esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Cooperative Communication Algorithms
### OPNET Simulation  
KCN was compared with three other routing algorithms (Beacon-less routing (BLR) [17], REER [18], GPSR [10]). The networks range was set to 1000 m \(\times\) 500 m, and 600 nodes are deployed randomly. The transmission radius was set to 75 m.  
A. Effects of \(f\) and \(k\) on \(W\)  
\(K\) is numbered from 1 to 10, and \(f\) varies from 0.15 to 0.75. The simulation results are shown in Figure 7; the simulation results of Figure (a)a and MATLAB are the same as those of Figure (a)a. In Figure (a)a, the higher the link failure rate, the larger the number of node retransmissions and the greater the end-to-end delay.  
Figure 7: Effect of \(f\) and k on end-to-end reliability.  
B. The Effect of \(f\) and \(\mu\) on Reliability  
The link failure rate is fixed at 0.3. As shown in Figure 8, \(K\) varies from 1 to 10, \(\mu\) from 0.1 to 0.9, and step size is 0.2. The simulation results of Figures 3, 4, 5, 6, 7 and 8a and Matlab are similar to those of Figure 3b. The greater \(\mu\) is, the greater possibility of node dormancy is, and the lower reliability \(W\) is. When \(\mu\) decreases to a certain extent (\(>=0.7\)), the reliability is so low that the packet cannot reach the Sink node. Thus, the delay cannot be counted, and the phenomenon of delay reduction occurs.  
C. Performance comparison of four routing schemes  
The reliability and energy consumption of KCN are compared with three other routing algorithms: REER, BLR and GPSR. The results are shown in Figure 9a. With the increase of link failure rate \(f\), the reliability of GPSR decreases rapidly due to the lack of packet loss processing mechanism. BLR periodically re-select relay nodes. Two forwarding mechanisms were used, namely, relay node forwarding and normal forwarding. Broadcasting was used in relay node selection to achieve high reliability. However, once the relay node is selected, it enters the normal forwarding. Under the normal forwarding condition, the relay node cannot process the forwarding according to the channel condition. Thus, its reliability also decreased as quickly as GPSR. In simulation, the same three-step handshake protocol (DATA, REP, SEL) was used for BLR and REER.  
The energy consumption per packet of the four algorithms is shown in Figure 9b. When the link failure rate is greater than 0.06, the energy consumption per packet of GPSR and BLR is decreased to 0. Thus, the energy consumption is no longer counted. BLR can cancel out some link failures when broadcasting, and its energy consumption per packet is low. In KCN and REER, non-cooperative nodes enter dormancy in the data transmission phase. Thus, their average energy consumption per  
Figure 8: The effect of f and \(\mu\) on W.  
Figure 9: Comparisons of Four Routing Algorithms.  
packet is low. With the increase of link failure rate, the reliability of REER is 0. KCN can maintain high reliability because of fixed \(K\)-node forwarding nodes. Meanwhile, the hop count is higher than that of REER, and it results in a slightly higher energy consumption per package than that of REER.
