esa-sceva/satcom-chunk-collection huggingface dataset:
# Naturally Occurring Flavonoids and Isoflavonoids and Their Microbial Transformation: A Review
## 2 Isoflavonoids and Flavonoids from Actinomycetes and Fungi
### Flavonoids
#### 2.2.2 Flavonoid Glycos  
Flavonoid glycosides derived from endophytic fungi were reported for the first time in 2016. Three quercetin-3-O-glycos, named guaijaverin (**67**), isoquecitritin (**68**), and hyperin (**69**), were isolated from the endophytic fungus _Nigrospora oryzae_. The fungus was isolated from the leaves of the Nigerian misteltoe _Loranthus micranthus_, which was widely used in African traditional medicine [16]. Actinoflavoside (**70**), possessing a rare 2,3,6-trideoxy-3-amino-ribopyranoside aminousugar skeleton, was obtained from the fermentation broth of a marine _Streptomyces_ sp. [58]. A flavonoid glycoside, daidzein-4',7-di-(2-deoxy-\(\alpha\)-L-fucopyranoside) (**71**), was obtained from actinomycetes, which showed moderate activity against tumor cells of A549, HepG2, and HCT116 [43].  
The strain _Streptomyces_ sp. ERINLG-4 was isolated from the soil samples collected from a depth of 5-15 cm in the Doddabetta forest. The EtOAc extract of the strain showed potent cytotoxic activity in vitro against the A549 lung adenocarcinoma cancer cell line. The following work led to the isolation of an active component, quercetin-3-O-\(\beta\)-L-rhammopyranosyl-(1\(\rightarrow\)6)-\(\beta\)-D-glucopyranoside (**72**), showing prominent cytotoxic activity against the A549 lung cancer cell line with an IC\({}_{50}\) value of 82 ug/mL. However, it showed no toxicity against the Vero normal cell line, up to 2000 ug/mL [59]. Three flavonoids, named myricetin (**50**), myricitrin (**73**), and quercetin (**74**) were obtained from the endophytic fungus _X. papulis_ BCRC 09F0222 isolated from hairy woody plants [48].
# Demodulation Technique Based on Laser Interference for Weak Photo-Acoustic Signals on Water Surface
## 3 Results  
In our study, a test platform was set-up with separate optical elements in an optical dark chamber. The optical dark chamber, interference optical path, and other test devices used in the study are shown in Figure 6. During the test, the signal generator created signals on two paths. The 10 kHz high-frequency signals on the first path acted on the reference optical path to generate high-frequency carriers of the same frequency, while the signals on the second path caused the speaker in the water pool to generate waves as the underwater target to be measured. The main equipment in our experiment is shown in Table 2.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Equipment** & **Parameter** & **Value** \\ \hline \multirow{3}{*}{He–Ne Laser} & Wavelength/nm & 632.8 \\  & Power/mW & 0.6–1.4 \\  & Power stability & \(\pm\)0.1\% \\ \hline \multirow{2}{*}{Underwater speaker} & Rated power/W & 15 \\  & Frequency response /Hz & 80–20,000 \\ \hline \multirow{2}{*}{Data acquisition card} & Sampling rate/kS/s & 100 \\  & Resolution/bit & 16 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Performance index of main equipment.  
Figure 5: Phase generated carriers (PGCs) interference signal demodulation flow.
