esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Evaluation of Model Developments
### Evaluation of Updated Land Cover and Vegetation
#### 4.3.2 Evaluation of Dynamic Vegetation Seasonal Vegetation Cover Evaluation
Figure 14 is an illustrative example of this evaluation, where Figure 14a shows that the growth model reasonably simulates the LAI (black line) as compared to both the observed LAI (near real time Copernicus Global land LAI product GEOV1) and its corresponding 1999-2013 climatology (purple line). Although it slightly underestimates its maximum value for the considered Hungarian site (hu-mat), the correlation with the near real time LAI is slightly improved. In this case, for 2004 at the hu-mat site, the gross primary production (GPP) based on prognostic LAI correlates better (\(r=0.925\)) with smaller RMSE (\(RMSE=1.105\)) than when using the GEOV1 LAI (\(r=0.894,RMSE=1.260\)). The time series of the above-ground biomass (AgB) from 1999 to 2013 for the Hu-mat site is illustrated in Figure 14b. It shows that using the growth model (black line), the AgB correlates much better with the WOFOST products than when using the prescribed LAI climatology. These results are indicative of the overall impact of the growth model at the site level, although for other sites (not shown) the impacts may fluctuate. It should be noted here that this development is not implemented in coupled forecast mode and therefore still requires further testing to be included in the operational system. Figure 13: Above ground biomass-based Anomaly Index (\(AI_{AGB}\)) for November 2010 in % of the 1999–2013 mean.
# Clustering-Based Energy-Efficient Self-Healing Strategy for WSNs under Jamming Attacks
## 6 Simulation Results  
In this section, we present comparative results of FCPA against the baseline power control and cooperation strategies discussed in Section 4. We evaluate the performance of the self-healing protocols in a WSN under constant jamming attack in terms of energy consumption, the lifetime of the network, coverage, and PDR. To this end, we simulate the protocols in an outdoor and flat coverage area using MatLab R2021b software. Table 2 shows the system parameters used in the validation and evaluation phase. The simulation runs until the first node exhausts its battery, then the data referring to residual energy and collected information are processed.  
We consider a WSN with 64 nodes uniformly spread, as shown in Figure 4. In the absence of a jammer, it is logical to assume that the sink node is located at the center of the WSN region. Therefore, the most harmful location for a jammer would be that same position, thus annulling the operation of the sink node. That is why first we consider the jammer at the center, the so-called Position 1. Then, to evaluate the impact of the jammer location, always assuming the cancellation of the initial sink node, we consider another six relevant positions according to the symmetry of the proposed scenario. Consequently, the performance of the different strategies is evaluated for each scenario according to the seven potential jammer locations. In all cases, the jammer transmit power is considered fixed and equal to 14 dBm.  
In the results below, we show the clusters and network structures associated with each self-healing strategy in response to the jamming attack in each scenario according to the self-healing strategies. In addition, we provide data referring to the amount of information transmitted by the WSN and the residual energy of each node.
## 4 Results and Discussion
### Relationships between Plant Growth Indicators and NDVI  
Fertilization affects NDVI (as seen in Section 4.1) because plant growth strongly responds to fertilizer under nutrient limiting conditions. Figures 9 and 10 show the relationships between NDVI and GC fraction or plant height, respectively. At the plot scale, NDVI was moderately to strongly correlated to GC fraction and plant height for cotton, millet, sorghum and peanut. A strong linear relationship was expected for peanuts between NDVI and GC fraction because of its plant canopy structure. Peanut growth leads to a small plant height increase but a strong ground coverage increase that directly impacts NDVI by masking the background soil surface. For maize, plant height did not respond strongly to fertilization. The range in GC fraction was very small for maize fields on 26 August 2014. In general, GC fraction is fairly low, even at more advanced growing stages due to large distances between rows and relatively low nutrient application levels.
