esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background and Related Work
### Large Language Models
Self-supervised learning tasks such as the MLM task are a common and effective choice:  
\[\mathcal{L}_{\text{MLM}}=-\sum_{i\in\mathcal{M}}\log p(x_{i}|x_{\setminus i}; \Theta). \tag{3}\]  
Here, \(\mathcal{M}\) is the index set of tokens selected for masking, \(x_{i}\) represents the \(i\)-th token in the sequence, \(x_{\setminus i}\) denotes the other tokens excluding \(x_{i}\), and \(\Theta\) refers to the model parameters. The MLM task promotes the model's ability to capture and learn the deep semantic information of text by predicting the masked tokens in the sequence. After the pretraining stage, fine-tuning the model on specific attack behavior detection tasks is a necessary step. The fine-tuning process mainly involves optimizing the following loss function:  
\[\mathcal{L}=-\sum_{(x,y)\in\mathcal{D}}\log p(y|x;\Theta^{\prime}). \tag{4}\]  
Here, \((x,y)\) represents the labeled sample pair, \(\mathcal{D}\) is the training dataset, \(y\) is the label of the sample, indicating whether the sample is \"normal\" or \"attack\" behavior, and \(\Theta^{\prime}\) are the fine-tuned model parameters. Through this step, the model learns how to predict the corresponding label \(y\) based on the input data \(x\), thereby achieving accurate detection of network attack behaviors. As discussed, applying large language models to network attack behavior detection requires careful design of input representations and pretraining tasks as well as effective fine-tuning on specific detection tasks [33]. These steps collectively ensure that the model can fully leverage its language understanding capability to accurately identify and analyze potential network attack behaviors. To overcome these challenges, researchers must meticulously adjust the model's pretraining and fine-tuning strategies to ensure that it captures the specific knowledge and language patterns of the cybersecurity field. Additionally, incorporating domain experts' knowledge into model training and evaluation is key to enhancing model performance. Lastly, in light of the severity of cybersecurity incidents, the interpretability and trustworthiness of models are non-negligible factors. Researchers need to develop new methods to ensure that the model's decision-making process is transparent and can provide reliable evidence to support its detection results. In summary, the development of large language models offers new technical means and research directions for network attack behavior detection. By delving into these models' potential and continuously adapting to the specific needs of the cybersecurity field, detection capabilities with respect to network attack behaviors can be effectively enhanced, making a significant contribution to maintaining network security. As model design, training strategies, and application methods continue to innovate and optimize, future large language models will have even broader prospects in the field of network attack behavior detection.
# Benchmarking of Load Forecasting Methods Using Residential Smart Meter Data
###### Abstract  
As the access to consumption data available in household smart meters is now very common in several developed countries, this kind of information is assuming a providential role for different players in the energy sector. The proposed study was applied to data available from the Smart Meter Energy Consumption Data in the London Households dataset, provided by UK Power Networks, containing half-hourly readings from an original sample of 5567 households (71 households were hereby carefully selected after a justified filtering process). The main aim is to forecast the day--ahead load profile, based only on previous load values and some auxiliary variables. During this research different forecasting models are applied, tested and compared to allow comprehensive analyses integrating forecasting accuracy, processing times and the interpretation of the most influential features in each case. The selected models are based on Multivariate Adaptive Regression Splines, Random Forests and Artificial Neural Networks, and the accuracies resulted from each model are compared and confronted with a baseline (_Native_ model). The different forecasting approaches being evaluated have been revealed to be effective, ensuring a mean reduction of 15% in Mean Absolute Error when compared to the baseline. Artificial Neural Networks proved to be the most accurate model for a major part of the residential consumers.  