## 3 Results and Discussion
### Antimicrobial Activity of the CFS
plantarum_ CNTA 600, and _B. subtilis_ CNTA 517. In addition to its sensitivity to the CFSs of the strains tested, it is a micro-organism capable of growing in refrigeration and whose presence has accounted for 15% of foodborne illnesses according to the annual report of the RASFF of the year 2023 [4]. The antimicrobial activity of the CFSs from _P. acidilactici_ and _B. subtilis_ species against the selected spoilage micro-organisms could be classified as negative or null, as they did not produce any halos in the agar well diffusion assay. On the contrary, the CFS of _L. plantarum_ CNTA 600 exhibited a medium activity against _P. fluorescens_ (10.78 \(\pm\) 0.05 mm) which aligned with the activity described by [PERSON] et al. [58]. It also demonstrated strong activity against _K. marxianus_ (14.14 \(\pm\) 0.12 mm), for which the antimicrobial activity of different antimicrobials has not been described in the literature yet [59]. Notably, the CFS displaying the highest antimicrobial activity was the one from _L. brevis_ CNTA 1374, producing halos of 32.20 \(\pm\) 0.04 mm against the spoilage LAB _L. parabuchneri_, not previously described. Considering these results and its ability to produce histamine in cheese [60], _L. parabuchneri_ CNTA 1075 was selected as the spoilage indicator micro-organism to be tested against the CFS of _L. brevis_ CNTA 1374 in the following tests. The MIC of the CFS of the different species was determined by the time-kill curve and was seen to be specific for each strain but within a similar range (Figure S2). The MICs of _P. acidilactici_ CNTA 1059, _L. plantarum_ CNTA 600, and _B. subtilis_ CNTA 517 against _L. monocytogenes_ were 2.5%, 5.0%, and 1.25%, respectively. In the case of _L. brevis_ CNTA 1374, a lower MIC of 0.15% was determined against _L. parabuchneri_. These results align perfectly with those obtained with the agar diffusion assay, which showed _L. brevis_ CNTA 1374 to attain the greatest inhibition halo, while _L. plantarum_ CNTA 600 showed the weakest activity out of all the selected strains.
## 2 Theoretical Background
### Literature Review
This approach is expected to provide sufficiently reliable results in the architectural planning stage depending on dataset improvement, increasing the number of data, and reflection of key parameters. The characteristics of the prediction models of the previous analyzed studies are summarized in Table 2. They showed limitations in the small number of data and small number of validation samples in constructing prediction models. Therefore, to overcome the limitations of previous studies, we developed an early-stage construction cost prediction model suitable for the actual situation of the estimation projects, using a dataset with more than 900 data. Moreover, the constructed prediction model is verified by applying the BIM process to it.
## 4 Materials and Methods
### Experimental Setup and Imaging  
#### 4.1.1 Cowpea Grown in the Glasshouse  
_Vigna unquiculata_ (cowpea) plants were grown at the Plant Growth Facility ([[https://www.cranfield.ac.uk/facilities/plant-growth-facility](https://www.cranfield.ac.uk/facilities/plant-growth-facility)]([https://www.cranfield.ac.uk/facilities/plant-growth-facility](https://www.cranfield.ac.uk/facilities/plant-growth-facility)), accessed on 10 March 2023) located at Cranfield University (Cranfield, UK). The plants were grown in pots filled with compost that was washed and depleted of macro- and micronutrients. The compost was then reconstituted with prepared nutrient solutions of defined composition. The compost-washing method followed the method by [PERSON] et al. [30], with some modifications. This was achieved by flooding one-part compost to five-parts deionized water, mixing and breaking aggregates. The soluble solution was drained through a double-headed 0.5 um sieve. The steps were repeated five times, and the depleted-nutrient compost was dried in an oven at 70 \({}^{\circ}\)C for 72 h. After drying, the compost was mixed with a nutrient solution prepared according to the treatment required. Four nutrient solutions were prepared based on Letcombe nutrient solution [30], with a high level of nitrogen and high level of phosphorus (HNHP), high level of nitrogen and low level of phosphorus (HNLP), low level of nitrogen and high level of phosphorus (LNLP). The concentrations were 49.1 mM and 14.6 mM N for HN and LN, and 13.4 mM and 3.3 mM P for HP and LP, respectively. Each treatment was replicated five times. The different treatments induced changes in leaves' pigmentation, resulting in variations in the spectral characteristics (color) during plant development. During their development stages, plants with adequate nitrogen levels exhibited green leaves, whilst deficiency was characterized by chlorosis progressing from light green to yellow to brown, and phosphorus deficiency inhibited shoot growth and decolorized leaves from a blue-green color to pale green/yellow in severely affected regions [29]. Digital images were taken twice weekly, using a high-resolution (3296 \(\times\) 2472 pixels) RGB camera (color 12-bit Prosilica GT3300) installed on the Lemmatec phenotyping platform in the glasshouse. The camera was set 3.5 m above the top plant canopy, covering an area of 0.48 m\({}^{2}\) during imaging. Imaging commenced at the vegetative growth stage, 28 DAS (days after sowing), when the first trifoliate leaf had unfolded at node 3 and ended at the physiological maturity stage (90 DAS), when the seed pods were matured and ready for harvesting. The format of all the images used in this study was JPEG.