# Validated Questionnaire on Intraoral Scanner Effectiveness in Paediatric Patients
## 4 Discussion
The results of the present study illustrate that IOSs are useful tools to visualize the oral situation in pediatric dentistry and improve the understanding of diagnosis and treatment planning. This appears to be particularly important regarding the significance of parental understanding, especially in vulnerable patient groups and patients with language barriers. The use of an  
Figure 3: Example of intraoral scan with evidence of MIH. Figure 2: Intraoral scan shows sealants on 3.6.  
intraoral scanner and visual aids could improve the communication of treatment risks to people with limited language skills and medical knowledge [19]. The benefits of visual communication are already used in many ways in dentistry, and recorded images and models are effective tools for diagnosis, treatment planning and communication. In [PERSON] et al. 's 2024 study, a significantly higher understanding of children's oral situation was shown by the group of parents who were informed about their child's diagnosis and treatment planning with visual aids using IOS. This group showed better results in all questions than the group who received only verbal information without visual aids. The visualization tools seemed to be particularly useful, when information was provided in detail, such as which tooth was affected or which areas needed improvement regarding oral hygiene. Visualization support also significantly improved understanding regarding pending treatment. Additionally, the conditions that caused the planned treatment were better understood, which may result in better acceptance of the treatment. Individual patient IOSs are suited to present dental conditions with greater specificity and in a fully personalized manner. Numerous studies have shown that IOS have been found comparable to the clinical visual examination of the oral situation of school-age children [20]. However, intraoral scanners for documentation purposes only are not yet routinely performed in clinical, public health or research settings. It has also been shown in the past that children show a greater acceptance of medical care when using digital technologies [21]. Furthermore, patients whose dental treatment included intraoral scanning reported greater comfort and less chair time compared to conventional impression techniques [22]. Especially when dealing with younger or more anxious patients, a skeptical attitude towards treatment can lead to lower treatment acceptance due to a lack of understanding of the need for treatment [23]. Special conditions such as MIH require intensive, long-term treatment. If the affected teeth are visualized to the patient and their carers during previous examinations, this can lead to a better acceptance of the planned treatment and therefore better preservation of the teeth.
## 6 Gaussian Curvature  
The bending contribution to the elastic energy of a 2D body (Equation 1) involves a \"bending Poisson coefficient\" \(\
u^{\prime}\) that enters the equation in front of the Gaussian curvature \(\kappa_{11}\kappa_{22}-\kappa_{12}^{2}\). The coefficient \(\
u^{\prime}\) plays no role in nanotubes or in folded sheets, where the Gaussian curvature is zero. Alternatively, a Gaussian bending modulus \(D^{\prime}\equiv-(1-\
u^{\prime})D\) can be introduced. It is often used in membrane theory [46], but remains difficult to measure or to evaluate numerically [47]. It has been demonstrated theoretically [48] that the coefficient \(\
u^{\prime}\) of graphene differs from its in-plane Poisson coefficient \(\
u\). Using the parameters of second-generation Brenner potential, [PERSON] et al. [48] arrived at \(\
u^{\prime}=0.42\) and \(\
u=0.40\), still quite similar. With the same set of parameters, the flexural rigidity obtained is \(D=1.40\) eV, which according the the above definition yields \(D^{\prime}=-0.8\) eV [49]. By comparison, DFT calculations for carbon nanotubes and fullerene structures give \(D^{\prime}=-1.52\) eV and \(D=1.44\) eV (\(\
u^{\prime}=0.47\)) [7] or \(D^{\prime}=-0.7\) eV and \(D=1.6\) eV within the tight-binding formalism [46]. Recently, finite-temperature molecular dynamics has been performed for a graphene sheet containing a free edge in order to have access to the Gaussian bending modulus \(D^{\prime}\)[47]. The numerical data obtained could only be understood by attributing a small _positive_ value to this modulus, \(D^{\prime}\approx 0.03\) eV (\(\
u^{\prime}>1\)). This surprising result emphasizes the dominant role of entropic effects. At zero temperature, both integrands in Equation (1) must be positive definite expressions. This condition imposes \(A>0\), \(D>0\), and both \(\
u\) and \(\
u^{\prime}\) to be the interval \((-1,+1)\).
