esa-sceva/satcom-chunk-collection huggingface dataset:
# Vibration and Reliability Analysis of Non-Uniform Composite Beam under Random Load
## 3 Numerical Studies, Results and Discussion
### Reliability Analysis of Non-Uniform Composite Beam with Different Design Parameters  
In order to study the influences of different design parameters on the vibration reliability, the reliability of non-uniform beam with different taper ratios, \(n\) and \(m\), were calculated under the same random load with \(\left(\,A_{a}\,\sim N\big{(}50,10^{2}\right)\,\mathrm{m}/\mathrm{s}^{2}\) and \(\,\varphi\,\sim N\left(200,\left(200/15\right)^{2}\right)\,\mathrm{rad}/ \mathrm{s}\)). Other constant parameters are \(b_{0}=0.005\) m, \(h_{0}=0.001\) m and \(h=1.5\). When studying the influence of the change of \(m\) on vibration reliability, \(n\) is a constant of 2. Similarly, when \(n\) changes, the value of \(m\) is a constant of 2.5. The results are shown in Figure 6.  
It can be seen from Figure 6 that within the range of parameters studied, the reliability of the non-uniform composite beam increases with the increment of \(n\) and decreases with the increment of \(m\). It can be concluded that the taper design itself of the non-uniform composite beam will affect the structural reliability. It should be noted that  
Figure 5: Vibration responses (maximum amplitude and strain) and reliability of beam in different periods of time.  
Figure 6: Vibration reliability of non-uniform composite beam with different \(m\) and \(n\).  
the exact structural reliability variation trend will also depend on the excitation. The iteration mathematic model proposed in this paper can be used to solve and analyze the vibration responses and reliability of non-uniform composite beam with different design parameters. For the multiple layered composite beam, different design parameters lead to different reliability results. Reasonable design under random loading condition with certain variation range of its frequency and amplitude can enhance structural reliability.
# Node-Based Optimization of GNSS Tomography with a Minimum Bounding Box Algorithm
## 2 Methodology  
### Observations Used in the Tomographic Model  
For successful tomographic modeling, the slant wet delay (SWD) or slant water vapor (SWV) needs to be estimated in the tomographic equations. As part of the wet, the SWD is separated from the slant total delay (STD), which is produced due to the GNSS signals across the entire atmosphere. The SWD can be approximated by  
\[\mathrm{SWD}(el,az)=\mathrm{m}_{\mathrm{w}}(el)\cdot\mathrm{ZWD}+\left[\mathrm{ m}_{\mathrm{G}}(el)\cdot\left(\mathrm{G}_{\mathrm{W}}^{\mathrm{N}}\cdot\cos( az)+\mathrm{G}_{\mathrm{W}}^{\mathrm{E}}\cdot\sin(az)\right)+R_{\mathrm{c}}\right] \tag{1}\]  
where \(\mathrm{SWD}(el,az)\) is the function of the SWD, \(\mathrm{m}_{\mathrm{w}}\) (\(el\)) is the wet mapping function; ZWD is the zenith wet delay; \(\mathrm{m}_{\mathrm{G}}\) (\(el\)) is the gradient mapping function; \(\mathrm{G}_{\mathrm{W}}^{\mathrm{N}}\) is the north-south gradient; \(\mathrm{G}_{\mathrm{W}}^{\mathrm{E}}\) is the east-west gradient; \(R_{\mathrm{c}}\) is the cleaning postfit residuals [21].  
The SWD is used as the tomographic observation, or it can be further converted into SWV by  
\[\mathrm{SWV}=Scal\cdot\mathrm{SWD} \tag{2}\]  
where \(Scal\) is the conversion factor [22; 23].  
In GNSS tomographic solution process, the SWV is then used as the GNSS tomographic observation for the estimation of water vapor densities at each node in the tomographic model.