## 2 Experimental Details  
### Fabrication  
Multilayer thin films were designed by combining Nb\({}_{2}\)O\({}_{5}\) as a high-refractive-index material and SiO\({}_{2}\) as a low-refractive-index material. We designed the SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films using Essential Macleod with variable parameters such as material, refractive index, extinction coefficient, and wavelength. Nb\({}_{2}\)O\({}_{5}\) and SiO\({}_{2}\) layer thicknesses were decided in order to achieve highest transmittances in the range of 500 nm to 550 nm. Each layer's thicknesses were designed in the range of 40 nm to 120 nm. Single-layer thin films and multilayer thin films composed of SiO\({}_{2}\) and Nb\({}_{2}\)O\({}_{5}\) were fabricated by the plasma-assisted reactive magnetron sputtering method in order to improve the durability of thin films. The commercial coating machine (OWLS-1800, Optorun Co., Ltd., Tsurugashima, Japan) was used in the experiment. The coating equipment separates the metal coating region using mid-frequency magnetron sputtering and the oxidation region using radio-frequency inductive coupled plasma. The glass substrates were rotated into two regions repeatedly and finally a metal oxide thin film was densely deposited on the glass substrates. The respective refractive index (\(n\)) and extinction coefficient (\(k\)) were obtained using the SiO\({}_{2}\) (1250 nm) and Nb\({}_{2}\)O\({}_{5}\) (600 nm) single-layer thin films on three glass substrates (B33, D263, and D270, Schott AG). The SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films were designed by the number of layers, thickness, and sequence of layers in order to achieve a high transmittance at a central wavelength of 530 nm. The SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films were prepared by the plasma-assisted reactive magnetron sputtering method. A multi-target apparatus was used for the deposition process using the parameters listed in Table 1. The base pressure (Pa) and working pressure (Pa) were 2.0 \(\times\) 10\({}^{-5}\) and 8.0\(\sim\)9.0 \(\times\) 10\({}^{-1}\). The deposition rate (A/s) of SiO\({}_{2}\) and Nb\({}_{2}\)O\({}_{5}\) was 6.2-9.29 (A/s) and 1.67\(\sim\)4.76(A/s), respectively. Various deposition conditions such as power supplied to the magnetron, deposition rate, and sputtering time were precisely controlled.
# Numerical Study of Photoacoustic Pressure for Cancer Therapy
## 2 Photoacoustic Model
The Finite Element Method (FEM) is now well known and has been applied for many years in mechanics, thermodynamics, electromagnetics and in electrical engineering [13; 14] and consists of solving systems of partial differential equation with boundary conditions in open or closed domains [11]. The general problem is solved on a discrete mesh of the domain [11] and the unknown physical quantities (\(\mathbf{E}\), \(T\), \(P\)) are computed at the nodes of the mesh by using a variational method. The control of the error on the solution is achieved through an extended and improved 3D method, including a process of iterative remeshing [9; 10; 12]. The accuracy of the computed solutions are closely related to the quality of the mesh [15; 16]. The quality of the solution is improved by adapting the size of the mesh elements to the physical solution [10; 12; 17] through the remeshing process with adaptive loops. If strong variation is induced in the unknown physical quantities of interest, the convergence of the solution to a stable solution requires such mesh adaptions [9; 10]. At each step of the adaption process, the approximations of the solutions of the thermic and acoustic wave equations \(T\) and \(P\), the temperature and the pressure are calculated in the basis of the interpolation polynomials between nodes. The maximum deviation between the solution associated with the mesh and the exact solution at nodes is limited by using the interpolation error (which is based on an estimation of the discrete Hessian of the solution) [18; 19] and is obtained from OPTIFORM software (adaptive remeshing generating isotropic or anisotropic meshes) [9], to govern the remeshing of the domain (with minimum and maximum element sizes \(h_{\text{min}}=0.1\) nm, \(h_{\text{max}}=100\) nm, and a tolerance on the relative error on the computed unknown physical quantities \(\delta=0.001\)). Therefore, the domain is entirely remeshed each time and a new mesh is constructed.