## Conventional GTR and GBR
### Membrane
#### 2.1.1 First-Generation Membranes  
The first-generation membranes aimed to achieve mechanical properties with a minimal toxic effect on adjacent tissue. At that time, the occlusive property was of the primary focus. In 1969,e-PTFE was developed and became a standard material in the 1990s. It has a double layer with pores between 5 and 20 microns. On one side is a 1-mm-thick open microstructure with 90% porosity, which retards the epithelial growth, and, on the other side, is a 0.15-mm-thick membrane with 30% porosity, which makes space for new bone [14]. The efficacy of e-PTFE was proven in many studies [14]. However, a higher exposure rate due to the high porosity and the additional surgery needed to remove it were its significant drawbacks. To overcome the limits of e-PTFE, high-density PTFE membrane (d-PTFE) with a smaller pore size (less than 0.3 microns) was developed in 1993 [15]. The feature of the adjusted transparency resulted in proper bone regeneration even in exposed cases, and no tissue integration into the membrane made it easy to be removed [14]. However, d-PTFE still had the limitation of collapse into the defect. Since e-PTFE and d-PTFE membranes showed low mechanical rigidity, titanium-reinforced e-PTFE and d-PTFE membranes were developed. The embedded titanium framework could be bent to fit on the alveolar defect. It was efficient for space maintenance in severe bony defects [14]. In several studies, Ti-reinforced e-PTFE showed a higher space maintaining ability and better stability than e-PTFE [16; 17]. In a case which recommends proper mechanical support such as vertical bone augmentation, titanium (Ti) mesh is recommended. Ti mesh has high rigidity, elasticity, stability, and plasticity, and its holes allow good blood supply directly from the periosteum to the surrounding tissues [15]. However, stiff Ti mesh tends to be exposed more often, and it is difficult to remove it due to the bone tack or other fixation devices [13].
## 3 Acoustic Localization
In the underwater environment, signal-to-noise ratio (SNR) is usually used to describe the quality of the received signals. High SNR of the received signals means more accurate TOAs, which leads to high localization accuracy. Therefore, due to the uncertainties in measured TOAs, the surface buoy positions \([x_{n},y_{n},z_{n}]^{\mathrm{T}}\), and the yaw angle measurement system, the \"measured\" AUV output \(\hat{\psi}(t)\) is assumed to be subject to random noises \(\epsilon\sim N(\mathbf{0},\Sigma)\) where \(\epsilon\) is an \(\mathcal{R}^{3\times 1}\) vector, and the covariance \(\Sigma=diag([\sigma_{x}^{2},\sigma_{y}^{2},\sigma_{\bar{\psi}}^{2}])\) with \(\sigma_{x},\sigma_{y}\), and \(\sigma_{\bar{\psi}}\) being the corresponding standard deviations.
# An Improved Channel Estimation Technique for IEEE 802.11p Standard in Vehicular Communications
## 2 System Model of the IEEE 802.11p
### Channel Model  
Recently, the V2V channel model characteristics have been explored in the literature [17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28]. Table 2 summarizes different characteristics of the seven realistic channel models [25; 28] of vehicular communication environments. A classical Tapped Delay Line (TDL) channel model, namely, wide stationary uncorrelated scattering (WSSUS), was proposed by [29]. Another closely related channel model is known as non-WSSUS, which is proposed by [25]. These models are accepted as standard channel model for the IEEE 802.11p based systems. These realistic channel models were obtained through a channel measurement campaign which was performed in the metropolitan Atlanta, Georgia, USA. The campaign consisted of six different scenarios. The V2V or (VTV) Expressway Oncoming, the VTV Urban Canyon Oncoming, Roadside To the Vehicle (RTV) Suburban street, the RTV Expressway, the VTV Expressway Same Direction With Wall (SDWW), and the RTV Urban Canyon.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Values** \\ \hline FFT size & 64 \\ FFT period & 6.4 μs \\ Symbol duration & 8.0 μs \\ GI duration & 1.6 μs \\ Total subcarriers & 52 \\ Pilot subcarriers & 4 \\ Data subcarriers & 48 \\ Code Rate & 1/2, 2/3, 3/ 4 \\ Modulation Schemes & BPSK, QPSK, 16 QAM, 64 QAM \\ Bit Rate & 3, 4.5, 6, 9, 12, 18, 24, 27 \\ Frequency spacing of subcarriers & 156.25 KHz \\ Error correction coding & k = 7 (64 states) convolution code \\ Bandwidth & 10 MHz \\ \hline \hline \end{tabular}
\end{table}
Table 1: IEEE 802.11p standard parameters.  
Figure 2: Transmitter block diagram of IEEE 802.11p.  