## 2 Results and Discussion
### Starvation as a Mode of ITC Action against V. cholerae
Bacteria were grown in MOPS labeling medium in the presence of 150 uCi/mL [32P]Orthophosphoric acid with various concentrations of ITC or starved for amino acids by the addition of SHX. The labeled guanosine nucleotides separated on TLC are presented in the panels. The percentage of ppGpp in the total pool of guanosine nucleotides in various conditions is presented on the graphs. The results presented are mean values from 3 independent experiments. The significance of differences between the results and the control was tested using the Student’s _t_-test. Statistical significance is marked with asterisks: *** \(p\) < 0.001; ** \(p\) < 0.01.  
two enzymes conservative for enterobacteria, RelA and SpoT, and the third one is RelV, which to date seems to be specific just for this species. In the recent studies, we showed that ITC action in _E. coli_ relies on amino acid starvation pathway mediated by RelA [22; 25], and _relA_ deficient strain was unable to accumulate (p)ppGpp in response to ITC. It indicated that the stringent response induction by ITC is mediated by amino acid starvation. Antimicrobial activity of SFN and PEITC was also affected by the supplementation of a culture medium with several amino acids and tri-peptides [22; 25; 45]. Isothiocyanate group (-NCS) was proposed to be an electrophilic functional group prone to react with both amines and thiols [46; 47]. Nonetheless, the interactions with specific cellular targets were also reported [48; 49]. [PERSON] and colleagues showed direct enzymatic inhibition of thioredoxin reductase and acetate kinase in enterohemorrhagic _E. coli_ O157:H7 by AITC [49]. We can assume that the observed morphological changes and metabolic downregulation of nucleic acid synthesis in _V. cholerae_ as the response to tested ITC are connected with rapid elevation of (p)ppGpp levels. However, the genetic and molecular background of this phenomenon should be further investigated, especially the role of _relV_ in the stringent response mechanism of _V. cholerae_.
## 6 Discussion
### Implications for Educators and Developers
#### 6.2.3 Future Trends  
In the future, including DFDLOF in education settings demands continuous research and development in educational technology. The emergence of these advanced learning systems underscores the growing imperative for interdisciplinary collaboration between educators, technologists, and researchers to support ongoing enhancement.  
The DFDLOF framework, its strengths, and its limitations have important implications for the future of education. For educators, the framework introduces a tool to improve the teaching and learning process; for developers, it indicates the value of user-centric, secure, and ethically designed educational technologies. This framework lays the groundwork for future personalized education innovations that promote a more data-driven, adaptive, and learner-focused character of education.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Aspect** & **Strengths or Limitations** & **Example/Analysis** \\ \hline Adaptability & Strength & \begin{tabular}{l} Dynamically adapts learning content to individual needs, enhancing engagement and outcomes. \\ \end{tabular} \\ \hline Data-Driven Approach & Strength & \begin{tabular}{l} Provides insights into learning patterns, enabling informed decisions in curriculum design. \\ \end{tabular} \\ \hline Real-Time Feedback & Strength & \begin{tabular}{l} Offers immediate response to learner inputs, correcting misconceptions and supporting continuous learning. \\ \end{tabular} \\ \hline Integration Complexity & Limitation & \begin{tabular}{l} Challenging to integrate into existing educational infrastructures due to data and expertise requirements. \\ \end{tabular} \\ \hline Data Privacy and Security & Limitation & \
\begin{tabular}{l} Heavy reliance on learner data raises concerns about data security and ethical use. \\ \end{tabular} \\ \hline Applicability in Diverse Contexts & Limitation &
\begin{tabular}{l} Effectiveness in diverse cultural and socio-economic settings needs further exploration for broader applicability. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 5: Strengths and limitations of the DFDLOF framework.
# Determination of Point-to-Point 3D Routing Algorithm Using LiDAR Data for Noise Prediction
## 3 Methodology
### Building Corner Extraction Step 1 to Step 3
#### 3.3.3 Reflection Route  
Route followed by noise following the law of reflection, which states that the angle of incidence is equal to the angle of reflection [38]. According to the [PERSON]'s law for reflection, the angle made by the incident ray is equal to the reflected ray that is \(\text{Sin }\alpha\) (i) = \(\text{Sin }\beta\) (r), where, \(\alpha\) and \(\beta\) are incident and reflected angle (as shown in Figure S10) [39]. The basics of [PERSON]'s law are mentioned in Supplementary Section S2.3.3. For the reflection route, there are two types of routes (a) ground reflection routes and (b) wall reflection routes.  
1. Ground Reflection: Reflection through the ground. The ground may be uniform and non-uniform. There are two cases formed, one for uniform and other for non-uniform ground. Both cases are discussed in Supplementary Section S2.3.3 (c). An example for ground reflection is shown in Figure 11(a),b.
2. Wall reflection Route: Route that is calculated after reflection of noise signal from the wall of building. Procedure for wall reflection route is provided in Supplementary Section S2.3.3 (c). Result is shown in Figure 13.
