esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimization of PFMEA Team Composition in the Automotive Industry Using the IPF-RADAR Approach
## 3 Methodology
### Modelling Uncertain Values of Criteria Weights  
The determination of criterion weights can be performed in various ways. If the results are reliable and the problem under consideration corresponds to a problem from the literature, the weights can be adopted from such a source [17]. Another approach is direct estimation, which is most commonly used when there is a single decision-maker. Furthermore, weights can be determined by aggregating the assessments of decision-makers, as applied in [47; 48; 49]. Another method involves applying various MADM techniques, as demonstrated in [18; 50; 51; 52].  
In this study, the criteria weights were determined by aggregating the assessments of decision-makers, \(e,\ e=1,\ldots,E\) using the fuzzy addition operator, where the sum of the assessments was divided by the total number of decision-makers, \(E\). As already stated in the introductory chapter, the decision-makers were as follows: a shift manager \((e=1)\), an HR specialist \((e=2)\), and a production supervisor \((e=3)\). The decision-makers provided their assessments of criteria importance independently in written form via email.  
Based on the recommendations of the AIAG&VDA Handbook [2] regarding the knowledge and skills of PFMEA team members, and in collaboration with the decision-makers, the following criteria were defined: knowledge of the considered process/product \((k=1)\), experience working in a PFMEA team \((k=2)\), interdisciplinary expertise \((k=3)\), and communication skills and teamwork abilities \((k=4)\). It is important to emphasize that all criteria are of a benefit type.  
For expressing their assessments, the decision-makers used the following linguistic terms modelled using IVPFNs:  
* Completely unimportant criterion (C1): \(\{[0.0,0.2],[0.8,1.0]\}\);
* Unimportant criterion (C2): \(\{[0.2,0.4],[0.6,0.8]\}\);
* Moderately important criterion (C3): \(\{[0.4,0.6],[0.4,0.6]\}\);
* Important criterion (C4): \(\{[0.6,0.8],[0.2,0.4]\}\);
* Very important criterion (C5): \(\{[0.8,1.0],[0.0,0.2]\}\).  
As can be seen, the domain of IVPFNs is within the interval from 0 to 1. A membership degree value closer to 1 indicates a higher criteria importance, and vice versa. The opposite rule applies to the non-membership degree.
# Android Malware Detection Based on Hypergraph Neural Networks
## 4 Methodology
### Hypergraph Construction  
After obtaining the FCG and vertex features of the android application, the next step is to focus on the construction of the hypergraph, which is mainly the construction of hyperedges. We propose two schemes for the construction of hyperedges:  
K-order Common Call Hyperedges: The case where the same function calls multiple other functions is common in android applications, and such multiple co-calls reflect dependencies or similar functional relationships between multiple functions. Therefore, this paper proposes to construct a hyperedge using the K-order nearest neighbors of a function. When \(K>1\), the hyperedge is able to model a complete calling relationship, as shown in Figure 2. Intuitively, the longer the call relationship, the better it may be at passing relevant information about the underlying functionality to the central function, such as using the underlying interface to retrieve user read and write permissions, monitor user action behaviour, etc. Here, K is the hyperparameter of the method. A larger K may involve some unimportant neighborhood vertices and bring noise into the information transfer, and a smaller K can only model local information and cannot reflect the advantages of hypergraph modeling; thus, K needs to be adjusted specifically for the actual task.  
Common Permission Hyperedges: Inspired by APIGraph [6], this paper constructs a set of hyperedges for functions that share permissions. First, Androgurad is used to parse the APK manifest file to obtain the system permissions required by each function. The set of system permissions is selected, where each permission is treated as a hyperedge and the functions that require this permission belong to this hyperedge. In android, public permission requests usually express high-level semantic information about the function's functionality; thus, using common permissions to build hyperedges is useful for discovering similar functional features between functions.
