness of feedback-only, predictive, and ideal preview controllers--with and without warm-start--is rigorously assessed using comprehensive key performance indicators (KPIs) such as final biomass yield, setpoint adherence, resource consumption, net profit, and solver computation time. The findings of this research are expected to provide valuable, actionable insights for both researchers in control engineering and agricultural systems, as well as practitioners seeking to implement advanced AI-enabled control solutions for optimal greenhouse environmental management. The remainder of this paper is organized as follows: Section 2 reviews related literature. Section 3 details the greenhouse model. Section 4 describes the NMPC formulation, controller variants, and performance metrics. Section 5 outlines the simulation setup. Section 6 presents and discusses the results, and Section 7 concludes the paper.
## 1 Introduction
In contrast to works that specify the necessary filter for each derivative [26], both HO-PID [25] and HO-AR [17] controllers use a much more efficient design of a single \(n\)th-order binomial filter  
\[Q_{n}(s)=Y_{f}(s)/Y(s)=1/\Big{(}T_{f}s+1\Big{)}^{n}=1/P_{n}(s) \tag{8}\]  
The above-mentioned joint filter can also be seen as a generalization of the approach used in [8]. The combination of \(Q_{n}(s)\) with an ideal \(PD^{m}(s)\) controller (6), for \(n\geq m\), yields fully realizable \(PD_{n}^{m}(s)\). Furthermore, in combination with AR (5) and saturation non-linearity, this yields the \(PD_{n}^{m}R\) controller. For a comparison, the approach in [26] requires the computation of three first-order differential equations for the implementation of PIDA controller filters. However, a joint filter (8) based on three equations provides access to the first, second and third derivatives of the output (see, e.g., [23]). If only the first two derivatives are used, the \(PD_{3}^{2}R\) controller can contribute to more effective noise attenuation. The common filter (8) has the furtheradvantage that all components contained in the control signal (7) are delayed in the same way. When using controllers with HO derivatives, the simplification by using only one filter becomes even more obvious. When designing HO-ARCs, it is still sufficient to use an IPDT model with two unknown parameters as in simple PI or AR controllers. Moreover, the proposed method takes into account the POCD requirements and it simplifies the process identification as it uses a simpler process model than SOPUZ (see, e.g., [11]). The optimization phase of the controller is then reduced to the selection of a derivative degree \(m\) and a suitable low-pass filter required for the implementation of the controller and noise attenuation. The choice of the filter depends on the stability requirements, the closed-loop speed, the maximum overshoot and undershoot, the attenuation of the measurement noise, and the constraints of the control signal. The rest of this article is organized as follows. Section 2, extended by Appendix A, briefly summarizes the MRDP rules for setting \(PD_{n}^{m}R\) controllers for IPDT models. A sample of HO-ARCs based on a simple inverse process approximation without measurement noise is presented. Section 3 provides a more detailed analysis of process noise using the speed-effort (SE) and speed-wobbling (SW) characteristics. The practical limitations of linear and constrained controller designs are analyzed in Section 4. Sections 5 and 6 discuss and summarize the lessons learned and make suggestions for future research.
# Characterization of the Solution of the Seismic Source Mechanism in Southeastern Sichuan
## 2 Geological Settings  
The convergence of the Indian and Eurasian plates has led to the uplift of the Tibetan Plateau [24, 25]. The eastward extrusion of the Tibetan Plateau material, obstructed by the Yangtze Craton, has formed the Longmen Shan orogenic belt along the eastern margin of the plateau and the adjacent Sichuan foreland basin [26, 27, 28]. Located on the western edge of the Yangtze Craton, the Sichuan Basin possesses a rigid Precambrian crystalline basement, with its top boundary gradually rising from northwest to southeast, ranging in depth from approximately 13 km to 7 km [29]. In contrast to the tectonically active and seismically frequent Longmen Shan orogenic belt, the interior of the Sichuan Basin exhibits high structural stability, with a very low present-day strain rate (4-8 \(\times\) 10\({}^{-9}\)/year) [30, 31]. Historically, the basin has experienced almost no strong earthquakes with magnitudes exceeding 6.0 [4].  
Since the Indosinian period, the Sichuan Basin has undergone multiple phases of tectonic activity influenced by surrounding orogenic belts, resulting in the superposition of multiple sets of structures. From west to east, the basin can be divided into three main tectonic units [32, 33] (Figure 1a). Among them, the western subsidence zone is bounded by the Longmen Shan Fault Zone to the west and the Longquan Shan Fault Zone to the east. Its tectonic features are controlled by the compressive effect of the Longmen Shan Fault Zone, with the development of a series of northeast-trending thrust faults and related folds. The central dome zone lies between the Longquan Shan Fault and the Huaying Shan Fault, where gentle dome structures are widely developed. The closure conditions at the top and slope areas of the domes are favorable, and the carbonate reservoirs of the Middle Triassic and Lower Permian contain a large amount of conventional natural gas resources. The eastern fold zone is mainly bounded by the Huaying Shan Fault Zone and the Dalu Shan Fault, with the development of a series of northeast-trending tight linear folds, such as the Huaying Shan Anticline and the Changning Anticline. The regional fracture system is relatively complex, with a high density of high-angle reverse faults and local strike-slipfaults, which jointly control the distribution of the stress field and the development of folds. Within the fold zone, the Silurian Longmaxi Formation is rich in organic shale, providing good fracture network conditions for the occurrence of shale gas.