# Void Avoidance Opportunistic Routing Protocol for Underwater Wireless Sensor Networks
## 5 Conclusions  
In this paper, we propose EEDOR-VA, a void avoidance protocol. EEDOR-VA increases the packet delivery ratio relative to our previous protocol EEDOR [15] and the established DBR [20], especially in networks with a small number of nodes where the void areas are most likely to occur, as we presented in Section 4. In addition, EEDOR-VA improves the reliability of the network by detecting void/trapped nodes in advance of data transmission using the hop count discovery process. It also reduces the number of nodes that actually transmit the data packets by using _Rank_ to distinguish between node holding times. This approach helps to decrease the energy expenditure in the data transmission process as well as packet collision and its associated cost.  
The EEDOR protocol presented in [15] is localization free, as is its enhanced version EEDOR-VA. EEDOR was the superior protocol when compared to various other depth-based algorithms in [15]. In this work, we examined EEDOR-VA in two dissimilar network topologies in addition to different transmission power levels in one of the simulated topologies.  
The analyses of experimental simulation results show that EEDOR-VA enhances network performance in terms of energy consumption, packet delivery ratio and the number of nodes that actually complete the transmitting process. We further analyzed the impact of single and multiple sinks as well as two different sink deployment techniques on the EEDOR-VA performance in terms of total energy consumption and PDR.  
Figure 17: Impact of sink deployment on the EEDOR-VA packet delivery ratio.  
Figure 18: Impact of sink deployment on the EEDOR-VA energy consumption.  
**Author Contributions:** Conceptualization, R.M., F.C., W.P., N.A.; methodology, R.M., W.P.; software, R.M., W.P., F.C., N.A.; validation, W.P., F.C., N.A.; formal analysis, R.M., F.C., W.P., N.A.; investigation, R.M.; resources, W.P.; data curation, R.M.; Writing--Original draft preparation, R.M.; Writing--Review and editing, F.C., W.P., N.A.; visualization, R.M., F.C.; supervision, F.C., W.P., N.A.; project administration, W.P.; funding acquisition, W.P, F.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Stateflow-Based Energy Management Strategy for Hybrid Energy System to Mitigate Load Shedding
## 2 The HES Architecture and Modeling in Stateflow
### The HES Structure  
The structure of the proposed HES is presented in Figure 2. It consists of a photovoltaic (PV) array, energy storage unit (ESU), and diesel generator (Gen). These components are connected to the utility grid at the distribution feeder. The grid is assumed to be incapable of satisfying the load demand throughout the day; thus, during the absence of grid power, the PV, ESU, and Gen support is expected. Structural-wise, the PV array is connected to a DC bus by means of a unidirectional DC-DC converter with the maximum power point tracking (MPPT) control. The ESU is constructed using Li-ion battery banks and is connected to the DC bus via a bi-directional DC-DC converter. Thus, the energy flow for the ESU is in both directions. The utility grid, community load, and generator are directly connected to the AC bus. The AC and DC sources are interfaced through one bidirectional inverter. This topology reduces the cost of integration of HES's components [20]. To maintain the power balance of HES, a central controller with an embedded EMS is used. Due to the centralized control, the controller requires global information to fulfill the energy management needs; thus, the communication infrastructure needs to be established [21].  
Figure 1: Hierarchical control levels of a hybrid energy system.  
Figure 2: Architecture of the proposed HES.  
If \(P_{-}Load\ (t)\) is the hourly load demand of the system, in order to maintain the power balance of the system \(P_{-}HES(t)=P_{-}Load(t)\),  
\[P_{-}HES(t)=P_{-}Grid(t)+P_{-}PV(t)+P_{-}ESU(t)+P_{-}Gen(t) \tag{1}\]  
Here, \(P_{-}HES(t)\) is the hourly net output power of HES. The \(P_{-}Grid(t)\), \(P_{-}PV(t)\), \(P_{-}ESU(t)\), and \(P_{-}Gen(t)\) are the hourly power supplied by grid, PV, ESU, and diesel generators, respectively, according to the devised EMS.
