esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Betalain Content Changes after Pretreatments and Drying
The use of blanching as a pretreatment resulted in the greatest loss of yellow pigments in the beet at 58%, relative to the raw tissue. Tissue treated with 35 kHz ultrasound for 30 min had an equally low vulgaxanthin content (54% loss relative to raw tissue). After drying, the sample soaked for 20 min was characterized by the highest yellow pigment content, with a yellow pigment content of 494.4 mg vulgaxanthin/100 g d.m. However, that was the material in which yellow dye degradation was found to be the greatest, compared to undried. Overall, the highest vulgaxanthin retention (69-74%) was found in dried beetroot that was subjected to 10 min pretreatment, regardless of the technique used. Such a negative outcome most likely was a consequence of the temperature elevation in the material during drying, which resulted in the degradation of the betalain content. It has been established that both betanin and vulgaxanthin are very sensitive to thermal treatment [34]. In general, a two-way analysis of variance found no significant effect of the duration and frequency of ultrasonic treatment on betalain content in samples before and after drying. Previously, the effect of the US pretreatment frequency on phytochemical compounds in IR-dried sweet potatoes showed that the highest retention was noted after subjecting the material to 40 kHz for 30 min [37]. They also established that both the US frequency and drying temperature have a crucial effect on the quality of the obtained product, which was the opposite compared to our results. Figure 5: Content of red (**a**) and yellow (**c**) pigments in raw beetroot and beetroot subjected to various types of pretreatments; content of red (**b**) and yellow (**d**) pigments in raw beetroot and beetroot subjected to various types of pretreatments, a–f—homogeneous groups are presented above the column; different letters indicate statistical significance (\(p<0.05\)).
# A Robust Intelligent Controller for Autonomous Ground Vehicle Longitudinal Dynamics
## 2 Vehicle Modeling
### Longitudinal Tire Forces  
The literature provides a spectrum of the longitudinal force of nonlinear tire models such as Pacejka, Dugoff, and others [32; 33]. These models were developed via half-empirical or empirical studies that have given a mathematical characterization of the tire/road contact forces along the longitudinal direction and are expressed in terms of the slip rate, the coefficient of friction, and the normal load.  
[PERSON]'s model remains the most widely used model since it gives an in-depth description of the tire-road interaction via the magic formula described below:  
\[\mathfrak{f}_{xf}=\mu\mathfrak{f}_{zf,r}\sin\left(C_{x_{f},r}\tan^{-1}\left(B _{x_{f},r}\mathcal{S}_{x_{f},r}-E_{x_{f}}\left(\begin{array}{c}B_{x_{f},r} \mathcal{S}_{x_{f},r}\\ -\tan^{-1}B_{x_{f},r}\mathcal{S}_{x_{f},r}\end{array}\right)\right)\right) \tag{5}\]  
where \(\mu\) is the friction coefficient, \(\mathfrak{f}_{z}\) indicates the vertical forces, and \(\mathcal{S}_{xf}\) and \(\mathcal{S}_{xt}\) denote the front and rear longitudinal pure slip ratio, respectively. For a complete overview, the reader can follow [34; 35].  
Using Equation (5), the nonlinear behavior of the longitudinal contact forces is plotted in Figure 2 for different vertical forces and a range of longitudinal slip ratio values from \(-100\%\) to \(+100\%\). This figure demonstrates that the relation between the longitudinal  
Figure 1: Vehicle longitudinal dynamics.  
contact forces and the longitudinal slip is linear in the area indicated by the two dotted straight lines. The proportionality coefficients \(\mathbb{O}_{xf}\) and \(\mathbb{O}_{xt}\) are the longitudinal tire stiffness values related to the front and rear tires. These linear relationships, which will be opted for in the following section, can be expressed as:  
\[\mathfrak{f}_{xf}=\mathbb{O}_{xf}\mathcal{S}_{xf} \tag{6}\]  
\[\mathfrak{f}_{xt}=\mathbb{O}_{xt}\mathcal{S}_{xt} \tag{7}\]
## 6 Industrial Application of the Developed Approach  
The following section presents the industrial application of the described solution space management approach from Section 5. First, Section 6.1 introduces the details of the application case. Then Sections 6.2 and 6.3 show the application of the two solution management approach steps according to Sections 5.1 and 5.2.  