###### Abstract  
The current global roll-out of 5G infrastructure is designed to utilise millimetre wave frequencies (30-300 GHz range) at data transmission rates in the order of gigabits per second (Gbps). This frequency band will be transmitted using beamforming, a new introduction in near-field exposures. The International Commission on Non-Ionising Radiation Protection (ICNIRP) has recently updated their guidelines. We briefly examine whether the new approach of the ICNIRP is satisfactory to prevent heat damage and other adverse bio-effects once millimetre wave 5G is included, and we challenge the use of surface-only exposure assessment for local exposures greater than 6 GHz in part due to possible Brillouin precursor pulse formation. However, this is relevant whether or not Brillouin precursors occur from absorption of either 5G or future G transmissions. Many significant sources conclude there is insufficient research to assure safety even from the heat perspective. To date, there has been no published in vivo, in vitro or epidemiological research using exposures to 5G New Radio beam-formed signals.  
electromagnetic radiation; safety hazards; exposure evaluation; public health; beamforming 2020  
[PERSON], [PERSON], [PERSON]  
ICNIRP Guidelines' Exposure Assessment Method for 5G  
Millimetre Wave Radiation May Trigger Adverse Effects. Int. J. Environ. Res. Public Health2023205267. [[https://doi.org/10.3300/jepph20075267](https://doi.org/10.3300/jepph20075267)]([https://doi.org/10.3300/jepph20075267](https://doi.org/10.3300/jepph20075267))  
1  
Footnote 1: email: {[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON]  
in the range of 26 GHz, 28 GHz and 40 GHz, with a view to incorporating 66-71 GHz \"to encourage timely equipment support\" [3].  
The mmW band will be transmitted using beamforming--the first time this approach has been intentionally incorporated into telecommunication devices for public use, which will include near-field exposures from hand-held devices. Indeed, until 5G development, near-field exposures from this source were not investigated or considered in research or standards [4]. The 5G beam-forming component will be targeted to specific devices in narrow, high-power beams compared to 3G or 4G, which are transmitted routinely in all directions available to each antenna. Opinion is mixed about whether this will increase or decrease overall environmental exposures. However, during use, the energy in 5G beams will be relatively high for those in their path and those handling receiving/sending devices; the beamed energy will interact with people, trees and animals in its path. The latter includes pollinating insects for whom increased absorption between 3 and 370% can be expected if only 10% of incident power shifts to frequencies greater than 6 GHz [5].  
This paper explores the assumption by ICNIRP that it is not necessary to assess 5G exposures > 6 GHz using specific absorption (SA\({}_{\text{ab}}\)).
# Reconstruction of Preclinical PET Images via Chebyshev Polynomial Approximation of the Sinogram
## 2 Mathematical Formulation
### Numerical Implementation of the Inversion of the Radon Transform via Chebyshev Polynomials  
For the evaluation of all quantities involved in the inversion Equation (4), we assume that \(\widehat{f}(\rho,\theta)\) is given for \(K\) projection angles, \(\theta\), and for \(\Lambda\) detector locations, \(\rho\), namely:  
\[\theta=\theta_{k},\quad\theta_{k}\in[0,2\pi],\quad\forall\;k\leqslant K,\quad \text{and}\quad\rho=\rho_{\lambda},\quad\rho_{\lambda}\in[-1,1]\quad\forall\; \lambda\leqslant\Lambda. \tag{13}\]  
The values of \(\rho_{\lambda}\) represent the roots of the Chebyshev polynomial \(T_{n}(\rho)\), hence they belong to the zero set of \(T_{n}(\rho)\), denoted by \(\ker\left(T_{n}\right)\),  
\[\rho_{\lambda}\in\ker\left(T_{n}\right):=\Big{\{}\rho\in[-1,1]\;\Big{|}\;T_{n} (\rho)=0\Big{\}}. \tag{14}\]  
Equation (7) implies that \(\rho_{\lambda}\) must be located in  
\[\rho_{\lambda}=\cos\left[\left(\frac{2\lambda-1}{n}\right)\frac{\pi}{2}\right],\quad\lambda\leqslant\Lambda,\quad n\in\mathbb{N}. \tag{15}\]Taking into account the above assumptions, we present the computational steps of our proposed, Chebyshev-based reconstruction algorithm in Algorithm 1.  