# Experimental Evaluation of the Blackbody Radiation Shift in the Cesium Atomic Fountain Clock
## 5 Conclusions  
Reducing the uncertainty of BBR shift in the cesium fountain clock plays a vital role in improving its performance. The uncertainty of BBR shift in the room-temperature fountain clock is mainly affected by the temperature fluctuations in the atomic flight zone. In this study, through theoretical analysis and experimental testing, a fountain system structure with uniform temperature and good heat preservation was designed, and new methods of measurement of the temperature of the fountain clock system were researched. The temperature of the outer wall of the vacuum pipe in the atomic flight zone was accurately measured experimentally, and the temperature distribution and changes in the resonant cavity and the atomic flight zone were obtained from the results of finite element analysis. The total temperature uncertainty was less than 0.12 \({}^{\circ}\)C, and the resulting uncertainty of BBR shift was 2.4 \(\times\) 10\({}^{-17}\), which corresponds to the international advanced level. In view of the current problem of the large uncertainty of the BBR shift in the cesium fountain clock at room temperature, we will carry out further research on the cryogenic cesium fountain clock in the future, with the goal of greatly reducing the sensitivity coefficient of this uncertainty using the liquid nitrogen cooling method, thereby reducing the uncertainty of the frequency shift in the fountain clock and improving its performance.  
Conceptualization, F.Y. and X.W.; methodology, F.Y. and X.W.; software, D.L.; validation, J.R. and Q.H.; formal analysis, Y.G.; investigation, J.S.; resources, J.R.; data curation, S.F. and H.Z.; writing--original draft preparation, F.Y.; writing--review and editing, F.Y.; visualization, Y.B.; supervision, S.Z.; project administration, J.R.; funding acquisition, J.R. All authors have read and agreed to the published version of the manuscript.  
Figure 6: Temperature distribution on the central axis of the atomic flight zone.  
**Funding:** This research was funded by Chinese Academy of Sciences for Western Young Scholars, grant number XAB2018A06, XAB2018B16, and XAB2019A07; Large Research Infrastructures Improvement Funds of Chinese Academy of Sciences, grant number DSS-WXGZ-2020-0005; and National Natural Science Foundation of China, grant number 12173044.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data are contained within the article.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 7 Results and Discussion
From the results obtained without any interference, we find the code sequence chip time duration \(T_{c}=2.6\) ps, and the optimal value of \(P=53\), and thus, the bit time duration can be calculated as  
\[T_{b}=P^{2}T_{c}=2809\times 2.6\text{ ps}=7.3\text{ ns}\]  
Furthermore, the bit rate \(R_{b}=\frac{1}{T_{b}}=137\) Mbps, and the network throughput equals 137 Mbps \(\times\) 1310 user \(=180\) Gbps \(*\) user. The EVM% versus the system OSNR for different types of modulation schemes is presented in Figure 14. This figure illustrates that the proposed 256-DPPM/WMPC scheme outperformed the other modulation schemes for any EVM%. Moreover, when the proposed scheme was considered, the EVM% was the lowest at any OSNR. Furthermore, at 30 dB OSNR, the EVM% was 17%, 5%, and 2% for the 64-DPPM, 256-DPPM, and 265-DPPM/WMPC modulation schemes, respectively. This was due to the sufficient optical signal received at the receiver and the high efficiency of the proposed hybrid modulation/coding scheme. Table 6 compares the published and proposed techniques for underwater optical and wireless communication systems. This comparison includes the BER performance, transmission distance, number of active users, bit rate, and network throughput. From this comparison, we observe that the proposed modulation/coding scheme outperforms other published methods in terms of transmission distance and network throughput. Figure 13: BER performance versus the number of active users N for the 256-DPPM/WMPC-OCDMA system for pure seawater, with C = 0.03, at 460 nm, receiver aperture area of 0.05 m\({}^{2}\), and different values of the WMPC prime number P.
