esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Due to significant spectral overlap, NIR spectra are often complex, with broad peaks that can obscure finer details, especially in biomolecular samples where multiple bond types contribute to the overall signal [24]. To interpret the complexity of these unresolved spectral bands in NIR spectra, chemometric analyses are applied to improve peak resolution and minimise spectral interference from overlapping bands [25,26]. The large number of spectral variables in NIR data can introduce significant noise and interference, potentially compromising the reliability of predictive models. However, Partial Last Squares Regression (PLSR) mitigates the noise by reducing dimensionality through latent variables (LVs), which minimise spectral overlap and improve model accuracy [27]. However, few studies have validated NIRS for determining the FA composition of forages, and its application in analysing the FA within complex matrices like TMRs is rare. [PERSON] et al. [28] reported validation results with R\({}^{2}\) values ranging from 0.86 to 0.97 for FAs in different types of forage. Other authors [29] found lower R\({}^{2}\) values, ranging from 0.64 to 0.89. Recently, [PERSON] et al. [30] evaluated the FA composition in different types of flaxseeds, obtaining R\({}^{2}\) values between 0.71 and 0.85. However, they highlighted the excellent performance of Fourier Transform NIR (FT-NIR) in evaluating proteins (R\({}^{2}\) = 0.87) and Neutral Detergent Fibre (aNDF) (R\({}^{2}\) = 0.90). Although fat constitutes a relatively minor component of the ration, comprising approximately 2-5% of dry matter, it plays a crucial role in several physiological processes. It facilitates the absorption of essential FAs, helps mitigate inflammatory processes (e.g., through omega-3 FA intake), enhances the absorption and utilisation of lipophilic compounds such as vitamins and polyphenols, and modulates ruminal activity [31]. Additionally, dietary fats originate from various sources, including forages, concentrates, and vegetable oils, adding to the compositional variability. The separation of fibrous, starchy, and oily components can often compromise measurement accuracy, making representative spectral determinations more challenging. This study aims to address these challenges by developing predictive models to estimate the chemical composition, particularly the FA profile, of TMRs used in ten buffalo dairy farms across four seasons. Specifically, it evaluates the effectiveness of NIR spectrometry in constructing these predictive models.
# Projected Augmented Reality Intelligent Model of a City Area with Path Optimization
## 3 Experiments and Results
### Results for Different Crossover Methods  
There are many different crossover methods, for recombining the genes to generate the offspring. Two popular crossover methods were chosen in the present research: Ordered Crossover (OX) and Edge Recombination (ER).  
In OX, the two individuals to be crossed are cut in two points. Each offspring receives a portion of the genes copied directly from one of the parents, and the remainder genes are filled by copying them from the other parent in the same order they were before. This method ensures all of the individuals contain all the points of interest to be visited, without repetitions.  
In ER, crossover is performed giving priority to adjacent genes. That means the genes in the offspring will inherit adjacent genes from their parents.  
Table 1 shows the results of different experiments, applying OX and ER, for different size populations. In those experiments Elitism was maintained \(E=15\) and mutation rate was maintained \(M=1\%\). The table shows the number of generations required to find a good solution and the time required to find that solution. Time is in milliseconds. As stated previously, the results are the average of thirty runs.  
When there is no improvement after three generations, the GA is stopped and the best solution found is returned.  
In the present paper, since the solution to the problem was known, the simulation was stopped when the algorithm found a path with 5791 m.  
As the table shows, OX is much more efficient than ER, taking about half the number of generations and one third of the time for the best population size. Therefore, it will be used in the other experiments. The table also shows the best population size is 25-30 individuals, as highlighted in bold type. Using larger populations it is possible to reduce the number of generations in ER but each generation takes more time to simulate and the global time required does not decrease.  
Figure 10: Example of a path planned to visit ten different points of interest, simulated in the computer. The red donuts are points of interest, the solution path is marked in blue.
