esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Theoretical Foundation
### CDI Framework
#### 3.5.3 MDA  
MDA utilizes huge multiple sets of real time data through tiny ML-based algorithms in this healthcare system to provide a better service for the welfare of society, revolutionizing the healthcare industry.  
Tiny ML-based MDA rapidly translates the core areas of a patient's health conditions with comprehensive and accurate reports. There are enormous sources available for MDA to analyze for future endeavors such as electronic health records (EHR), social media platforms, mobile apps, pharmaceutical research, payer records, campaigns, and smart medical devices. Due to the availability of high-quality real time data, the results generated from MDA are more accurate and effective. While medical professionals cannot make sense of billions of data points across millions of patients, tiny ML can improve healthcare with more types of data and more cases to process. Cognitive healthcare has dual benefits: (i) improving patient health and (ii) reducing the costs of sub-optimal treatment plans.  
Based on Section 3.5.1-Section 3.5.3 mentioned above, Figure 6 shows the basic elements of the CDI framework that include understanding, verifying, planning, evaluating, attention, and perception to serve as objectives in a specific cognitive task.
# A Comprehensive Study of the Use of LoRa in the Development of Smart Cities
## 4 Results of the Analysis of the Selected Works
### Analysis of the Application Layer
#### 4.1.4 Energy  
Accuracy in electrical billing is highly needed, especially with the widespread use of smart-home appliances in the daily lives. The development of automatic meter reading (AMR) avoids the need for a person to visit a physical location for reading the meter and reduces the possibility of reading the data wrongly [44]. Currently, General Packet Radio Service (GPRS) solutions are used in this context, but they are quite expensive and can lose SMS packets. In this situation, the use of LoRa would allow the creation of a private network including a third-party service. To improve the electrical billing service, a two-way communication between users and providers could be implemented. This would allow the user to see the energy consumption in real time.  
Another approach related to energy is the monitoring of power plants. With the growing of the worldwide population, fossil fuel consumption has been increasing in the last years. For this reason, photovoltaic (PV) power plants are considered as an alternative solution. Since the PV plants are highly dependent on solar irradiation, ambient temperature, and atmospheric conditions, IoT solutions could allow monitoring these parameters in real time [45].
## 3 Results and Discussion
### ANFIS Model Verification  
The predicted power consumption (Ep) versus the measured power (Em) consumption from the real case study are compared in Table 2 and Figure 8.  
A group of real data comprised of eight cases was used to run the ANFIS, then the ANFIS provided the predicted power consumption. Next, the Ep obtained by the ANFIS was compared with the measured Em. It was noticed that the maximum deviation was less than 6.5%, thus the ANFIS model provides a comparable value of power consumption that was very close to the actual values.  
The error per cent \(Ei\) for any sample of data i (i varied from 1 to m, here m = 8) between the predicted values of energy by the ANFIS model (_Epi_) and the measured values (_Emi_) was estimated from the following equation:  
\[E_{i}=\frac{|Em_{i}-Ep_{i}|}{Em_{i}}\times 100 \tag{12}\]  
While the corresponding average error percent \(Eav\) was computed using the following relation:  
\[E_{av}=\frac{\sum_{i=1}^{m}E_{i}}{m} \tag{13}\]  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Test No.**} & \multicolumn{4}{c}{**Parameters**} & \multicolumn{4}{c}{**Power Consumption kWh/t**} \\ \cline{2-7}  & **RR** & **Gape (mm)** & **CSS (mm)** & **S (MPa)** & **Measured E** & **Predicted E** \\ \hline
1 & & & & 21.666 & 0.197 & 0.185 & 6.09 \\
2 & & & & 8.33 & 0.114 & 0.109 & 4.39 \\
3 & & & & 6.286 & 0.06 & 0.061 & 1.67 \\
4 & & & & 8.069 & 0.094 & 0.1 & 6.38 \\ \hline
5 & & & & 4.897 & 0.033 & 0.034 & 3.03 \\
6 & & & & 8.071 & 0.152 & 0.153 & 0.66 \\
7 & & & & 8.635 & 0.336 & 0.351 & 4.46 \\
8 & & & & 11.021 & 0.379 & 0.366 & 3.43 \\ \hline \hline \end{tabular}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{4}{c}{Average Error} & 3.76 \\ \hline \hline \multicolumn{4}{c}{\(R^{2}\)} & 0.9947 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The ANFIS predicted powers versus the measured energy consumed by the jaw crusher.  