## 3 Results
### Membrane Distillation Performance
The coated PES membrane has relatively high bulk porosity, but as shown in Table 3, the membrane is not symmetric and has a more dense structure at the surface and in the first 100 \(\upmu\)m. This causes less mass transport and more heat transport through the membrane in the first 60 \(\upmu\)m, reducing the energy efficiency. Membranes applied with the same application systems (membrane 3 and 5 and membrane 6 and 7) have equal energy efficiency, regardless of the fact that the resulting membrane is a hydrophobic/hydrophilic membrane or a membrane with 2 hydrophobic surfaces. This can be explained by the independence of the energy efficiency as function of membrane thickness, which is shown by different authors [20; 48]. This independency occurs because both heat transfer due to flux and heat transfer due to conduction are approximately inversely proportional to the membrane thickness. A high salt retention above 99.9% was measured for all membranes. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Membrane** & **Structure** & **Flux (kg\(\cdot\)m\({}^{-2}\cdot\)h\({}^{-1}\))** & **Energy Efficiency (\%)** & **Salt Retention (\%)** \\ \hline
1 & hydrophobic/hydrophilic & & & **Wetted** \\
3 & hydrophobic/hydrophilic & 16.2 \(\pm\) 0.5 & 55 \(\pm\) 2 & 99.98 \(\pm\) 0.01 \\
4 & hydrophobic/hydrophilic & 0.4 \(\pm\) 0.3 & - & 99.99 \(\pm\) 0.01 \\
5 & 2 hydrophobic surfaces & 14.5 \(\pm\) 0.5 & 50 \(\pm\) 2 & 99.99 \(\pm\) 0.01 \\
6 & hydrophobic/hydrophilic & 16.1 \(\pm\) 0.1 & 44 \(\pm\) 3 & 99.92 \(\pm\) 0.06 \\
7 & 2 hydrophobic surfaces & 13.9 \(\pm\) 0.1 & 43 \(\pm\) 5 & 99.99 \(\pm\) 0.01 \\ PVDF & hydrophobic & 12.0 \(\pm\) 0.1 & 52 \(\pm\) 2 & 99.99 \(\pm\) 0.01 \\ PE & hydrophobic & 15.3 \(\pm\) 0.4 & 67 \(\pm\) 4 & 99.99 \(\pm\) 0.01 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Flux, energy efficiency and salt retention. Process conditions: \(T_{f}\) = 60 \({}^{\circ}\)C, \(T_{p}\) = 45 \({}^{\circ}\)C, \(v\) = 0.13 m\(\cdot\)s\({}^{-1}\), NaCl concentration = 35 g\(\cdot\)L\({}^{-1}\).
## 2 Materials and Methods  
### Used Configurations and Method Overview  
Two main configurations are investigated; the first one represents the implanted femur without soft tissue while the second one represents the implanted femur with soft tissue.  
The first configuration consists of the femoral implant (Profemur Gladiator Hip Stem, Wright 5, Microport), inserted in the cavity of the surgically prepared artificial femur (model 3403, Sawbones, Malmo Sweden).  
To represent the soft tissue that surrounds the biological femur bone, a biological soft tissue mimicking phantom is used, which is referred to as soft tissue, for brevity. The second configuration consists of the femur-implant structure surrounded by the soft tissue and the cylindrical container holding the artificial soft tissue.  
The term implant insertion refers to the process of progressively hammering the implant into the femur. Each resulting structural state, following an insertion hit, is referred to as an insertion step.  
The following two experiments were performed to investigate the influence of the soft tissue on the VA monitoring technique during implant insertion: (a) Implant insertion experiment without soft tissue. During this experiment the vibrational properties of the femur-implant structure during an insertion without soft tissue surrounding the femur were investigated. (b) Implant insertion experiment with soft tissue. During this experiment the vibrational properties of the femur-implant structure during an insertion with soft tissue surrounding the bone were investigated.  
The two aforementioned experiments feature two individual implant insertions, during which, it is not guaranteed that the exact same implant fixation condition will be encountered. As a result, a third experiment was conducted to identify the influence of the soft tissue on the femur-implant structure for the exact same implant fixation condition. This was achieved by means of a comparative test pre and post soft tissue addition, during which, the vibrational properties of the femur-implant structure were recorded before and after adding soft tissue, without altering the fixation state of the implant in the femur between the measurements.
# Study of Diagnostic Accuracy: Fundus Photography vs. Optical Coherence Tomography
## 2 Materials and Methods
### Test Procedure
#### 2.2.1 Assessment Step  
An optometrist external to the analysis performed the tests on each patient and, afterwards, encrypted the information derived from the examinations performed. The data were sent to the groups of examiners (optometrists and ophthalmologists) in two different files: one with the patients' information, visual acuity, and FP (stage I) and another with this information plus the reports obtained using the macula 3D OCT and optic nerve 3D OCT (stage II). Figures 2 and 3 show an example of the information sent to examiners at Stages I and II to assess each eye.  
The information gathered during these examinations, the best corrected distance visual acuity, and the stored digital images (FP non-mydriatic imaging and report of macula 3D OCT and optic disc 3D OCT) were independently graded by the two research groups. Both independently graded the posterior pole of each eye based on the masked information provided in each assessment stage.  