# Attribute-Centric and Synthetic Data Based Privacy Preserving Methods: A Systematic Review
## 2 Privacy Preserving Data Publishing and Major Research Tracks
### Major Research Tracks in Privacy Preserving Data Publishing  
A variety of techniques were developed to safeguard user privacy in personal data handling. To this end, famous solutions are encryption, masking, watermarking, secret sharing, secure multiparty computation, anonymization, and secure enclaves [36, 37]. Despite other solutions, anonymization is one of the most widely used tools for preserving the privacy of user data owing to the least computing complexity, the ease in employment, and the conceptual simplicity. Anonymization technology has significantly advanced from multiple perspectives, and many independent tracks exist thus far. Figure 4 systematically presents the advancements in the privacy domain. The anonymization concept started with the syntactic privacy methods and advanced to many other latest methods, as shown in Figure 4. For example, the syntactic methods yielded poor utility and were improved by the clustering-based methods. The DP-based methods have shown remarkable achievements in static and dynamic scenarios. For example, DP-based methods were implemented widely in different domains such as federated learning, IoT, industrial IoT, and cloud computing environments for privacy preservation. Many AI-based methods were also used to improve many critical parts of the traditional anonymity methods and to improve the privacy and utility results [38]. Some methods were developed to counter a specific privacy threat or to preserve privacy in a specific data style (i.e., table, graph, matrix, text, trace, etc.). In some cases, more than one method was jointly used to protect the privacy of user data. To the best of our knowledge, detailed tracks and famous methods under each track, inparticular, attribute-centric anonymization and synthetic-data-based methods, have not been discussed in previous studies.  
Figure 5 demonstrates the data sources used in this study. We extracted the relevant information from popular sources with the help of relevant search strings.  
The distinctive features of the attribute-centric methods are to extract valuable knowledge to the extent possible about the underlying data and to reduce anonymity operations. In contrast, the unique features of synthetic-data-based methods are to mimic the properties of real data as much as possible and curate close copies of real data. Both these methods are developed to meet the growing demands of both privacy and utility in the big-data- and AI-driven era. The attribute-centric methods have a close relationship with the three famous syntactic methods (e.g., \(k\)-anonymity, \(\ell\)-diversity, and \(t\)-closeness). In contrast, synthetic-data-based developments have a strong connection with differential privacy-based methods.  
Figure 4: Schematic of famous and SOTA privacy tracks and methods developed from 2002\(\sim\)2023.
## 2 Scope and Methodology of the Research
Additionally, samples of the algal suspension were collected from each beaker of the flocculation tester at regular intervals (typically every 5 min) to assess temporal variations in suspension concentration and dry weight content. The concentration was measured using an Orion AquaMate 8000 UV-VIS spectrophotometer (Thermo Scientific, Waltham, MA, USA), which recorded the optical density of the suspension at a wavelength of 684 nm. This wavelength was chosen based on a spectral scan that identified it as the point of maximum absorbance. To establish a relationship between absorbance \(A\) (optical density) and algae concentration \(C_{a}\), a standard curve was created. This curve was generated by plotting optical density measurements of algae suspensions at known concentrations against their corresponding dry weight values. The algae dry weight was determined using a Radwag MA.X2.A moisture analyzer (Radwag, Radom, Poland), providing measurements with a precision of \(\pm\)0.0001 g. The resulting data confirmed a linear relationship, as shown by the following equation:  
\[A=1.253364815\times C_{a}. \tag{1}\]  
This relationship allows for precise interpolation of unknown samples. The standard curve was stored in the spectrophotometer's memory, enabling the instrument to directly convert absorbance readings into concentration values during analysis. The method proved to be highly reliable, with a correlation coefficient (R\({}^{2}\) = 0.997952), confirming its accuracy and precision. The favorable values for the coefficient of determination (R\({}^{2}\) = 0.997952) residual sum of squares \(\sigma^{2}\) = 0.110644 and residual mean square = 0.0110644 demonstrate statistical significance across the entire study range, with a mean relative error of \(\pm\)4.04%. The local concentration of algae in the suspension (\(C_{a}\)) was determined as the average of three measurements. In each case, the measured concentration values were repeatable, with the standard deviation not exceeding 0.33% of the mean value. Furthermore, samples of the clarified liquid, suspension, and sediment were collected for microscopic analysis. Observations were conducted using a Motic AE 2000 inverted microscope (MOTIC, Hong Kong, China), integrated with Motic Images Plus 3.0 software for computerized image analysis. This setup enabled seamless integration of microscopic observations with digital imaging, facilitating in-depth analysis of the recorded images.