A use case was conducted at a German automotive company to evaluate the developed solution space management approach in an industrial environment. The findings are used to assess the fulfillment of the requirements presented in Section 4. All data and information presented in the following section are taken from a real use case but presented in an alienated form due to confidentiality restrictions. In particular, this applies to the characteristics of the production network, such as the number and type of products, market demand, number of sites, production line capacities, etc. Due to the alienated data base, the results presented in the following sections do not represent generally valid recommendations for action in real-life decision situations but are intended to demonstrate the applicability and validity of the developed approach.
# A Scalable Solution to Detect Behavior Changes of Elderly People Living Alone
## 3 Method and Datasets
### Description of the Proposed Method  
#### 3.2.1 An Abstraction of the Living Space  
In Ref. [42] it is argued that, with respect to human activity, we should make a distinction between locations and places: \"places are locations that carry some meaning to user and to which the user can potentially attach some (meaningful) semantics\". People do not just happen to be in certain places--their presence in the respective place and the amount of time they spend there are the result of decisions, based on needs, preferences, habits, or values. Normally, the meaning people attach to certain places has nothing to do with details like the surface of the room, the position of the furniture, the existence and location of certain appliances, etc. Hence, from the perspective of an observer of the behavior of a person in his/her living environment, all these details are unimportant. Starting from this idea, in our previous work ([43]), we proposed an abstraction of the residential living space as a collection of Behaviorally Meaningful Places (BMPs): living room, bedroom, kitchen, and bathroom represented as points located symmetrically in a generic 2D Cartesian space.  
Figure 4 shows an example of the result of abstraction of a particular residential space.  
Figure 4: An illustration of the abstraction of a residential space: (**a**) the actual floor plan with the locations of the motion detectors \(M_{k}\) and (**b**) the map of the generic 2D space indicating the locations of the behaviorally meaningful places P1-P4 (P1-bedroom, P2-Kitchen, P3-bathroom, P4-living room).  
Assuming that all the sensors have binary output, for the sensor deployment depicted in Figure 4a it is possible to associate the sensor events with the BMPs as follows:  
\[\begin{array}{l}\{P_{1}\}=\{M010\}\cup\{M011\}\cup\{M013\}\\ \{P_{2}\}=\{M003\}\cup\{M004\}\cup\{M005\}\cup\{M015\}\\ \{P_{3}\}=\{M012\}\cup\{M014\}\\ \{P_{4}\}=\{M001\}\cup\{M002\}\cup\{M006\}\cup\{M007\}\cup\{M008\}\cup\{M009\} \end{array} \tag{1}\]  
where \(\{P_{i}\}\) is the set of sensor events describing the activity in the place \(P_{i}\) and \(\{M_{j}\}\) is the set of events generated by the motion detector \(M_{j}\).
## 3 Calculation Methods
### Fluent-EDEM Coupling Process  
The momentum and energy are transferred between the DEM and the CFD by compiling an application programming interface (API). The program compiled by the API contains a CFD-DEM coupling scheme that takes into account fluid-particle interaction forces, including the drag, buoyancy, and lift forces. At the beginning of the computation, EDEM is run first, determining the contact force between particles by solving Equations (5)-(8) and the initial state of the particles by solving Equations (3) and (4). Fluent then updates the status information pertaining to the particle location and velocity, which is transferred to EDEM via the API. By solving the continuity equation (Equation (1)) and the momentum conservation equation (Equation (2)), Fluent updates the fluid grid state and attains the interactional forces (drag, buoyancy, and lift forces) between fluids and particles. Then, the interactional forces between fluids and particles are transferred to EDEM via the API to update the stress state of particles. Finally, a new cycle starts. A schematic representation of the process is shown in Figure 12.  
Figure 11: Schematic diagram of the Hertz–Mindlin contact model.