Assessment stages:  
* Stage I: based on a conventional eye examination and FP.
* Stage II: based on a conventional eye examination, FP, and OCT.  
Figure 2: Information sent in Stage I: patient information, visual acuity, and FP non-mydriatic image. Patient was 52-year-old Spanish woman with a corrected distant visual acuity (CDVA) value of 1.0.  
The eye fundus classifications were made following the criteria previously established by the group of ophthalmologists and optometrists to ensure the consistency of the analysis methods. The eye fundus was classified as follows:  
1. Not evaluable: images are of insufficient quality to categorize the state of the fundus of the eye.
2. Evaluable: images are of sufficient quality to categorize the state of the eye fundus. The evaluable cases could be healthy or have abnormalities. The eyes with abnormalities were classified in two groups depending on the severity of the alteration, referable or preferential referable (Figure 4).  
1. Healthy includes cases that have a normal appearance, which rules out any pathological alterations in its characteristics aside from those associated with age.
2. Referable includes cases with physiognomic characteristics that lead to an alteration that must be assessed as minor or major, as measured by an oph  
Figure 3: Information sent in Stage II: patient information, visual acuity, FP non-mydriatic image and OCT report 3D of macula (**A**) and optic disc (**B**). Patient was a 52-year-old woman with a CDVA value of 1.0.  
thalmologist at any point in time. These cases include those that present an abnormal appearance that modifies the retinal morphology and a structure that shows deterioration in the ocular health of the posterior pole.  
Preferential referable includes cases with characteristics that suggest any alteration that must be evaluated by an ophthalmologist within a short period of time.
# A Control-Oriented Linear Parameter-Varying Model of a Commercial Vehicle Air Brake System
###### Abstract  
This paper presents a control-oriented LPV (Linear Parameter-Varying) model for commercial vehicle air brake systems, where a pneumatic valve actuator is used to control the brake chamber pressure. To improve the brake system response time and reduce the vehicle stopping distance, the traditional treade valves used in the air brake system are replaced by electro-pneumatic valves. Also, to develop the model-based brake control strategy, a nonlinear mathematical model is developed based on [PERSON]'s second law, fluid dynamics of the orifice, force balance of spool, and solenoid dynamic characteristics. The brake chamber dynamics is also considered during the charging and discharging processes. The developed nonlinear model is calibrated based on both valve actuator geometry and test bench experimental results. It is proposed to model the nonlinear system in the LPV form so that gain-scheduling controllers can be developed. To obtain the LPV model, system identification is conducted using the calibrated nonlinear model to obtain a set of linearized models under different brake chamber pressure levels, and the resulting identified linear models are assembled to form the LPV model with brake chamber pressure as the varying parameters. A linear infinite-horizon continuous-time LQR (Linear Quadratic Regulator) controller was designed for the braking system based on the developed LPV model with the fixed parameter to demonstrate the effectiveness of the developed LPV model.  
air brake system; proportional valve; control-oriented model; linearization through system identification; LPV model +
Footnote †: journal: Applied Mechanics and Physics Letters
# Immobilised Humic Substances as Low-Cost Sorbents for Emerging Contaminants
## 2 Materials and Methods
### Characterization of Immobilized Humic Substances  
The HSs were characterized in order to better understand their structures, including the content of elements (C, H, N, O) and phenolic and carboxylic groups, and obtain thermogravimetric analysis data. Scanning electron microscopy gave insight into the surface morphology of the HSs after immobilization and thus provided an opportunity to compare the visual differences in the surface morphology of the studied materials before and after immobilization. The BET (Brunauer-Emmett-Teller) method was used to determine one of the most important parameters of the sorbent: the specific surface area.  
The elemental analysis (C, H, N and O) was carried out using a model EA-1108 elemental analyzer (Carlo Erba Instruments, Egelsbach, Germany), and the discovered values were normalized with respect to the ash content. The ash content was measured after heating 50 mg of each HS sample at 750 \({}^{\circ}\)C for 8 h.  