load forecasting; smart meter; residential consumption; Random Forest; Artificial Neural Networks +
Footnote †: journal: Applied Sciences
###### Abstract
For example, [PERSON], [PERSON], and [PERSON] studied the influence of PT symmetric lattices on the collapse of vortex beams in Kerr medium and found that PT symmetric lattices can cause asymmetric collapse, which provides a new idea for controlling beam collapse [19]. These research results provide a theoretical basis and experimental guidance for the application of PT symmetric media in the fields of optical device design, optical information processing, new optical materials, and optical fiber sensing. The existing research on the use of bright solitons [20; 21], Airy beams [22], and cosh-Airy beams [23] in PT symmetric lattices mainly focuses on the characteristics of shedding solitons. However, the research on the dynamic behavior of more complex beam structures (such as Airyprime beams) when propagating in PT symmetric lattices is still insufficient. In particular, the formation mechanism of oscillating solitons and the energy ratios of the remaining self-accelerating and self-restoring beams, including how they are controlled by the initial parameters of the lattice and the beam, still lack systematic discussion. This research introduces a novel type of mutation beam (Airyprime beams) that propagates in PT-symmetric optical lattices, during which it sheds oscillatory. This not only increasesthe diversity of solitons but also enhances the security of information transmission. Additionally, Airyprime beams demonstrate strong robustness in complex optical systems, maintaining stable propagation even under disturbances. This characteristic makes them less susceptible to external interference or manipulation in complex environments, and thereby enhances the confidentiality and security of information that is transmitted using Airyprime beams. Given the above shortcomings, this study aims to explore the transmission characteristics of Airyprime beams in PT symmetric optical lattices, focusing on the generation and control mechanism of oscillating solitons. By analyzing the effects of lattice parameters (such as the modulation depth and frequency) and initial beam characteristics (such as the truncation coefficient and peak intensity), this study attempts to reveal the internal physical mechanism of the dynamic behavior of oscillating solitons. The innovation of this study lies in determining a method for to precisely control the generation of oscillating solitons by optimizing the lattice configuration and beam control, which provides theoretical support and experimental guidance for beam shaping, optical path design, and nonlinear optical manipulation. It provides a new idea regarding advanced optical manipulation in complex optical environments and has important theoretical significance and application value.
# Blockage Effects in Wind Tunnel Tests for Tall Buildings with Surrounding Buildings
###### Abstract  
To study the blockage effects in wind tunnel tests for tall buildings with surrounding buildings and establish a reasonable calculation method for the blockage ratio, this paper carried out fifty-one test conditions of pressure model wind tunnel tests with three scale ratios. The tests considered the relative location, relative height, and model number of the surrounding buildings to those of the target building by the rigid pressure models. Based on the wind tunnel tests, the blockage effects on the pressure coefficients and drag coefficients were studied in detail. The results showed that the blockage effects were different when the relative positions of the surrounding models to the target model were different, even if the blockage ratio was the same. The blockage effects caused by the surrounding models with unit blockage ratio were usually more significant than those caused by the target pressure-measuring model itself. The existing correction methods for the blockage effects are mainly derived from the wind tunnel tests of an isolated building model. Using existing calculations to evaluate the blockage effect of wind tunnel tests for tall buildings with surrounding buildings may result in obvious deviations. Finally, the concept of the equivalent blockage ratio was proposed, which can be used to calculate the blockage ratio of wind tunnel tests of tall buildings with surrounding buildings. The proposed calculation method of this equivalent blockage ratio can provide a reference for the determination of scale ratios for wind tunnel test models of tall buildings.  
blockage effect; wind tunnel tests; grouped tall buildings; calculation method +
Footnote †: journal: Applied Sciences
## 3 Results  
### Chronology Framework and Sedimentary Rates  
The chronology for core SO-31 was based on the AMS \({}^{14}\)C dating data with a composite age-depth model (Table 1 and Figure 2). The indication of the core had a 2\(\sigma\) basal age of ca. 12,674-13,026 calibrated years before present (cal. yr. BP), which corresponded to a median sedimentation rate of 0.057 cm per year (cm/yr). According to the age-depth model illustrated in Figure 2, the sedimentation rate of this studied core ranged from 0.012 cm/yr to 0.140 cm/yr. Intervals of increased sedimentation accumulation rate (exceeding 0.057 cm/yr) were observed during two periods dated to cal. 12,828-10,667 cal. yr. BP and 5137 cal. yr. BP to the present, whereas the lowest-rate period (below 0.02 cm/yr) occurred ca. 10,667-5137 cal. yr. BP (Figure 2). The sediment dating data of SO-31 are largely consistent with the findings reported by [PERSON] et al. for SO219/31-4 [13], likely due to the proximity of the two sites (less than 500 m apart). Minor discrepancies of datasets between the SO-31 and SO219/31-4 can be attributed to variations in the specific locations and depths of the sampled sediments.  