###### Abstract  
The objective was to evaluate the accuracy of ClinCheck(r) reliability in the sagittal, vertical, transverse, and arch length dimensions before and after Invisalign(r) (Align Technology, Santa Clara, CA, USA) treatment. This retrospective study was conducted on 206 patients who underwent dual-arch clear aligner therapy exclusively with Invisalign(r). Digital models were obtained from iFero(r) scanners from three different private practices where the treatment plans were performed and executed by multiple orthodontists with varying degrees of experience. The ClinCheck(r) models of the initial, achieved, and predicted outcome were obtained from Align Technology(r) and the values were compared using Pearson correlation (\(p<0.05\)) to determine if predicted values were correlated with achieved values. ANOVA was used to compare the different centers. The highest reliabilities were associated with interincisal angle (96.23%), upper intercanine width (97.97%), lower intercanine width (97.67%), upper intercanine width (97.58%), and lower intercular width (97.72%) (\(p<0.001\)). The lowest reliabilities were associated with arch length parameters in which the upper was 38.79% and the lower at 30.02% (\(p=0.03\), \(p<0.001\)). However, there were no statistically significant differences between the centers in terms of the accuracy of treatment provided. The mean predicted accuracy of Invisalign(r) was 76.85% overall; however, Invisalign(r) providers may need to exaggerate the digital tooth movements to achieve the desired outcome.  
Invisalign(r); orthodontics; clear aligners; ClinCheck(r)
## 4 Surface-Immobilized Peptides on Medical Implants
### Other Materials  
Polyethylene is a biomaterial used in joint replacement, and like titanium, it is inert. Surface oxidation approach is usually used to create functional groups suitable for further chemical reaction. PEG was used as a hydrophilic spacer molecule, linking the polyethylene surface and E14 LKK peptide (LKKLLKLLKLLKLL), derived from magainin, which was attached to the free terminus of PEG. The PEG spacer additionally provided mobility to the tethered peptides. This modification demonstrated antimicrobial activity in broth cultures against _E. coli_[169]. Additionally, polymycin B retains its microbial activity against _E. coli_, when covalently bound to glass surface, via a silane coating [170]. Studies of several coatings for catheter material were carried out, but yielded either low biocompatibility, or inefficient long-term/limited antimicrobial activity [171]. So far, AMP coatings on catheters have only been tested in one in vivo study [172], where peptide E6 (RRWRIVIVIVRVR-NH\({}_{2}\)) was attached to polyurethane material of catheter, using a polymer tethering approach. The peptide-coated catheter pieces were shown to have antibacterial properties against both Gram-positive and Gram-negative bacteria, in vitro in both culture medium and urine. In addition, they were shown to be effective in a mouse in vivo urinary track infection model. The synthetic peptide melimine, was found to reduce _P. aeruginosa_ and _S. aureus_ adhesion to contact lenses both when adsorbed or when covalently attached, and furthermore melimine was resistant to heat sterilization [94].  
Recently, a synthetic, tryptophan-rich peptide tethered on polyethylene terephthalate was capable of preventing _S. aureus_ biofilm formation in vitro, while not being toxic to human cell lines [173]. In another study, plant-derived, cyclic AMPs coupled to steel surfaces via polydopamine, demonstrated antibacterial and antibiofilm activity against _S. aureus_[174]. Chitosan films have also been used as platforms for the covalent immobilization of AMP due to the intrinsic osteogenic and antibacterial properties of chitosan [175; 176; 177; 178]. Covalent immobilization of the human lactofericin peptide hLF1-11 on chitosan films, both with and without a PEG spacer was designed. However, no improvement in the antibacterial properties was observed, as the functionalization with hLF1-11 without a PEG spacer increased the bacterial adhesion to chitosan films [179], though the viability of attached bacteria was decreased, especially with the PEG spacer.
# Least-Squares Reverse Time Migration in Imaging Domain Based on Global Space-Varying Deconvolution
## 3 Analysis of Numerical Experiments  
This section focuses on analyzing the physical characteristics of the point spread function. Figure 1 shows the global point spread function for the 2D Marmousi model. We can find the variations of observation illumination, wave propagation, and limited wavelet frequency-band at different positions. The propagation effect is mainly reflected in amplitude performance. Compared to the PSFs in the shallow model, those in the deep show much worse focusing with increasing attenuation radius. Since the RTM and PSF results are computed under the same observation system, the deconvolution can remove the influence of limited illumination angles in RTM results. Moreover, the seismic wavelets should match the one in RTM as they may have a great influence on point spread functions with respect to phase, amplitude, and attenuation radius.  
Figure 2 displays the inverted images using different point spread functions (red and blue circles in Figure 1). Even with the same wavelet, the images using the PSFs show significant variations in the space. The PSF at grid (26, 1) has wider illumination angles and better focusing than the one at grid (26, 11), and thus it can more accurately reflect the illumination characteristics of shallow structures in the model. As a consequence, the above PSF allows for better descriptions of the shallow structures but provides inaccuracy in the deep model. In contrast, due to limited illumination angle and wavefield propagation effect, the image obtained by the PSF at grid (26, 11) is much closer to an RTM result.  