```
Reconstruction algorithm: Chebyshev approximation of the sinogram Input:\(\widehat{f}(\rho,\theta)\) given at \(\rho_{\lambda}\), \(\forall\lambda\leqslant\Lambda\) and \(\theta_{k}\), \(\forall\;k\leqslant K\) Compute:\(t_{r}=\dfrac{1}{(1-\rho^{2})}\) for all \(x_{1}\), \(x_{2}\) and \(\theta_{k}\), via Equation (2), \(t_{\ell}=\ln\left(\dfrac{1-\rho}{1+\rho}\right)\) for all \(x_{1}\), \(x_{2}\) and \(\theta_{k}\), via Equation (2), \(T_{n}(\rho)\) for all \(n\), via Equation (7), \(T_{n}^{\prime}(\rho)\) for all \(n\), via Equation (12), \(c_{n}(\theta)\) for all \(n\), via Equation (6) as in [28], \(t_{1}=-t_{r}c_{0}(\theta)\) for all \(\rho\) and \(\theta_{k}\), \(t_{2}=-2t_{r}\sum\limits_{n=1}^{N}c_{n}(\theta)T_{n}(\rho)\) for all \(\rho\) and \(\theta_{k}\), \(t_{3}=t_{r}\sum\limits_{n=1}^{N}c_{n}(\theta)T_{n}^{\prime}(\rho)\) for all \(\rho\) and \(\theta_{k}\), \(t_{4}=4\sum\limits_{n=1}^{N}c_{n}(\theta)\sum\limits_{k=1}^{\left\lfloor\frac {n+1}{2}\right\rfloor}\dfrac{T_{n-2k+1}^{\prime}(\rho)}{2k-1}\) for all \(x_{1}\), \(x_{2}\) and \(\theta_{k}\), \(\dfrac{\partial H(\rho,\theta)}{\partial\rho}=\sum\limits_{i=1}^{4}t_{i}\), \(-\dfrac{1}{4\pi^{2}}\int\limits_{0}^{2\pi}\dfrac{\partial H(\rho,\theta)}{ \partial\rho}\mathrm{d}\theta\), via numerical integration Output:\(f(x_{1},x_{2})\)
```  
**Algorithm 1**Computational steps of the proposed Chebyshev-based reconstruction algorithm
# The Influence of Interlock Loss between Rebar and Concrete on Bond Performance of RC Member
## 5 Analytical Case Study Assuming Lug Loss Due to Rebar Corrosion
### Investigation on the Effect of Lug Height Loss  
Figure 13 shows the load-deflection curves and strain distribution for the analysis cases focusing on the effect of lug height loss. In the case of the LugH-75% and LugH-50%, load-deflection curve, maximum load, main rebar strain distribution, and crack distribution were nearly same as those of the sound case, while stiffness reduced slightly with lug height decreasing. Until lug height reduction reached to 50%, lug height had almost no influence on the structural behavior of the member. In the LugH-25%, stiffness after flexural cracking was low, the crack concentrated in the center of the span, and the beam failed in crushing at the compression side, not by shear crack opening. This is due to bond loss and the fact that the small lug height of 0.5 mm resulted in reduced stress transfer between the lugs and the concrete. The strain distribution of LugH-25% indicates that the concrete surrounding rebars were damaged locally, which was not seen in the other cases.  