Figure 2: Geological column and down-core variations in mean grain size (MZ) and major elements of the core SO-31 sediments show the change in the sedimentary environment. Dashed horizontal lines indicate the boundaries between depositional units (Unit 1, Unit 2, and Unit 3). The nine ages marked with arrows in geologic column were obtained by the AMS \({}^{14}\)C dating.
# Cooperation-Assisted Spectrum Handover Mechanism in Vehicular Ad Hoc Networks
## 3 Proposed Scheme  
This section will describe our cooperation-assisted spectrum handover (CASH) scheme in detail. Figure 4 shows the concept of the cooperation-assisted spectrum handover. PU is the primary vehicle and SU is the secondary vehicle. Each PU communicates with a BS and other SUs at the same time because it is equipped with multiple antennas. In addition, each vehicle can obtain the spectrum information of neighboring BSs in advance through multi-hop V2V communications; it then makes the best handover decision. When the PU or SU hands over the new BS, it directly switches to the selected spectrum without scanning the overall spectrum. Therefore, the CASH scheme can save the scanning time and mitigate the impact of switching spectrum (e.g., packet loss and performance degradation).
# Effect of Controlled Expiratory Pressures on Cerebrovascular Changes During Valsalva Maneuver
## 2 Materials and Methods
### Measurements  
The experimental instruction and the biosignal measurement were assigned to different experimenters following single-blind procedures. Changes in blood velocity and function in the CCA were measured to investigate their effects on VM. Changes in CCA blood velocity during the VM were measured using diagnostic ultrasound with a 2-14 MHz linear transducer array (RS85, Samsung Medison, Seoul, Republic of Korea). The parameters, including peak systolic velocity (PSV), HR, and resistance index (RI), were obtained using Doppler-mode scanning. The RI is a widely used measure of resistance to arterial flow (RI = (PSV\(-\)EDV)/PSV; EDV, end-diastolic velocity). This reflects not only the resistance at the measurement site but also the resistance distal or downstream to the ultrasound probe. Functional changes in the CCA caused by the VM were evaluated using pulse wave velocity (PWV) and arterial stiffness index. To calculate the PWV and stiffness index, CCA diameters (including systolic and diastolic) were obtained using B-mode axial CCA images, and BP was obtained using a smartwatch (SM-R850, Samsung Electronics, Suwon, Republic of Korea) after being calibrated for each participant before the experiment. To calibrate the smartwatch's BP, an electric blood pressure monitor (TMB-1112 upper arm blood pressure monitor with cuff) was used. The location of the CCA for measurement was determined using an ultrasound image 2 cm below the CCA bifurcation. Hemodynamic changes in the brain were measured using near-infrared spectroscopy (NIRS) (NIRSIT ON, OBELAB, Seoul, Republic of Korea). Regional oxygen saturation (rSO2) and oxyhemoglobin (HbO) were obtained in the left and right prefrontal cortices using NIRS. NIRS patches were attached above both eyebrows on the left and right prefrontal cortex [20].  
Data collection was conducted according to the time flow (Figure 3). NIRS data were continuously collected in real-time for approximately 80 s, including both before and after the VM. Doppler ultrasound measurements were taken for 15 s before the VM and 30 s after the B-mode measurement for 5 s after the VM. BP and B-mode measurements started simultaneously.  