Further experiments were done by the European Telecommunications Standards Institute (ETSI) and a comprehensive vehicular channel model was formulated [28]. This channel model is known as HIgh PERformance radio Local Area Network (HIPERLAN)/2 and it is also available in Matlab 2016 version. This model has a delay profile called Model-E, that represents Non-Line-Of-Sight (NLOS) conditions with an average delay spread of 250 ns. In CDP scheme, the time-variant characteristics of channel models [25] have been employed, however its impact on the overall OFDM performance due to intercarrier interference under HIPERLAN/2 SISO fading channel model [28] still needs further investigations. We have investigated this severe channel model for the proposed channel estimation. We have also tested the proposed scheme for the VTV Express oncoming channel model as shown in Table 2. The time and frequency variations have been analyzed in the paper. We will use a short-term HIPERLAN-E for the HIPERLAN/2 Model-E channel model in this article.
## 2 Background on Internet of Things (IoT) and Sensors
### Advantages and Disadvantages of IoT for Emergency Response  
We can summarize the advantages of IoT for emergency response, as follows:  
* Real-time monitoring [42, 43]: IoT sensors can provide real-time data on environmental conditions, infrastructure status, and people movement during an emergency. This information can help emergency responders make better decisions and respond more quickly to the emergency.
* Early detection [29, 44, 45]: IoT sensors can detect emergencies, such as natural disasters or infrastructure failures, before they become critical. This early detection can help to prevent emergencies from becoming more severe and dangerous.
* Improved communication [16, 46, 47, 48]: IoT technology can improve communication among emergency responders and with the public. This can help to coordinate a more effective response and keep people informed and safe during an emergency.
* Automated response [49, 50, 51]: IoT technology can automate certain emergency response processes, such as sending alerts or deploying emergency resources. This automation can save valuable time and reduce the potential for human error.  
The disadvantages of IoT for an emergency response include:  
* Reliability: IoT sensors may not always be reliable, especially in extreme weather conditions or other emergency situations. This can lead to false alarms or delays in response.
* Technical expertise: IoT technology requires specialized technical expertise to install and maintain. This can limit its adoption in some areas or by some organizations that do not have the necessary expertise.  
The advantages of IoT technology for an emergency response outweigh the disadvantages. However, it is important to carefully consider the potential drawbacks and address them appropriately to ensure that IoT technology is used effectively and safely in the emergency response.
## 4 Conclusions  
In this communication, the resonant properties of graphene sheets with different types of vacancies was investigated by molecular dynamics simulation. The effect of defect type, external stress, and system temperature on the resonance properties of graphene have been discussed. The resonance frequencies of both types of graphene increased with external stress loading. It shows a clear step-shaped variation. This is mainly due to the occurrence of nonlinear deformations of graphene in the vibration process. When the external force is less than 15.91 nN, the resonance frequencies of two types of graphene showed a consistent trend. The maximum frequency was up to 132.9 GHz. When the external force was less than 90 nN, the resonance frequencies of graphene with a single vacancy defect were greater than the resonance frequencies of graphene with edge defects. When the external force was less than 90 nN, the resonance frequencies of graphene with edge defects were greater and changed more rapidly. Temperature had little influence on the resonance frequency of the graphene nanosheet. The resonance frequency was 99.7 GHz between 0.1 K and 50 K. When the temperature was 75 K, the resonance frequency jumped to 132.9 GHz. When the temperature was greater than 75 K, the resonance frequency remained constant. Due to the ultralow density, ultrahigh resonance frequency, high strength and stiffness, high sensitivity to the environment, and other  
Figure 10: Absolute displacement in the normal direction at different system temperatures: (**a**) Single vacancy defect; (**b**) Edge defects.  
Figure 9: Resonance frequency as a function of temperature with two different vacancy defects.  
characteristics, graphene can be considered as an ideal material for ultra-sensitive biosensors which can achieve accurate and highly-selective detection of biomolecules.  
The work is supported by Research Program supported by National Science Foundation of China (61176130) and National Science Foundation of Ningbo (2016A610030).  
[PERSON] conceived and designed the experiments; [PERSON], [PERSON] and [PERSON] performed the experiments and analyzed the data; [PERSON] wrote the paper.  
The authors declare no conflict of interest.