For a more detailed study on the lug height effect on the bond, the authors conducted a rebar pull-out test which used threaded rebars with different lug heights. This followed the pull-out test sequence described in Section 4 and all lugs of embedded rebar were grinded manually before concrete casting. The same three cases with reduced lug height as in the analytical cases were set at 75%, 50%, and 25% of original height. Figure 14 shows the test results of the cases with sound rebar, grinded rebar, and PC rod. It is noted that Figure 15 shows one of the test results with two specimens for each case and they had small scatter, as shown in Figure 11. Pull-out behavior showed the same trend as member analysis, where the cases with lug height reduced to 75% and 50% showed almost the same pull-out stiffness compared with the sound case, but the rebar with 25% lug height had low pull-out stiffness. Bond strengths became smaller in correlation with lug height reduction because the contact area between lug and concrete became smaller. However, in the beam analysis, these difference in bond strength did not affect the structural behavior because the external force to cause local bond fracture on rebars was larger than that to cause the whole beam failure.  
Based on these results, stress transfer in a member can be maintained up to a certain lug height loss while bearing pressure increases as the contact area between concrete and rebar is reduced by lug height reduction. When lug loss ratio exceeds a certain level, the concrete at the interlocking surface breaks down locally. If lug height is uniformly decreased, local bond fracture propagates one after another, and unity between rebar and concrete is lost entirely.  
Figure 13: Analysis results (effect of lug height loss).
# A Review of Image Reconstruction Algorithms for Diffuse Optical Tomography
## 3 Forward Process
### \(P_{n}\) Approximation
It was demonstrated that the highly absorbing and scattering regions in the low-scattering medium were imaged more accurately in the reconstructed image using the higher-order \(P_{N}\) approximation.
# High-Frequency Limits of Graphene Field-Effect Transistors with Velocity Saturation
## 4 Simple Model of GFETs
### Substrate Phonon Scattering Model
This illustrates the difference between momentum relaxation (the resistance) and energy relaxation (the temperature or electronic distribution) mechanisms (Another example of such a difference, is acoustic phonon scattering which gives rise to a linear temperature dependence for resistivity but a cubic one for relaxation, reflecting single phonon and inelastic supercollision scattering respectively [27]). In the full saturation regime all terms are negligible compared to the HPhP term and one obtains the saturation current:  
\[I_{sat} = \frac{4e^{2}}{\hbar}\frac{k_{F}W}{\pi}\frac{\hbar\Omega_{I}}{e} \tag{2}\]Physically, the current saturation is due to the carrier velocity saturation \(v_{sat}\):  
\[v_{sat}=\frac{I_{sat}}{neW}\approx\frac{2}{\pi}\frac{\hbar\Omega_{I}}{E_{F}} \times v_{F} \tag{3}\]  
Equations (1)-(3) strictly hold at large doping when \(E_{F}\gtrsim\hbar\Omega_{I}\); the crossover to Fermi energy limited current at low doping can be taken into account by substituting \((E_{F}^{-2}+\hbar\Omega_{I}^{-2})^{-1/2}\) for \(\hbar\Omega_{I}\)[11] (The \(2/\pi\) pre-factor, which stems from the angular projection of electron momentum along the current axis, is sometimes omitted in the literature [8]). In Ref. [11] the saturation current was deduced by fitting the differential conductance by the law \(R^{-1}(V_{ds})=R^{-1}(0)V_{ds}/\left[1+(V_{ds}^{0}/R(0)I_{sat})\right]^{2}\), which can be deduced from Equation (1). The saturation is not complete in our samples due to limited mobility and we cannot extract \(I_{sat}\) and \(v_{sat}\) directly. In Figure 3b, we show the calculated drift velocity \(v_{d}\) as a function of \(\mathcal{E}\) (solid lines) for different densities from the current saturation model with \(\hbar\Omega_{I}=0.1\) eV. Further, we show the measured \(v_{d}\) at large density (\(n=5\times 10^{12}\)cm\({}^{-2}\)), where channel density is mostly homogeneous. The very good agreement between theory and experiment, in a regime where HPhP scattering dominates, confirms the relevance of our model. As a conclusion of this section, we note that the effect of high mobility is mainly to decrease the threshold voltage of saturation and thus to clarify the transition toward the current saturation regime. This is why full current saturation is only observed in high-mobility samples.