Figure 1: The global point spread function in the 2D Marmousi model.
# Intelligent Network Service Optimization in the Context of 5G/NFV
## 4 Methodology of MAPE's Analysis Service
### Reinforcement Learning: State-Space Modelling and Rewards
Then, this reward component is defined as: \[m(b_{init},b_{after},f_{init},f_{after})=\frac{1}{2}(\frac{b_{after}-b_{init}}{ b_{init}}+\frac{f_{after}-f_{init}}{f_{init}}),b,f>0\] (2)
* Number of VNF Instances: This reward component depends on the number VNFs that are running per NS, also considering the ones that might occur after a scale-out or scale-in operation. A positive reward is produced in cases where the number of running VNFs is decreased, and a negative reward is produced if the number of running VNFs increases. Let \(n_{init},n_{after}\) be the number of VNFs before and after an action's execution. Then, this reward component is defined as: \[v(n_{init},n_{after})=n_{after}-n_{init},n>0\] (3)  
Two of the reward components are focused on the quality of the video transmission before and after the execution of an optimization action, while the third is focused on the cost of the action. The total reward is computed as  
\[reward=w_{1}\cdot r(MOS_{init},MOS_{after})+w_{2}\cdot m(b_{init },b_{after},f_{init},f_{after})+ \tag{4}\] \[w_{3}\cdot v(n_{init},n_{after}),w_{i}\in[0,1] \tag{5}\]  
The adjustment of the reward weights can lead to an effective joint optimization between QoE and cost by penalizing the VNF's scaling-out operations according to needs and resource availabilities.
## 2 The Experiment Facilities
### The Test Facility  
At the end of 2014, the high-pressure gas system was built in National Institute of Metrology of China (NIM), which consisted of 3 sections, including a pVTt primary standard device, sonic nozzle secondary standard device, and close loop working standard device. The maximum pressure in the system could be 2.5 MPa.  
For the sonic nozzle secondary standard device (SN device), there were 16 sonic nozzles used as the masters, as shown in Figure 3. The sonic nozzles were traceable to the pVTt primary standard device. The flowrate could be (20-400) m\({}^{3}\)/h with the best measurement capabilities 0.15% (\(k=2\)) [37].  
For the close loop working standard device (CL device), there were four turbine flowmeters used as the reference meters, as shown in Figure 4. The high-pressure gas was recirculated in the standard device, which was driven by the blower and the temperature was controlled by the heat exchanger. The reference meters were traceable to the sonic nozzle secondary standard device. The maximum flowrate could be 1300 m\({}^{3}\)/h with the best measurement capabilities 0.18% (\(k=2\)) [38].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number of Paths** & \begin{tabular}{c} **Gauss–Jacobi** \\ **Positions**\(x_{i}=d_{i}/R\) \\ \end{tabular} & \
\begin{tabular}{c} **Gauss–Jacobi** \\ **Weights (4 Path)**\(w_{i}\) \\ \end{tabular} &
\begin{tabular}{c} **Velocity Weights** \\ **(4/8 Path)**\(W_{i}\) \\ \end{tabular} \\ \hline A(1-A/2-A) & 0.8090 & 0.3693 & 0.1382/0.0691 \\ B(1-B/2-B) & 0.3090 & 0.5976 & 0.3618/0.1809 \\ C(1-C/2-C) & \(-0.3090\) & 0.5976 & 0.3618/0.1809 \\ D(1-D/2-D) & \(-0.8090\) & 0.3693 & 0.1382/0.0691 \\ \hline \hline \end{tabular} Here, \(d_{i}\) was the path height, which referred to the vertical distance of the path line from the pipe axis, and \(x_{i}\) was the corresponding path height ratio.  
\end{table}
Table 1: Path position and path weight.  
Figure 3: Schematic diagram of the sonic nozzle secondary standard device.  
It could be seen from Figure 7 that the differences between two devices under different installation conditions were decreased with the increasing of Reynolds number, but they were still much higher than the uncertainty of the best measurement capabilities 0.15% (\(k=2\)).  
The header was the only disturbing component in the experiments. Without the FC, the serious flow distortion would occur downstream from the header, resulting in additional measurement errors. With the FC, the measurement accuracy could be greatly improved.