Figure 8: Error bars for the predicted energy with the help of the ANFIS model versus the measured energy values for different test data.  
Based on the average error per cent provided in Table 2, the ANFIS model successfully predicted the power consumption with a 3.67% deviation from the measured data. Thus, the ANFIS model with gaussmf had an accuracy of more than 96% to predict the energy consumed by the jaw crusher.
## 4 Case Studies--Seaport of Aveiro in Portugal and ASM Offshore
The market associated with a company, from its suppliers and customers to its competitors, directly affects its positioning and influences its competitive advantage in relation to other companies in the same sector. Considering that ASM Offshore acts as an anchor for the Port of Aveiro, with regard to the intended cluster, a deeper analysis of the various stakeholders becomes relevant. Considering the market previously analyzed, in relation to this company's potential wind tower customers, Enercon, Senvion, GE Wind Energy, Siemens Games Acciona, and Nordex stand out. About the offshore foundations, the main players and potential customers are Ortersd, Vattenfall, EDP, RWE, DEME, Van Oord, Saipem, SHL, Kyearner, Smulders, Lamprell, PrinciplePower, and WindPlus. Regarding the suppliers of raw materials that can integrate the products manufactured by ASM Offshore, this information is shown in Table 6.  
Based on Table 6 it is possible to infer that most potential ASM Offshore suppliers are international. Through this assertion, and based on the literature review, it is possible to deduce two possible alternatives: (i) there is no specialized national market related to the offshore energy sector that can meet the needs of national companies; or (ii) the international market offers better quality/price products that justify your purchase to international companies, with increased transport costs and fees. This perspective allows us to infer that there is no national market for this sector, competitive with international networks. The main competitors of this company are some of the institutions related to offshore wind towers and foundations. Figure 3: Value chain of the offshore wind energy market.
# Stable Evaluation of 3D Zernike Moments for Surface Meshes
## 3 Algorithms for Computing the 3D Zernike Moments for a Surface Triangular Mesh  
### Zernike Moments over a Shape Defined by a Triangular Surface Mesh  
Let us consider a shape \(S\), covering a volume \(V\). The shape is assumed to be represented by a triangle mesh that defines its boundary. Each facet (triangle) \(T\) is defined by three vertices \(A\), \(B\) and \(C\) that are oriented consistently counter-clockwise when seen from the exterior of the shape. As the Zernike polynomials are complete and orthonormal over the unit ball \(\mathbb{B}\), the shape is assumed to fit within this ball. This is obtained by centering the mesh to the origin \(O\), and scaling the mesh such that the longest distance between a vertex of the mesh and \(O\) is set to one.  
Assuming that this shape is homogeneous (i.e., represented by a constant scalar field, with the constant set to one), its Zernike moments \(c^{m}_{nl}\) are given by:  
\[c^{m}_{nl}=\int_{V}\overline{Z^{m}_{nl}(x)}\mathrm{d}x, \tag{23}\]  
where \(n\) is the order of the moment, \(l\) is a non negative integer smaller or equal to \(n\), with the same parity as \(n\), and \(m\) an integer with \(-l\leq m\leq l\).  
Figure 2: _Instabilities in evaluating the \(\chi^{rst}_{nlm}\) factors. We show the maxima (in blue) and minima (in red) for the \(\chi^{rst}_{nlm}\) for a given \(n\), as a function of \(n\)._  
Using the origin \(O\) of the coordinate frame as a reference point, each facet \(T\) defines a tetrahedron, \(\sigma_{T}=(O,A,B,C)\). We set \(A=\overrightarrow{OA}\), with similar notations for \(B\) and \(C\). As these tetrahedra are oriented, the integral over the whole shape is simply the sum of the integrals over them. Therefore  
\[c_{nl}^{m}=\sum_{\sigma_{T}}\text{sign}(V(\sigma_{T}))\int_{\sigma_{T}} \overline{Z_{nl}^{m}(\mathbf{x})}\text{d}\mathbf{x}. \tag{24}\]  
The volume of the oriented tetrahedron is given by  
\[V(\sigma_{T})=\frac{1}{6}\text{det}(\mathbf{A},\mathbf{B},\mathbf{C})=\frac{1}{6}\begin{vmatrix} x_{A}&x_{B}&x_{C}\\ y_{A}&y_{B}&y_{C}\\ z_{A}&z_{B}&z_{C}\end{vmatrix}.\]