## 2 Materials and Methods
### Characterization  
The S-4800 scanning electron microscope (SEM, Hitachi, Japan) was used to examine the morphology of the materials. The X-ray diffraction (XRD, Bruker AXS, Karlsruhe, Germany) was used for the structural characterization, and Raman spectra were performed using a Raman spectrometer (Renishaw, NewMills, UK). The Kubo \(\times\)1000 automatic surface area and pore analyzer (Beijing Builder Co., Ltd., Beijing, China) were used to measure the N\({}_{2}\) adsorption-desorption isotherms at a temperature of \(-\)196 \({}^{\circ}\)C, with \(10^{-5}<P/P_{0}<1.0\). The samples were treated under vacuum at 80 \({}^{\circ}\)C for 2 h. The BET-specific surface area (\(S_{\text{BET}}\)) was calculated by the Brunauer-Emmett-Teller (BET) equation. The total pore volume (\(V_{\text{tot}}\)) and the average pore size (\(D_{\text{aver}}\)) were calculated using the Barrett-Joyner-Halenda (BJH) method. The presence of functional groups on the samples were measured by the Fourier-transform infrared spectroscopy (FTIR, BrukerTensor 27, Ettlingen, Germany) in the range of 400-4000 cm\({}^{-1}\). The water contact angle was measured for a 3 \(\mu\)L water drop at room temperature using a contact angle/interface system (JY-PHb, Jinhe Instrument Manufacturing Co., LTD, Nanjing, Jiangsu, China) to determine the hydrophobicity of the samples. The L2 concentration was determined using GC 9790 gas chromatography (Fuli Analytical Instrument Co., Ltd., Wenling, Zhejiang, China) with a hydrogen flame ionization detector (GC/FID) and a 2.0 m long \(\times\) 2.0 mm I.D. stationary-phase column (GDX-102). Other detection conditions are as follows: an oven temperature of 200 \({}^{\circ}\)C, an injector temperature of 250 \({}^{\circ}\)C, and a detector temperature of 280 \({}^{\circ}\)C, with an N\({}_{2}\) carrier gas flow rate of 50 mL min\({}^{-1}\).
###### Abstract  
The sedimentary clays of the Douala sub-basin (Cameroon) were studied to determine their mineralogical composition and physicochemical properties to boost their potential suitability as materials for traditional ceramics and eventually modern ceramics. These clayy materials are not widely used locally as building materials and little data are available on these materials in the field of ceramics and they are relatively unknown. Three profiles from 3.9 to 7.4 m thickness were studied on the field in order to determine their mineralogical (X-ray diffraction, infrared), chemical (X-ray fluorescence) and physicochemical (particle size, Arterberg limits, organic matter, cation exchange capacity and hydrogen potential) properties. Globally, ten (10) clay samples were analyzed to highlight the nature and technological properties of these clays. Mineralogically, kaolinite (48.3-69.2 wt.%) and quartz (20.5-41.2 wt.%) were the most abundant minerals in these raw clay materials. They were associated with a very small or moderate quantity of little, hematite, geothetic, feldspar, gibbsite and mica. Geochemically, the clayy materials had high silica (SiO\({}_{2}\), 22.21-58.03%) and alumina (Al\({}_{2}\)O\({}_{3}\), 12.84-22.94%) contents, with a significant amount of iron oxides (Fe\({}_{2}\)O\({}_{3}\), 1.07-17.92%). Other oxides (K\({}_{2}\)O, MgO, TiO\({}_{2}\), Na\({}_{2}\)O, MnO, CaO and P\({}_{2}\)O\({}_{3}\)) were in a relatively lower proportion. A high level of alumina content explains the kaolinite nature of these clayy materials. The results of the granulometric analysis of the clayey materials showed the following distribution: clay (26-99%) followed by silt (1-70%) and sand (0-4%). This corresponds to silty clay soils according to the Belgian textural classification diagram, with high plastic index (63.9%) characteristics. The studied clay materials are good candidates for the production of ceramics and terracotta building. This study is therefore important for any application of this type of clay in various industrial fields.  
Cameroon; clay material; Douala sub-basin; mineralogical; physicochemical +
Footnote †: journal: Applied Sciences