# The Research of Complex Product Design Process Model under the Concept of Self-Recovery
## 2 Relevant Research  
### Research on the Concept of Self-Recovery  
With the development of the self-recovery concept, [PERSON] et al. [9] proposed a hybrid energy structure composed of solar cells and self-recovery nano-generators to solve the problem of reduced output capacity due to the potential mechanical damage of solar cells. [PERSON] et al. [10] used a liquid-transfer active balancing device to build a targeting self-recovery regulation system which realizes imbalance fault self-recovery at the structural level by injecting compressed air into the targeting chamber to change the mass distribution of the balancing disc and rotor. [PERSON] et al. [11], based on the reliability principle and self-recovery concept, proposed a multiple therapy target fault self-recovery regulation method for an electro-hydraulic control system, where the occurrence of displacement faults of the catalytic cracking unit in the refinery was reduced at the structural level by designing an adjustable actuator. [PERSON] et al. [12] reasoned the situation change in a smelting furnace according to the fluctuation rate and duration of the raw material granule size in the smelting furnace by adjusting the current parameters between electrodes. [PERSON] et al. [13] proposed a control method for rotor multi-frequency cycle vibration in rotor-bearing systems, which suppresses rotor multi-frequency vibration through parameter changes to achieve rotor self-seeking optimal control of vibration. [PERSON] et al. [14] identified unbalanced vibrations with the help of the axial trajectory method and used a multi-directional vibration vector as the self-balancing control signal, where the unbalanced vibration was offset by parameter adjustment.  
At present, the self-recovery concept is researched and applied extensively at the structural and parametric levels. [PERSON] et al. [15] summarized the current research on the concept of self-recovery and formally proposed the theory of artificial self-recovery. Artificial self-recovery theory includes different technical fields, which are divided into two categories: parameter adjustment and structural adaptation, meaning that the system will be guarded against deviating from normal operation by regulating parameters, or the product will be self-adapted to variable operating conditions by changing the product structure, stiffness, and damping distribution.  
At the structural and parametric levels, the research on the self-recovery concept has formed a relatively well-developed theoretical system. However, in the design stage, there are fewer research achievements in applying the self-recovery concept at the functional level.
## 4 Evolution of Cadmium Transporters and Their Functions in Cadmium Accumulation
### Evolution of Cd Transporters  
The evolution of membrane transporters may have played an important role in the adaptation of plants to metalliferous environments. The ancestors of modern land plants colonized the terrestrial habitat approximately 500-470 Mya. Since then, dramatic changes, including large fluctuations in water availability, illumination, light intensity, temperature, and the carbon-dioxide-to-oxygen concentration ratio, have occurred in the living environments of land plants compared to the aquatic environments of seagrass grown in the ocean [92]. Have the membrane transporters of plants experienced any persistent adaptive and stepwise evolution for their adaptation to changing environments? To answer this question, a comparative genomics analysis of NRAMP, HMA, ABCC, ZIP, CDF, CAX, and OPT families was performed using 41 plant species ranging from rhodophytes to eudicots. The results showed that the vascular plants (including lycophytes, ferns, gymnosperms, and angiosperms) contain many more Cd transporter family members in their genomes than do algae and bryophytes (liverworts and mosses) (Table 1), implying that the Cd transporter families may have undergone a lineage-specific expansion as a result of gene duplication (whole-genome duplication or duplications of large chromosomal regions) and/or tandem duplication [93; 94; 95]. Such expansion of membrane transporter families in vascular plants could have provided an adaptive advantage for the colonization of new habitats, such as metalliferous soils, before significant vascular development occurred in early land plants. Furthermore, most Cd transporter families except the OPT family can be identified across all plant species (Table 1), suggesting that these Cd transporter families seem to be highly conserved throughout the evolutionary lineage of the entire plant kingdom, thereby indicating an evolutionarily conserved function of them in the metal homeostasis of these transporters (Figure 1). However, the OPT protein family was not detected in all algal species (Table 1). [PERSON] et al. [96] attempted to find the YS1-like proteins in the genome sequences of green alga _Chlamydomonas reinhardtii_ and red alga _Cyanidioschizon merolae_ but failed to identify any homologs. Likewise, a previous phylogenetic analysis of 325 OPT family members, ranging from prokaryotes to eukaryotes, revealed that OPT family members in eukaryotes were found only in fungi and land plants [97]. Thus, it may be suggested that the OPT family evolved after the emergence of land plants.