## 2 Wake Effect and Lifetime Estimation in DFIG Wind Farm  
### DFIG Wind Turbine and MPPT Method  
As shown in Figure 1, the DFIG wind turbine has two degrees of freedom for active power control which are the pitch angle and the tip speed ratio; the wind turbine delivers the active power from the stator side of the generator, and delivers or absorbs active power from the rotor side of the generator depending on whether the slip is negative or positive. According to the aerodynamic model, the mechanical power \(P_{m}\) extracted by the turbine can be calculated by [27]:  
\[P_{m}=\frac{1}{2}\rho\pi R^{2}C_{p}(\beta,\lambda)v^{3} \tag{1}\]  
where \(\rho\) is the air density, \(R\) is the radius of the turbine blade, \(v\) is the wind speed, and \(C_{p}\) is the power coefficient, which is related to the pitch angle \(\beta\) and the tip speed ratio \(\lambda\). The tip speed ratio, defined as the ratio of the blade tip speed over the speed of the incoming wind, is given by:  
\[\lambda=\frac{\omega_{r}R}{v} \tag{2}\]  
where \(\omega_{r}\) is the rotor speed.  
In the case of a specific wind speed, the mechanical power is controlled by the pitch angle and the tip speed ratio. By the MPPT method, the wind turbine operates at the maximum mechanical power. According to (1), the maximum mechanical power is obtained at the maximum power coefficient, which is a function of the pitch angle and tip speed ratio. The power coefficient of the NREL 5 MW wind turbine in terms of the pitch angle and tip speed ratio is shown in Figure 2a [28]. It can be observed that the maximum power coefficient is obtained at the pitch angle of \(0^{\circ}\) and the tip speed ratio of 7.55. Consequently, the MPPT method controls the wind turbine operating at the pitch angle of \(0^{\circ}\) and tip speed ratio of 7.55 to maximize the mechanical power extraction at a specific wind speed.  
Figure 1: Configuration of a Doubly-Fed Induction Generator (DFIG) wind turbine including power converter and controller. RSC, Rotor-Side Converter; GSC, Grid-Side Converter.  
The parameters of the NREL 5 MW DFIG wind turbine are shown in Table 1[28]. As shown in Figure 2b, the active power curve of the NREL 5 MW wind turbine with the implemented MPPT method is presented with the relationship between the active power curve and the wind speed. It is noted that the tip speed ratio is kept at 7.55 except for the case that the rotor speed is limited at 6.9 rpm and 12.1 rpm.
## 4 Discussion  
In this study, we found that SP enhances the proliferation and odontogenic differentiation of KN-3 cells.  
EMD and amelogenin peptide promote the proliferation of dental tissue cells, such as PDL fibroblasts and bone marrow stromal cells (BMSCs) [24; 25]. In a previous study, we showed that SP, derived from EMD, can also promote cell proliferation of human BMSCs [8]. However, the effects of SP on proliferation in odontoblasts had not been previously investigated.  
Figure 5: Effect of SP on odontoblastic differentiation in KN-3 cells. Quantitative real-time PCR analysis of dentin sialoprotein (DSPP) in KN-3 cells at 1, 3, 6, and 24 h.  
Figure 6: KN-3 cells treated with or without SP were incubated with anti-DSPP monoclonal antibody. Cells were incubated with a fluorescence-labeled secondary antibody. The samples were stained with DAPI solution. Scale bar = 100 μm.  