Doppler measurements were collected 15 s before VM (PRE) and 30 s after VM (POST1 and POST2), in which the resulting data was divided into two sessions of 15 s each, POST1 and POST2, for further analyses. According to a previous study, the normalization time of BP after VM was confirmed to be less than 15 s [21]. CCA diameters and BP were measured before and after VM to calculate PWV and stiffness index. B-mode images were acquired immediately before Doppler mode measurement. Doppler and B-mode measurements during the VM were not performed because of neck muscle contraction and blood vessel movements. No follow-up was performed, and all data were collected at Gachon University.
# Image Dehazing Algorithm Based on Deep Learning Coupled Local and Global Features
## 2 Atmospheric Scattering Model  
In computer vision, the atmospheric scattering physical model is usually used to simulate the degradation process of foggy images. This model was proposed by [PERSON] and [PERSON] [16; 17], and it is believed that the degradation of the observed imaging image is caused by two parts: one is the background light formed by the scattering of ambient light such as sunlight by the scattering medium in the atmosphere, and the other is the absorption of the target object by the suspended particles in the atmosphere and the scattering of the object itself. As a result, the brightness of the imaging system is reduced and the contrast is reduced to form a fog map. The spatial representation of the physical model of atmospheric scattering is shown in Figure 1, which can be mathematically represented as:  
\[I(x)=J(x)\ t(x)+A[1-t(x)] \tag{1}\]  
where \(I(x)\) is the foggy image acquired by an imaging device; \(J(x)\) is a fog-free image to be restored; \(A\) is the global atmospheric light value; \(t(x)\) is the image transmittance; \(x\) is the pixel coordinates of the image. In addition, \(t(x)\) can also be expressed as:  
\[t(x)=\exp[-\beta d(x)] \tag{2}\]  
where \(\beta\) is the scattering coefficient of the atmosphere; \(d(x)\) is the distance from the object to the imaging system.  
The deformation of Equation (1) can be obtained as  
\[J(x)=\frac{I(x)-A[1-t(x)]}{t(x)} \tag{3}\]  
The above equation shows that to solve the fog-free image with a known fog image, we need to estimate the transmittance map and the atmospheric light value from the fog image first, and then solve it based on the atmospheric scattering model. Therefore, an accurate estimation of the transmittance map and atmospheric light values is crucial to recover fog-free images [18].
# Metal Nanozymes: New Horizons in Cellular Homeostasis Regulation
## 4 Strategies in the Quest for New Nanozymes
Nevertheless, other, more sophisticated coating methods can be applied, providing additional bioinspired features of the nanomaterials. For example, [PERSON] et al. used apoferritin (apoFt) as a nanocarrier for the in situ synthetized Pt nanostructures [124]. Apoferritin was treated with K\({}_{2}\)PtCl\({}_{4}\) salt at pH 8.5 to increase the electrostatic interaction between Pt ions and the interior surface of the protein. Pt ions were reduced, resulting in PtNPs trapped inside the FT shell. The obtained platinum ferritin nanoparticles were bioactive, nontoxic, and stable, with an excellent CAT-like activity [124]. Many interesting designs with multimodal effects are being developed as part of the research that extends the similarity of metaloxide NPs to naturally occurring enzymes. For example, [PERSON] et al. constructed a bifunctional ROS control and Cu\({}^{2+}\) chelation system based on the CeO\({}_{2}\) NPs [125]. The system consisted of a mesoporous nanoparticle functionalized with a derivative of phenylboronic acid (MSN-BA). It is used to design glucose-responsive materials due to its unique reversible covalent interactions with the cis-diol moiety in glucose to form cyclic boronate moieties [126]. Such modified CeO\({}_{2}\)NPs behave like reservoirs with pore blockers to prevent the premature release of the encapsulated drug at unwanted sites in the organism. The release mechanism depends on a redox reaction involving the presence of H\({}_{2}\)O\({}_{2}\) to which the arylboronic esters are oxidized to phenols [127]. The complete breakage of arylboronic esters results in the release of CeO\({}_{2}\)NPs and their payload after that. Due to the catalytic ability of