The carboxylic and phenolic groups of each HS sample were determined using a TitroLine easy automatic titrator (Schott-Gerate GmbH, Mainz, Germany). The well-known Ca acetate method [18], based on the formation of acetic acid, was used for determining the total number of carboxylic groups. For this, 20 mg of the immobilized HSs was weighed into a 100 mL Erlenmeyer flask, and 10 mL of a 0.2 N calcium acetate solution was added under an N\({}_{2}\) atmosphere. The samples were potentiometrically titrated to a pH of 9.0 with 0.1 N NaOH. To estimate the total acidity, 20 mg of the sample was dispersed in 10 mL of a 0.1 M Ba(OH)\({}_{2}\) solution, which was then shaken overnight under an N\({}_{2}\) atmosphere, filtered and washed with water. The filtrate, together with the washing solution, was potentiometrically titrated with 0.1 M HCl down to a pH of 8.4 under an N\({}_{2}\) flow.  
Thermogravinetric analysis (TGA) was performed by weighing a 5 mg sample into a ceramic crucible, which was then analyzed with a TA Instruments-Waters LLC SDT Q600 (New Castle, DE, USA) under an N\({}_{2}\) atmosphere at a gas flow rate of 100 mL/min. The temperature increase was 15 \({}^{\circ}\)C/min, and the samples were heated from room temperature to 105 \({}^{\circ}\)C and kept isothermal for 2 min to eliminate moisture. The heating was then continued to 900 \({}^{\circ}\)C. The weight loss and derivative data were recorded.  
Scanning electron microscopy (SEM) was used to determine changes in the surface morphology of a sample after immobilization of the HS. The sample was applied to a double-sided disc made of a carbon-based material that was electrically conductive. The samples were placed in a Hitachi S-4800 scanning electron microscope with a voltage of 3.0 kV. Image J was used for data processing.  
The surface area of the sorbents was measured using a Quantachrome QUADRASORB SI Kr surface area pore size analyzer with a standard Autosorb degasser. The Langmuir method was used for specific surface area measurements.
# Quantum Leap from Gold and Silver to Aluminum Nanoplasmonics for Enhanced Biomedical Applications
## 3 Applications
### Plasmonic Medicine
#### 3.2.1 Plasmonic Cancer Diagnosis and Treatment
HET showed a synergistic combination of PTT and PDT on HeLa cells by generation of reactive oxygen species (ROS) from TiO\({}_{2}\) Au nanorod (NR) conjugates (Figure 4a,b) [180]. A different mechanism of photothermal therapy of HeLa cells was also shown by using continuous wave and pulsed laser sources on Au NPs to produce singlet oxygen (\({}^{1}\)O\({}_{2}\)) by hot electrons (Figure 4c) [181]. The biomedical applications of hot electrons go beyond PTT and PDT. Hot electron transfer from Au NPs was used to generate plasmon-induced activated (PIA) water with reduced intermolecular hydrogen bonds [182]. PIA water has shown anti-inflammatory and anti-oxidative properties, thereby preventing the oxidative stress caused by the acute inflammation [183]. Alumina (Al\({}_{2}\)O\({}_{3}\)) NPs have also been used in cancer therapy. Poly-\(\gamma\)-glutamic acid functionalized alumina nanoparticles (\(\gamma\)-PAN) were evaluated for protein adsorption ability, and found to lower cell viability in a prostate cancer cell (PC-3) line through ROS production and oxidative stress [184]. Therapeutic cancer vaccination based on T-cells is hindered by difficulties to produce large amounts of cells using current vaccine carrier systems [185]. Al\({}_{2}\)O\({}_{3}\) NPs were shown to carry antigens to autophagosomes in dendritic cells, reducing the number of antigens required to activate T-cells [186]. It was found that immunization of mice with Al\({}_{2}\)O\({}_{3}\) NPs conjugated to tumor antigens resulted in tumor regression. These studies encourage the use of Al\({}_{2}\)O\({}_{3}\) NPs as adjuvants for cancer vaccines [187]. Alumina NPs can depolarize cell membranes, causing cytotoxicity in human epithelial A549 lung cells [188]. In order to enrich ubiquitinated proteins from cancer cells, Al\({}_{2}\)O\({}_{3}\) NPs were covalently linked to ubiquitin-binding protein and showed that dendritic cells could more effectively phagocytize the protein/alumina nanoparticle complexes, increasing the antitumor response [189]. Aluminum garnet particles were also used for imaging and PDT of cancer cells [190].