## 1 Introduction
Snoring in the pediatric patient may be associated with micro-awakenings, sleep fragmentation, and be the cause of daytime symptoms such as irritability, attention deficit, hyperactivity, and drowsiness. More rarely, the patient with OSAS may manifest with hypertension, daytime sleepiness, and cardiac changes [14]. The prevalence of OSAS in development age is between 1% and 6% [13; 14]. It can occur at any age although showing, according to current evidence, a maximum peak incidence between the second and sixth years of life, in conjunction with the rapid growth of lymphoid tissue. In pre-puberty, the disease manifests itself equally in both sexes; meanwhile, in adolescents, the data suggest a higher prevalence in favor of the male sex. This condition is burdened by general misinformation and is often underdiagnosed. The gold standard test for OSAS is polysomnography (PSG) [15; 16], although it has numerous limitations such as cost, accessibility, and requiring hospitalization. Alternative pediatric population screening tools are emerging including questionnaires (PSQ, PSQ-SRDB), which are effective in identifying mild OSAS, as well as being noninvasive, repeatable, and reproducible. Similarly, active anterior rhinomanometry (AAR) also allows for the highlighting of patients with clinically severe forms of the disease by assessment of nasal resistance opposed to airflow. Indeed, in the age of development, nasal resistance values correlate significantly with polysomnographic parameters [17]. With reference to the therapeutic approach of pediatric OSAS, the 2016 national Guidelines validate the use of orthodontic therapy, and in particular the benefit induced by orthopedic expansion of the upper jaw, in children with predominantly oral breathing and contracted upper jaw [16]. The rapid palatal expander (RPE) not only promotes a widening of the dental arches and hard palate but increases the diameter of the nasal cavity and nasopharynx [18; 19], improving lingual posture and thus reducing the risk of obstruction [20], showing favorable effects on the growth of the maxillary complex [21]. RPE results in decreased nasal resistance values to airflow [22; 23], improving nasal ventilation and oxygen saturation [24]. Since the association between adeno-tonsillar hypertrophy and OSAS in pediatric age is well-established in the literature [25; 26], the present retrospective study aims to further investigate the effects of treatment with RPE in growing patients having contracted upper jaw, in whom there is or is not the concomitant presence of one or more sites of obstruction (adenoid and/or tonsillar hypertrophy and/or septal deviation), such as to promote oral breathing. This is to evaluate the effects on respiratory function, sleep quality, and related behavioral disorders generated by orthopedic expansion of the upper jaw.
# C-SHAP: A Hybrid Method for Fast and Efficient Interpretability
## 5 Experimental Evaluation
### Dataset  
The paper [14], which was the first to leverage SHAP for feature explanation, utilized a set of benchmark datasets. We used the same datasets to ensure comparability between our methods. These datasets encompass both classification and regression tasks, providing a comprehensive evaluation scope. The classification datasets include Indian Liver Disease, [[https://www.kaggle.com/datasets/uciml/indian-liver-patient-records](https://www.kaggle.com/datasets/uciml/indian-liver-patient-records)]([https://www.kaggle.com/datasets/uciml/indian-liver-patient-records](https://www.kaggle.com/datasets/uciml/indian-liver-patient-records)) (accessed on 14 November 2024); Heart Disease, [[https://www.kaggle.com/datasets/johnsmith8](https://www.kaggle.com/datasets/johnsmith8)]([https://www.kaggle.com/datasets/johnsmith8](https://www.kaggle.com/datasets/johnsmith8)) 8/heart-disease-dataset (accessed on 14 November 2024); Wine [[https://www.kaggle.com/datasets/yasserh/wine-quality-dataset](https://www.kaggle.com/datasets/yasserh/wine-quality-dataset)]([https://www.kaggle.com/datasets/yasserh/wine-quality-dataset](https://www.kaggle.com/datasets/yasserh/wine-quality-dataset)) (accessed on 14 November 2024), Vertebral Column, [[https://www.kaggle.com/datasets/caesarlupum/vertebralcolumndataset](https://www.kaggle.com/datasets/caesarlupum/vertebralcolumndataset)]([https://www.kaggle.com/datasets/caesarlupum/vertebralcolumndataset](https://www.kaggle.com/datasets/caesarlupum/vertebralcolumndataset)) (accessed on 14 November 2024); and Breast Cancer, [[https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data](https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data)]([https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data](https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data)) (accessed on 14 November 2024). For regression tasks, we used the Diabetes dataset we mentioned earlier, [[https://www.kaggle.com/datasets/mathchi/diabetes-data-set](https://www.kaggle.com/datasets/mathchi/diabetes-data-set)]([https://www.kaggle.com/datasets/mathchi/diabetes-data-set](https://www.kaggle.com/datasets/mathchi/diabetes-data-set)) (accessed on 14 November 2024). Table 2 illustrates the mentioned datasets. These datasets provided a comprehensive evaluation across various tasks.