## 4 Experiments and Results
### Results of the Two-Way ADI Problem  
For the two-way ADI problem, only the Hijazi and Hasawi dialects were included in the dataset. Only these two classes were considered because they originate from the furthest two regions in the Kingdom of Saudi Arabia (Hijazi is the dialect in the east, while Hasawi is the dialect in the west). Therefore, it was assumed that the difference between their dialects might be more easily distinguished by our considered machine learning algorithms than other dialects.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Classifier** & **Precision** & **Recall** & **F-Measure** & **Accuracy** \\ \hline Model 1 & 65.6\% & 64.1\% & 63.4\% & 64.5\% \\ \hline MultinomialNB & & & & \\ max\_df = 0.1, min\_df = 1, & 63.5\% & 62.9\% & 62.7\% & 63.4\% \\ ngram\_range = (1, 4) & & & & \\ \hline BernoulliN & & & & \\ max\_df = 0.75, min\_df = 5, & 60.3\% & 59.9\% & 59.1\% & 59.3\% \\ ngram\_range = (1, 1) & & & & \\ \hline SGDC & & & & \\ max\_df = 0.1, min\_df = 1, & 59.9\% & 59.9\% & 59.9\% & 60.1\% \\ ngram\_range = (1, 4) & & & & \\ \hline SVC & & & & \\ max\_df = 0.75, min\_df = 1, & 61.2\% & 61.2\% & 61.2\% & 61.4\% \\ ngram\_range = (1, 3) & & & & \\ \hline Logistic Regression & & & & \\ max\_df = 0.75, min\_df = 1, & 59.1\% & 59.0\% & 58.9\% & 59.3\% \\ ngram\_range = (1, 4) & & & & \\ \hline LinearSVC & & & & \\ max\_df = 0.75, min\_df = 1, & 59.7\% & 59.6\% & 59.6\% & 59.9\% \\ ngram\_range = (1, 4) & & & & \\ \hline NuSVC & & & & \\ max\_df = 0.75, min\_df = 1, & 60.4\% & 60.3\% & 60.3\% & 60.6\% \\ ngram\_range = (1, 4) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Results of two-way ADI problem (classes 1 and 3).  
As Model 1 had achieved the best performance among the other CNN models in the multiway ADI problem, it was chosen to carry out our investigation for the two-way ADI problem.  
Table 6 shows the results of the CNN approach (Model 1) and the classical machine learning algorithms in terms of precision, recall, F-measure, and accuracy for the two-way ADI problem.  
The results revealed that all the considered algorithms increased in performance. Model 1 achieved the best performance, with an accuracy of 64.5% and an F-measure equal to 63.7%, compared with the other classical machine learning algorithms. Among the latter, the MultinomialNB algorithm, in which the parameters were determined through a grid search, achieved 63.4% accuracy, followed by SVC, which achieved 61.4%.
## 1 Introduction  
_Potentilla anserina_ L., a perennial herb of the Rosaceae family, is widely distributed in the Qinghai-Tibet Plateau areas of China. Its roots have been used as a functional food and in traditional Tibetan medicine [1]. Current literature indicates that the roots of _P. anserina_ L. mainly contain a variety of biologically active components, such as polyphenols, tannins, flavonoids, triterpenes, and essential amino acids, especially polysaccharides [2]. Polysaccharides are considered important biological response regulators and their bioactivities have been widely studied, such as their antioxidant, anti-tumor, and immunostimulatory effects, as well as their antiviral and anti-diabetic activities. Antioxidant activity is one of the research hotspots in the polysaccharides field due to its positive effects on health. Researchers have also focused on preserving the structure of polysaccharides during extraction, which is crucial to maintaining its bioactivity [3; 4; 5].  
Oxidative stress in the body is involved in aging and various diseases, including neurodegenerative diseases, physiological senescence, cardiovascular disease, and diabetes mellitus; therefore, protecting the body from oxidative damage is essential for health [6,7]. Many natural antioxidants from food sources can protect humans from health problems caused by oxidative damage [8]. Studies have shown that various plant polysaccharides generally possess antioxidant activity and can be explored as effective potential antioxidants against oxidation-related diseases [5]. _P. anserina_ L. polysaccharides (PAPs) have strong antioxidant activities, and this work evaluated and compared the effect of ultrasonic treatment on the antioxidant properties of PAP [9].  