We showed that SP promotes KN-3 proliferation at 100 ng/mL, similar to the optimal concentration for PDL stem cells [10]. Therefore, we further examined the odontogenic differentiation at this concentration of SP (100 ng/mL).  
ALP is considered to be an odontogenic marker [26]. We found that SP enhanced ALP activity, which is similar to the effect of EMD in hard tissues and the effect of SP in KN-3 cells. Therefore, SP can also induce odontogenic differentiation in KN-3 cells.  
We quantified calcium levels in cultures of KN-3 cells by using alizarin red staining and investigation of extracellular matrix calcium deposition. Alizarin red staining is performed for the detection of calcified nodules formed by osteoblasts or odontoblasts [27]. We qualitatively and quantitatively determined changes in mineralization in response to treatment with SP. We found that SP enhanced mineralized nodule formation stained with Alizarin red and calcium deposition in cultures treated for 7 days, compared with untreated cultures. Our previous study showed that SP can also promote mineralization of PDL stem cells [16]. Our results suggest that SP can be used for the dentin formation for earlier protection of dental pulp tissue.  
We also investigated the effect of SP on odontogenic differentiation. We found that it impacted the levels of DSPP, which is a noncollagenous dentin matrix protein that is known as an early-stage marker of odontoblastic differentiation [28, 29]. KN-3 cells cultured for 1-12 h expressed high levels of DSPP [30]. This exhibited that KN-3 cells have the ability to differentiate into odontoblasts. In this study, we showed that DSPP expression was upregulated by SP in KN-3 cells. These results indicate that SP promotes odontoblastic differentiation.
## 5 Dynamic Mechanical Response Analysis of Asphalt Pavement under the Influence of Groundwater
### Impact of Groundwater on the Variation Patterns of Road Surface Deflection
From the data analysis results, it can be observed that the groundwater table had the following impact patterns on road surface deflection: (1) As the groundwater table rose, the overall road surface deflection gradually increased. When the distance between the groundwater level and the subgrade surface changed from 7 m to 1 m, the maximum deflection value at D1 increased by 42.36%. (2) When the groundwater table was more than 6 m below the roadbed surface, the road surface deflection tended to stabilize. (3) Changes in roadbed moisture had a less noticeable impact on the deflection growth rate at points D1 and D9.
# Potential and Limitations of the New European Ground Motion Service in Landslides at a Local Scale
## 3 Results
### Geomorphological Features and Sentinel-1 \(A\)-DInSAR  
Figure 4 shows different geomorphological features mapped during photointerpretation and field survey. Also, it is accompanied by the building damage inventory and the descending VLOS and horizontal velocity detected. This geomorphological map updates the previous cartography carried out by the IAME and by the INDUROT [43; 44; 45] used as context in Figure 2. First, the landslide limits were modified, especially at the southernmost boundary (Figure 4). Secondly, different surficial deposits that remained unidentified were also identified and mapped. The mass movement presents a main scarp of 0.9 km, which crosses the village of El Valle in a W-E direction and subsequently, assumes an N-S direction. At the head, some creep movements and colluvium deposits, extending over 0.04 km\({}^{2}\), were mapped. These can be found above the La Miera landslide and across El Valle village. In this village, a flow deposit with an area of 0.04 km\({}^{2}\) was also mapped, where the descending VLOS detected ranged from \(-\)11.6 to \(-\)1.7 mm/year. The horizontal velocities observed in El Valle village ranged from \(-\)7.2 to \(-\)2.5 mm/year. Within the landslide area, three flow deposits with areas of 0.013, 0.05 km\({}^{2}\), and 0.01 km\({}^{2}\) were mapped, although ground motion could not be detected using the EGMS. They present creep phenomena, and they may be directly related to erosion of secondary scarps. Within the landslide sector, a total of seven secondary scarps were differentiated. Furthermore, four accumulation lobes of material were mapped. The neighborhood of Los Campos is located on three of these accumulation lobes, where VLOS of \(-\)9.7 mm/year was measured. The northernmost and southernmost sectors of the La  
Figure 3: detected Deformation time series (TS) observed in the La Miera landslide. (**A**) Time series from descending track (TS-Desc). (**B**) Time series measured in horizontal motion track (TS-Hor). See TS locations in Figure 2B,C.  