# Fine-Grained High-Utility Dynamic Fingerprinting Extraction for Network Traffic Analysis
## 3 Data Processing
### DNS Domain Text Clustering
After the DNS graph is established, the importance of nodes is used as the feature vector of DNS messages. The PageRank algorithm was first used in the Google search engine. In order to accurately rank web pages, the number and quality of links in web pages are used to measure the importance of web pages. The directed graph \(G=(V,E)\) constructed by DNS messages is similar to the web-page ranking in search engines, in order to find important node information. Assume that \(n\) is the number of nodes, \(V\) and \(E\) represent vertices and edges, and the PageRank value \(G(i)\) of vertex \(i\) is shown in (7):  
\[G(i)=\sum_{(i,j)\in E}\frac{G(j)}{K_{j}} \tag{7}\]  
Calculate the PageRank value of each node, and use \(G\) to represent the PageRank value of all nodes, as shown in (8):  
\[G=\left(G(1),G(2),\cdots,G(n)\right)^{T} \tag{8}\]  
Assume that \(A\) is the adjacency matrix of graph \(G\), as shown in (9):  
\[A_{ij}=\left\{ \begin{array}{ll}\frac{1}{K_{i}},&if(i,j)\in E\\ 0,&if(i,j)\
otin E\end{array} \right. \tag{9}\]  
Then, (7) can be converted into (10):  
\[G=A^{T}G \tag{10}\]  
In reality, the process of users surfing the Internet is relatively complex. The PageRank algorithm assumes that surfing the Internet is a random process. In order to make \(A\) meet this condition, Equation (10) is improved, as shown in (11):  
\[G=((1-f)\frac{E}{n}+fA^{T})G \tag{11}\]  
\(E\) is the full 1 matrix,\(f\) is the attenuation factor, and (11) can be converted into:  
\[G=(1-f)e+fA^{T}G \tag{12}\]  
Therefore, (7) can be expressed as follows:  
\[G(i)=(1-f)+f\sum_{(ij\in E)}\frac{G(j)}{K_{j}} \tag{13}\]  
The calculation process of PageRank is a cyclic process. Given an initial value, the PageRank value of the node is calculated. When the change is less than the threshold value, the calculation is stopped. Calculating the PageRank value of the domain name can extract important domain names, the appearance of these important domain names often has certain meaning, and new domain names through manual analysis can have important roles in helping in anomaly detection. The generation of the network DNS message is continuous. In order to process the newly generated messages in real time, the single-pass incremental clustering algorithm is adopted. Firstly, the eigenvalues of vectors of each class are calculated as the cluster centers, and the similarity is used as the judgment criterion whenever a new message is generated, as shown in (14):  
\[Sl(M,n)=\frac{|M\cap n|}{M} \tag{14}\]  
\(M\) is the clustering center vector, and n is the feature of DNS messages. The classification of DNS messages is determined through similarity calculation. After a certain period, a new DNS is generated, and the clustering center is recalculated according to the clustering result.
## 3 The Proposed HSDW-MI Algorithm
### Two Phases of the HSDW-MI Algorithm
#### 3.2.2 Dynamic Weighting Phase of HSDW-MI Algorithm
1 Train a base classifier C on Dt, E\(\leftarrow\)[C];
2 Initialize the weights of the current classifier;
3 for Dt in S
4 According to the hybrid sampling phase to get the balanced data chunk \(D_{t}^{\prime}\);
5 for \(j\leftarrow\)1 to \(L\) do
6 Calculate the G-mean value of the classifier \(C_{j}^{t}\) trained by the current data chunk \(D_{t}^{\prime}\) using Equation (8): \(GM^{t}=\left(\prod\limits_{i=1}^{n}\frac{TP_{i}}{TP_{i}+TP_{i}}\right)^{\frac{1 }{2}}\);
7 Update the weights of classifier \(C_{j}^{t}\) using Equation (9): \(w_{j}^{t}=GM_{c_{j}}^{t}\times w_{j}^{t-1}\);
8 if \(w_{j}^{t}<\theta\) Remove classifiers that are below the threshold \(\theta\) in the ensemble: \(E\gets E-\left(C_{j}^{t}\middle|w_{j}^{t}<\theta\right)\) ;
10 Create a new base classifier \(C_{new}\) on the data chunk \(D_{t}^{\prime}\) and add \(C_{new}\) to \(E\);
11 Initialize the weights of \(C_{new}\), \(w_{C_{new}}^{t}\gets 1\);
12 end if
13 end for
14 end for
15 Output ensemble \(E\) and predicted label \(\overset{\wedge}{y}\). ```  
**Algorithm 2**The Dynamic Weighting Phase of HSDW-MI  
Lines 1-2 of Algorithm 2 represent the training of the initial base classifier in the ensemble and initialize the weights. Lines 3-4 represent obtaining the balanced data chunk by hybrid sampling. Lines 5-7 represent the dynamic weighting process of the classifiers in the ensemble. Lines 8-14 represent removing the base classifiers in the ensemble whose weights are below the threshold \(\theta\). Line 15 represents the output of the final result.