## 4 Vibration-Based Road Friction Monitoring
### Conclusions of Vibration-Based Friction Estimation Approaches  
From our literature review on vibration-based methods for detecting the road-friction coefficient, the following conclusions were derived:  
* Tyre vibration can be used to estimate the friction coefficient. Different approaches have been tried up to now.
* There are mainly two approaches. One approach focuses on low frequencies and the second approach on high frequencies.
* Regarding the low frequency approaches most of them are based on the assumption that longitudinal and lateral slip stiffness depend on the friction coefficient. However, there are contradicting studies and it seems that researchers cannot agree on this.
* There is more confidence on the influence of micro roughness (high frequencies) on the friction coefficient. However, there is no model that can describe the mechanism and mostly data-based approaches have been applied.
* The field trials in the different studies are not consistent or standardised. Various parameters, such as temperature, tread depth and water level, that influence the developed tyre-road friction coefficient are not always measured.
* The influence of tread depth and pattern has not been considered in greater detail. The same tyre with different tread depth will behave very differently for different water levels. It is possible to estimate tread depth by monitoring the longitudinal slip stiffness over longer periods of time.
# Hybrid Particle Swarm Optimization for High-Dimensional Latin Hypercube Design Problem
## 3 Proposed Method
### Minimum Point Distance Method  
According to Equation (2), each particle in PSO will learn its personal best particle _pBest_ and global best particle _gBest_ at the same time. When the personal best particle _pBest_ and the global best particle _gBest_ are in opposite directions from the current position \(x_{i}\) and the positions of _pBest_ and _gBest_ may be quite different, one particle may linger between _pBest_ and _gBest_, which will cause \"oscillation\" [37; 38] and reduce the search efficiency of the algorithm.  
The MPD method is proposed to avoid the oscillation problem of LHD particles. By rearranging the rows of the personal best particle _pBest_ of the LHD particles, the distance between the rows of the LHD particle and the global best particle _gBest_ is minimized. The Euclidean distance is used to calculate the distance between points, and the calculation equation is:  
\[d_{ij}=[\sum_{k=1}^{m}{(x_{ik}-x_{jk})^{2}}]^{1/2} \tag{7}\]  
By calculating the row spacing between each row of the personal best particle _pBest_ and each row of the global best particle _gBest_, the rows of the current particles are rearranged, and then the particle speed and position are updated. The specific operation is shown in Figure 4. In this way, the personal best particle _pBest_ and the global best particle _gBest_ can be in the same direction as the current particle, reducing the \"oscillation\" problem caused by the learning strategy.  
Figure 3: Use the ROV rule to convert the position value of particle X to the arrangement of design point Y.
# An Adaptive Routing Algorithm Based on Relation Tree in DTN
## 5 Algorithm Design  
The AR-RT algorithm is divided into two phases: adaptive replication phase and sub-policy forwarding phase.
# Alpha Centauri: Disc Dynamics, Planet Stability, Detectability
###### Abstract  
Alpha Centauri is a triple stellar system, and it contains the closest star to Earth (Proxima Centauri). Over the last decades, the stars in Alpha Cen and their orbits have been investigated in great detail. However, the possible scenarios for planet formation and evolution in this triple stellar system remain to be explored further. First, we present a 3D hydrodynamical simulation of the circumstellar discs in the binary Alpha Cen AB. Then, we compute stability maps for the planets within Alpha Cen obtained through N-body integrations. Last, we estimate the radial velocity (RV) signals of such planets. We find that the circumstellar discs within the binary cannot exceed 3 au in radius and that the available dust mass to form planets is about 30 \(M_{\odot}\). Planets around A and B are stable if their semimajor axes are below 3 au, while those around C are stable and remain unperturbed by the binary AB. For rocky planets, the planetary mass has only a mild effect on the stability. Therefore, Alpha Cen could have formed and hosted rocky planets around each star, which may be detected with RV methods in the future. The exoplanetary hunt in this triple stellar system must continue.  