Miera landslide are strongly eroded by the effects of runoff, generating very steep slopes and facilitating the development of slope instabilities of reduced size (flows).
# Large Language Models in Computer Science Classrooms: Ethical Challenges and Strategic Solutions
## 4 Suggested Guidelines for Ensuring the Ethical Use of LLMs in Academia
### Guidance for Efficient Use of LLMs by Teachers and Students  
Providing guidance on the efficient use of LLMs can help students and educators to optimize their interactions with these tools, improve their productivity, and enhance their learning experiences. [PERSON] et al. [38] have investigated the effectiveness of various pedagogically informed guidance strategies on students' performance, confidence, and trust in LLMs within educational settings. Their main research questions focused on the influence of different guidance strategies on students' interactions with LLMs, the impact on their performance and trust in these models, and how these strategies affect their confidence in effectively utilizing LLMs.  
Two main experiments were carried out to explore these questions. The first was conducted in an undergraduate computer science class with 145 students, examining the effects of different guidance strategies on student interactions with LLMs. The second was a controlled experiment using Prolific with 356 participants, focusing on solving math problems and analyzing the same guidance strategies in a controlled setting. The tested strategies included list-based suggestions, example-based instruction, metacognitive questioning, and a problem-solving-then-refinement approach.  
The results from the experiments revealed nuanced impacts of the guidance strategies. In the classroom study, list-based suggestions reduced unrelated queries, example-based instruction increased curiosity-driven unrelated questions, metacognitive questioning led to more thoughtful rephrasing, and the solve-then-refine approach prompted more clarification questions. The controlled experiment showed no significant performance difference between the strategies or between prompted versus unprompted LLMs. However, confidence in using LLMs showed a temporary increase after receiving guidance but decreased after task completion, suggesting that the initial confidence boost from guidance is not sustained through practical application. Trust in LLMs generally declined after interaction, indicating potential issues with the responses provided by the models.  
These findings emphasize the critical role of educators in shaping how students use LLMs. Effective guidance strategies not only influence student outcomes but also help cultivate an environment of thoughtful and responsible LLM usage. However, the study underscored the need for further empirical research to refine how LLMs are integrated into educational practices, ensuring that their full potential is realized without compromising educational integrity.
# Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones
## 2 Datasets and Methodology
### Radiometer Wind Products  
Most of the assessment of the CYGNSS winds discussed here uses comparisons with wind observations from mature satellite radiometer missions. These include the following polar orbiting microwave radiometers processed in near-real time at RSS: the NASA/JAXA AMSR2 [35], the NASA SMAP [36], and the recently decommissioned US Navy WindSat [37]. AMSR2 and WindSat observations are derived from microwave emission from the wind-roughened ocean at frequencies 6-37 GHz and a spatial resolution of 25-40 km [38; 39]. They are each processed with three types of algorithms, defined by different combinations of the observing frequency channels: a global algorithm for rain-free winds [40; 41], an all-weather algorithm valid even in rain [42], and a tropical cyclone algorithm (TC-winds) specifically designed for extreme winds in storms and in rain [22; 43].  
Unlike AMSR2 and WindSat, SMAP is a radiometer operating at a lower frequency (1.4 GHz) that is able to provide ocean surface wind observations at a resolution of 40 km, with higher accuracy at extreme winds, without being affected by rain [20; 44]. Because of the lower frequency, SMAP wind observations at lower winds (below 10 m/s) are noisier when compared to AMSR2 and WindSat and have not been used in our assessment. All these datasets have been extensively validated at all wind speed regimes, including in hurricanes [21; 22; 23; 25; 42]. The radiometers' data are available as L3 gridded datasets on a 0.25\({}^{\circ}\) Earth grid, with daily files including ascending and descending passes (www.remss.com, accessed on 30 September 2021).