# An Attempt to Establish a Mathematical Model for an Unconventional Worm Gear with Bearings
## 1 Introduction
Double-enveloping worm drives, as previously mentioned, have applications in various domains considering their advantages (as compared to the other worm gear types) such as higher efficiency (because of more favorable functioning conditions [10]), smoothness, and silence in operation, high load capacity due to a higher contact ratio, etc. However, this type of worm gear is sensitive to tolerance, needs accurate alignment, and is characterized by high wear and a tendency to seize [1]. Another significant aspect is the backlash, which has a major impact on smooth operation and over-transmission errors. To overcome these disadvantages of the globoid worm gear drive, a new roller enveloping toroidal worm gear was proposed. This design solution consists of a worm wheel in which the teeth are replaced with deep groove ball bearings. Using rolling elements turns the sliding friction into rolling friction during the process of worm gear meshing, which eliminates the backlash [18] (when they are used custom-designed bearings) and conducts higher gear efficiency. In [18], [PERSON] et al. investigated a new single-roller enveloping hourglass worm gear. They proposed a design to eliminate the backlash in mating gear transmission. A parametric study was conducted to analyze the influence of some design variables, i.e., the center distance, roller radius, transmission ratio, and radius of the base circle over the gear set characteristics. An analysis of the dynamic behavior of these gears was carried out in [19; 20; 21]. The 3D-generated CAD model was then compared with the calculated one. A very good match was found. Another interesting study about these new gearings is described in [9]. It presented a methodology for thermal power calculation. What we pursue as a priority in this paper is to obtain a general mathematical model of the non-conventional worm gear with bearings that is clear, coherent, demonstrable, and easy to apply for particular situations, an essential aspect for the realization of both 3D and physical models. The objective of the paper is to reduce the friction force in the worm-roller gear using the rolling force of the bearing (tooth) on the surface of a helical worm. In this paper, a mathematical model of a double-deep groove ball-bearing enveloping worm gear drive is presented. A total of 36 bearings were used (each new worm wheel tooth was composed of two bearings), replacing the worm wheel teeth. Here, a mathematical model is first formulated, followed by graphical validation of the globoid helix. The Wolfram 14.1, online version [22] program was utilized to generate globoid helices.
## Materials and Methods
### Analysis of Volatile Compounds  
Analysis of volatile compounds was conducted using headspace solid phase microextraction (HS-SPME). Approximately 0.25 g of crushed dried and fresh leaf samples were placed in vials with the internal standard; \(p\)-methoxyphenol (2 \(\upmu\)g). Vials were covered with PTFE/silicon septum and placed in a water bath at 60 \({}^{\circ}\)C for equilibration (10 min). SPME fiber (Supelco, Bellefonte, PA, USA) with a vivinylbenzene/carboux/polydimethylsiloxane (DVB/CAR/PDMS, 50/30 \(\upmu\)m, coating 2 cm) (Supelco) was used. Prior to extraction, SPME fiber was conditioned by inserting into a GC injection port for 1 h at 220 \({}^{\circ}\)C. For each extraction, SPME fiber was inserted into a vial that contained a sample kept in a water bath at 60 \({}^{\circ}\)C for 30 min. Next, the fiber was drawn into a needle and injected into the injection port of a GC-MS at an injection temperature of 220 \({}^{\circ}\)C for 3 min. The GC-MS analysis was performed on a Varian CP-3800/Saturn 2000 (Varian, Wallnut Creek, CA, USA) equipped with a capillary column, ZB-5 MS (30 m \(\times\) 0.25 mm i.d \(\times\) 0.25 \(\upmu\)m film thickness) (Phenomenex, Shim-Pol, Poland).  
Our gradient temperature program was as follows. The initial oven temperature was 50 \({}^{\circ}\)C, which was increased to 130 \({}^{\circ}\)C at a rate of 4 \({}^{\circ}\)C min\({}^{-1}\). Then, the temperature was raised to 180 \({}^{\circ}\)C at 10 \({}^{\circ}\)C min\({}^{-1}\) and finally raised up to 280 \({}^{\circ}\)C at a rate of 2 \({}^{\circ}\)C min\({}^{-1}\). Samples were injected in split mode (1:10), and helium gas was used as the carrier gas at a flow rate of 1.0 mL min\({}^{-1}\). Mass spectra were obtained in EI ionisation mode at 70 eV within a scan range of 35-550 m/z. After each extraction, SPME fiber was prepared for the subsequent extractions by placing in the injection port of GC-MS for 15 min at 220 \({}^{\circ}\)C, to ensure complete elution of volatiles. Identification of all volatile constituents was based on a comparison of experimentally obtained compound mass spectra with mass spectraavailable in NIST14 database. Furthermore, the experimentally obtained retention index (RI) by [PERSON] was compared with RI available in the NIST WebBook and literature data [42].