# Evaluation and Comparison of Spatial Clustering for Solar Irradiance Time Series
## 2 Solar Irradiation Time-Series Analysis
### Data Quality Control  
A necessary condition to establish objective conclusions in clustering is to work with valid data. For this reason, the quality control of measured (SIAR) and estimated time series in clear-sky conditions (CAMs McClear) should be performed. Generally, several problems occur in solar-data acquisition, such as failures of the acquisition system, synchronization issues, incorrect measurements at sunset or sunrise (due to high azimuth angles), or other artifacts. [PERSON] et al. [44] and [PERSON] et al. [45] studied this critical topic of quality check and proposed efficient Quality-Control Procedures (QCPs) for solar data. They showed that, after checking the plausibility of data, some visual support (graphs and histograms) helps in the interpretation of this quality check. We drew inspiration from these two papers to establish our own QCP, which is described in Figure 4.  
We modified the previous methods a little bit in view to, in our opinion, make them more relevant for the data studied in this study: kt analysis based on geographic clustering. These processes are essential to extract relevant information for data mining and analysis tasks of solar-energy time series [46]. The QCP methodology is based on four main steps:  
* GHICs correction related to a possible offset corresponding to an erroneous time stamp: clock issue or stations' location approximation (see Section 2.3.1);
* Visual validation of kt series to easily identify significant measurement errors (see Section 2.3.2).
* Quality evaluation of data provided by SIAR system and discarding of the stations with more than 30% of over-irradiance data (see Section 2.3.2).  
Figure 4: Proposed methodology for evaluation, correction, and cleaning of solar-irradiance data series.  
* Detection of the kt outlier. The data that are much larger than 1.2 are removed (see Section 2.3.3).
# On the Use of the Effective Width for Simply Supported Generally Loaded Box-Girders
## 1 Introduction
Indeed, the standards recalled above give formulas valid for a limited number of different load conditions, since a general formulation is missing in the scientific literature. On the other side, the authors of this paper developed, in [35], a simple analytical model supplying a closed-form expression for a simply supported beam experiencing a sinusoidal deflection of half-wavelength equal to an integer submultiple \(n\) of the span. The tool was used to study free vibrations of a box-girder via the adapted classic model (Euler-Bernoulli, Timoshenko), accounting for the shear lag. The idea of this paper is to use such an \(n\)-depending effective to analyze static problems. Indeed, since any load can be expanded in a sinus Fourier series, it is possible to associate a different effective width to each of the harmonic components. By superimposing the effects, displacements and stresses, triggered by the original load, can be computed. The primary objective of this work is to evaluate, in each cross-section of the box-girder, the maximum value of the normal and tangential stresses. In particular, in each cross-section, the maximum normal stress occurs at the nodes, while maximum tangential stresses occur at the nodes of the flange and in the middle of the web. The proposed procedure, thanks to its user-friendliness, is intended as a valid alternative to consider the shear-lag effect in bridge designs. Always in the framework of the Fourier analysis, the evaluation of displacements by using the Euler-Bernoulli beam model with the \(n\)-dependent inertia moment is proposed. Displacements by Euler-Bernoulli and Timoshenko beams with integer geometric characteristics are also illustrated for comparison. Finally, the idea of an average effective width, which by still keeping the necessary dependence on the load shape avoids the need to employ a series expansion, is suggested here. This average effective width is intended as a medium value of the wavelength-dependent effective widths, and it can be obtained by imposing the equivalence of the displacements, or of the normal stresses, in a significant point of the beam. The paper is organized as follows. In Section 2, the problem is defined, and the analytical expression derived in [35] for the effective flange width is recalled. In Section 3, making use of the reduced geometric characteristics, analytical expressions for both normal and tangential stresses are derived and discussed. In Section 4, always in the framework of the Fourier analysis, the deflections of the beam are evaluated by three different models of increasing refinement. In Section 5, the analytical formula for the average effective width for different load conditions is obtained and compared to the literature. In Section 6, displacements and stresses of a box-girder taken from the literature under different load conditions are evaluated by the present method and numerical results are discussed vs. Finite Element analyses. In Section 7, some conclusions are drawn.