Alpha Centauri; binary stars; protoplanetary discs; hydrodynamics; N-body integrations; exoplanets; celestial mechanics; stability; radial velocity; habitability 2020
# Spectral Envelope Transformation in Singing Voice for Advanced Pitch Shifting
###### Abstract  
The aim of the present work is to perform a step towards more natural pitch shifting techniques in singing voice for its application in music production and entertainment systems. In this paper, we present an advanced method to achieve natural modifications when applying a pitch shifting process to singing voice by modifying the spectral envelope of the audio excerpt. To this end, an all-pole model has been selected to model the spectral envelope, which is estimated using a constrained non-linear optimization. The analysis of the global variations of the spectral envelope was carried out by identifying changes of the parameters of the model along with the changes of the pitch. With the obtained spectral envelope transformation functions, we applied our pitch shifting scheme to some sustained vowels in order to compare results with the same transformation made by using the Flex Pitch plugin of Logic Pro X and pitch synchronous overlap and add technique (PSOLA). This comparison has been carried out by means of both an objective and a subjective evaluation. The latter was done with a survey open to volunteers on our website.  
v 201621 September 201614 November 201619 November 201621 September 201614 November 201619 November 201621 September 201621 September 201614 November 201619 November 201621 September 2 voice. This is why spectral envelope preservation might not be, in our opinion, the best choice to perform wide variations in pitch.  
The majority of singing processing and synthesis studies are focused on achieving a natural result through formant preservation [12], control of \(f0\) fluctuations [13], etc. However, it is still unclear how the spectral envelope changes with pitch; thus, we decided to study this particular effect with the goal of obtaining more realistic results.  
In this paper, two main tasks have been carried out. First, an analysis of the natural variations of the spectral envelope as the pitch of the singing voice varies is conducted. Then, a pitch shifting scheme that makes use of the proposed model is implemented. Figure 1 shows a diagram of the main stages performed for both the analysis of the behavior of the spectral envelope and the the pitch shifting process devised to take advantage of our findings.  
The manuscript is organized as follows: Section 2 describes the first stage, in which a parametric model [14] is used to fit accurately the spectral envelope of a number of recorded vowel sounds. In Section 3, the usage of this tool is explained and used for the analysis of a dataset consisting in 76 sung vowels, in order to obtain a set of functions describing the variations of parameters along pitch. Section 4 presents the pitch shifting algorithm developed, which is based on PSOLA with envelope transformation. The evaluation methodology is explained in Section 5, and the results are shown and discussed in Section 6. Finally, some conclusions are drawn in Section 7.
## 4 Methods
### Determining the Contamination Rate  
In practical application, the dataset obtained in phase I may consist of IC and OOC profiles. However, the type of collected profiles is usually not known beforehand. Consequently, we need to determine if there are any OOC profiles in the dataset. There are numerous outlier-detection algorithms that have been applied successfully in many application domains, but their performance is highly dependent on the correct setting of hyperparameters. However, the characteristic of the unsupervised outlier-detection models implies that there is a lack of information regarding the true category of each profile for dividing OOC profiles from IC profiles, and as a result, performing optimal hyperparameter estimation is difficult.  
In the second process of the proposed method, \(K\)-means clustering is conducted on the smoothed profiles. In this study, the number of clusters was set to two. Based on the sparsity characteristic of outliers, the ratio of outliers in a dataset is usually relatively low [52; 53]. The cluster that contains more than half of the profiles is considered the main cluster, which corresponds to the IC profiles.  
In this study, the average of all the profiles in the main cluster was treated as the baseline (reference) profile. We calculated the Euclidean distance between each profile and the baseline profile  
After determining the distance threshold, profiles with a distance greater than this threshold were considered OOC profiles. Finally, the contamination rate can be determined by calculating the proportion of the number of profiles exceeding the threshold to the total number of profiles. Note that the above method may overestimate the contamination rate. This is understandable since it includes samples from the set of IC profiles (due to the setting of type I error) as well as the real OOC profiles. A small number of misclassified IC profiles may not cause problems as they can be further verified by human experts. The detected OOC profiles may not yet have assignable causes; therefore, suspected OOC profiles must be analyzed to search for potential assignable causes.