The extraction method is an important factor for the use of active plant polysaccharides. Conventional extraction methods, such as Soxhlet extraction, heating reflux extraction, and hot water maceration, have several shortcomings, including being time-intensive, having a low efficiency and high energy consumption, and being environment unfriendly [10]. Ultrasound-assisted extraction (UAE) is extensively used in natural product extractions because it is a simple, inexpensive, rapid, and effective method that can enhance the yield, decrease the extraction time, and reduce the energy consumption [11,12]. Moreover, it can alter or improve the physical and chemical properties of extracted products, such as a decrease in molecular weight and the enhancement of antioxidant activity [13]. Up to now, many studies have demonstrated that UAE is a valid method for improving the bioactivities of polysaccharides [10,14]. Hence, in this study, UAE was used for the extraction of polysaccharides, where the power, temperature, and duration of ultrasonication were optimized using a Box-Behnken design (BBD). Furthermore, the physicochemical and antioxidant properties of polysaccharides obtained using ultrasound-assisted extraction (PAP\({}_{\text{UAE}}\)) and hot water extraction (PAP\({}_{\text{HWE}}\)) were evaluated and compared to determine the specific effects of ultrasonication.
## 2 Materials and Methods
### Set-Up
#### 2.3.2 EEG Data Recordings  
EEG signals were captured using 15 passive electrodes (FP1, FPz, F7, F3, Fz, F4, F8, C3, Cz, C4, P3, Pz, P4, O1, O2) arranged in accordance with the international 10-20 system [40]. The recordings were taken using the OpenBCI system, with a sampling rate of 125 Hz, and touch-proof electrode adapters (all produced by OpenBCI, Brooklyn, NY, USA). Electrode impedance was maintained below 50 kOhms, according to the impedance mode coded in the software of the OpenBCI GUI (version 5.2.2). The default settings of the OpenBCI electrode cap were used for the online reference and ground electrodes.
## 2 Nanofluid Thermal Conductivity
### Effects of Concentration of Nanoparticles on Nanofluid Thermal Conductivity
The results showed an almost linear increase in thermal conductivity with nanoparticle concentration. It can be concluded from the experimental findings, discussed above that the thermal conductivity of nanofluids increases with nanoparticle volume concentration. However, the rate of increase is different for various nanofluids due to the degree of agglomeration. The effect of nanoparticle concentration on the thermal conductivity of water-based nanofluids at room temperature is shown in Figure 19. For all nanofluids, the thermal conductivity increases with nanoparticle volume concentration (\(\varphi\)), while the rate of increase in thermal conductivity becomes smaller at higher concentrations. This decrease may be a result of nanoparticle clustering at higher concentrations. Figure 20 further reinforces the observations of Figure 19, showing that the thermal conductivity increases with nanoparticle volume concentration (\(\varphi\)). It is observed that the rate of increase in thermal conductivity becomes slightly smaller at higher concentrations for nanodiamond nanofluids, whereas the rate of increases becomes larger at higher concentrations for SiO\({}_{2}\) and ZrO\({}_{2}\) nanofluids. Figure 18: Variation of thermal conductivity of TiO\({}_{2}\)–water nanofluid at nanoparticle volume concentrations of \(\varphi=1\%,\ 1.5\%,\ \text{and}\ 2\%\), as a function of temperature, \({}^{\circ}\)C.
# Minimal Collagen-Binding Epitope of Glycoprotein VI in Human and Mouse Platelets
###### Abstract  
Glycoprotein VI (GPVI) is a platelet-specific receptor for collagen and fibrin, regulating important platelet functions such as platelet adhesion and thrombus growth. Although the blockade of GPVI function is widely recognized as a potent anti-thrombotic approach, there are limited studies focused on site-specific targeting of GPVI. Using computational modeling and bioinformatics, we analyzed collagen- and CRP-binding surfaces of GPVI monomers and dimers, and compared the interacting surfaces with other mammalian GPVI isoforms. We could predict a minimal collagen-binding epitope of GPVI dimer and designed an EA-20 antibody that recognizes a linear epitope of this surface. Using platelets and whole blood samples donated from wild-type and humanized GPVI transgenic mice and also humans, our experimental results show that the EA-20 antibody inhibits platelet adhesion and aggregation in response to collagen and CRP, but not to fibrin. The EA-20 antibody also prevents thrombus formation in whole blood, on the collagen-coated surface, in arterial flow conditions. We also show that EA-20 does not influence GPVI clustering or receptor shedding. Therefore, we propose that blockade of this minimal collagen-binding epitope of GPVI with the EA-20 antibody could represent a new anti-thrombotic approach by inhibiting specific interactions between GPVI and the collagen matrix.  