CeO\({}_{2}\) nanocomposites similar to the antioxidant enzyme, the authors proposed this nanocomposite for the treatment of Alzheimer's disease (AD) in an in vitro mouse model on PC12 cells. As an additional charge to the antioxidant function, preventing the oxidative aggregation of amyloid plaque, 5-chloro-7-iodo-8-hydroxyquinoline (CQ) was chosen as a guest molecule, as described below in the section devoted to AD. As a result, a cooperative effect of chelation and ROS enzymatic decomposition was found. Similarly, a noteworthy cooperative multimodal system containing nanovalves was also designed and applied in multimodal imaging in the work of [PERSON] et al. [128]. The abovementioned discoveries of the multienzymatic antioxidant activity of the metaloxide-based nanoenzymes are of great importance for potential medical applications. [PERSON] et al. discovered that PB nanoparticles with multienzyme-like properties can effectively lower intracellular ROS levels and achieve excellent cytoprotection efficacy [95]. In vivo experiments showed their anti-inflammatory activity in a mouse model of lipopolysaccharide-anchoride-induced hepatitis [101]. The results demonstrated their unique characteristics in inflammation and ROS-related damage. PBNPs and their analogues are gathering an increasing research interest [129].
# A Study of Order Modification for Reactive Power Support by Wind Farm during Communication Failure
## 3 Case Studies
### Simulation Results  
#### 3.2.1 Basic Simulation  
In order to estimate the modification effect in terms of reactive power supply, the comparison has to be processed along with the non-applied control scheme. The reactive power supply capability needs to be checked, as well as the voltage condition, including the connection point of the wind farm. Figure 8 shows the general reactive power supply process, using both the aforementioned allocation method, and the related voltage conditions. These exemplary curves were selected to show the highest variation conditions (array 1 has the longest connection distance, which also implies the largest voltage variation). As described in the simulation design, case A includes the voltage drop condition and the relevant order change. In general states, as shown in Figure 8, the modified signal, composed from the central controller, aptly manages the induced voltage variation. Consider the maximum reactive power reserve for each WT is nearly 2.5 MVAR (0.95 _pf_ utilized for calculating limit); both full support and compensation are represented in displayed curves.
## 3 Results and Discussion
### Differential Scanning Calorimetry (DSC)  
As indicated by [PERSON] et al. [32], this technique can determine the changes in the different physicochemical properties of compounds, which are shown by changes in the heat flow, and therefore, the oxidative stability of a sample can be evaluated through this technique [27]. DSC is the most widely used analytical technique for studies of physical characteristics and thermo-oxidative degradation of fats and oils, as well as their mixtures with herbal plant extracts, according to [PERSON] and [PERSON] [33].  
According to the results (Table 1), the maximum peak oxidation (T\({}_{\text{max}}\)) was 487 \({}^{\circ}\)C. The samples that produced this result (the highest antioxidant activity) were those with 75% EtOH and 10 \(\upmu\)s pulse duration. This result was expected since the extracts in 75%  
Figure 1: Y\({}_{\text{TP}}\) for PEF-treated and reference extracts in five different tested solvents and a pulse duration of 10 \(\upmu\)s. Y\({}_{\text{TP}}\) is the total polyphenol yield.  
Figure 2: Y\({}_{\text{TP}}\) for PEF treated and Reference extracts in five different tested solvents and a pulse duration of 100 \(\upmu\)s. Y\({}_{\text{TP}}\) is the total polyphenol yield.  
ethanol were found to have the highest content in total polyphenols. The highest difference in the resistance to oxidation between PEF and reference extracts, expressed by the increase in oxidation temperature (significant at \(p<0.05\)), was presented in the extracts produced with 25% EtOH. PEF extracts treated with 100 \(\upmu\)s (25% EtOH) reached an average increase in oxidation temperature of 61.5% (in relation to reference extracts), while PEF extracts treated with a pulse duration of 10 \(\upmu\)s reached a corresponding increase of 53.8%.