GPVI; collagen; blood platelets; thrombosis; anti-thrombotic therapies 2023  
11
# Seismic Performance of Modal Transfer Stations on Soft Clays
## 3 Seismic Environment Characterization  
The seismic tunnel-soil-building-bridge interaction effects were studied considering both interplate and intraplate events to assess the impact of frequency content, duration, and seismic intensity in the system interaction. Mexico City's seismic hazard is controlled by two main earthquake sources: interplate events, which originate between the Cocos and North American plates along the Mexican subduction zone, and intraplate earthquakes, which occur within the subducted Cocos plate. It can be highlighted that the two most destructive earthquakes that have occurred in Mexico City originated from these seismogenic sources. Recently published papers described the observed damage patterns that occurred during both earthquakes and the interaction effects typically observed in more detail [30; 35; 36; 37; 38].  
For this purpose, the ground motions recorded at station CUP5 during the earthquakes in September 1985 (interface event) and September 2017 (intraplate earthquake), which is located at a rock outcrop, were used as seed ground motion. The local building code [39] requires an intensity level related to a return period of 250 years to design most structures (i.e., base design earthquake); thus, the acceleration histories were adjusted to the uniform  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Direction** & **Structural Period (s)** \\ \hline Transversal & 0.45 \\ Longitudinal & 0.60 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Fundamental period of the bridge onrigid base.  
Figure 7: Schematic representation of the urban bridge: (**a**) front, (**b**) side, and (**c**) plan view. The pile elements are numbered 1 to 9 in order to be identified in the Results Section.  
hazard spectra (UHS) developed for this return period for each seismogenic source. The selected time history, also called seed ground motion, was modified by applying the method developed by [PERSON] and [PERSON] [40], as modified by [PERSON] and [PERSON] [41], to match the target UHS. As can be seen in Figure 8, the response spectrum calculated from the above methodology reasonably matches the target spectrum. The seed ground motions' characteristics are compiled in Table 4.
## 2 Principle
### MIMO Equalizers: State of the Art
Such channel estimation provides a clear picture of the cross-talk introduced by the mode multiplexer and the propagation through the six-mode FMF, which allows a better understanding of the MIMO DSP performance. Furthermore, a typical eye diagram is shown below of two de-correlated 12.5-Gbps NRZ 2\({}^{7}\)-1 pseudorandom binary sequences (PRBSs) launched into one fundamental mode LP\({}_{01}\) and a  
Figure 4: The squared magnitude of the 6 \(\times\) 6 impulse responses for MIMO equalization [25]. higher-order LP\({}_{12}\) mode, with power adjusted such that both channels received the same power of \(-12\) dBm at the receiver, with decent isolation, low los,s and minimal modal mixing [26]. Consequently, we can observe any substantial coupling between the modal groups within the FMF which would easily close the eye at the receiver. The eye diagram with heavy modal dispersion can be seen in Figure 5b, while the eyes of multiplexing independent channels LP\({}_{01}\) and LP\({}_{12}\) are displayed in Figure 5c,d.
## 6 Conclusions and Outlook  
### Conclusions  
The on-site GNSS monitoring data of the inlet slope of the flood discharge structure of the Lianghekou Hydropower Project were analyzed and studied, and the mechanical parameters of the slope at different water impoundment stages were investigated using GA-LSSVM-BP back analysis. The deformation and point factor of safety under different reservoir water level conditions were also studied using numerical simulation analysis. The following conclusions are obtained:  
1. After the second stage of water impoundment, the maximum value of slope deformation monitoring data is 20.6 mm, and the deformation is still in a controllable state.  
Figure 11: Point factor of safety distribution of slope under condition III. (**a**) Profile 5; (**b**) profile 10; (**c**) profile 13; (**d**) entire body.  
After the second stage of water impoundment, the slope deformation demonstrates an obvious hysteresis phenomenon.
2. The GA-LSSVM-BP model is used to back analyze the mechanical parameters of the slope in the two water impoundment stages, and the back analysis results show that the mechanical parameters of the slope will be significantly weakened by the effect of seepage.
3. Three-dimensional numerical simulation analysis of the slope under different conditions shows that the stability of the slope decreases as the reservoir water level rises, but the minimum values of point factor of safety of slope under the three conditions are: 1.41, 1.38, and 1.35, respectively, which all meet the safety requirements. Slope stability is mainly limited by the fb13 fault at the front of the slope. The obvious danger area formed by the cutting of the fb13 fault appears in the numerical simulation results, and this area needs to be focused on.