esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
MnO\({}_{2}\)-doped 9 mol\(\%\) CaO-stabilized zirconia (CSZ) was investigated in terms of phase stability, microstructure, and mechanical properties before and after thermal cycling. As the MnO\({}_{2}\) content increased from 2 to 4 mol\(\%\), the monoclinic phase fraction decreased significantly (from 32.6\(\%\) to 2.5\(\%\)), while the tetragonal phase fraction increased (from 58.2\(\%\) to 90.3\(\%\)), indicating an enhanced phase stability comparable to fully stabilized ZrO\({}_{2}\). The cubic phase fraction decreased from 9.2\(\%\) to 3.4\(\%\) with 2-3 mol\(\%\) MnO\({}_{2}\), but increased to 7.2\(\%\) at 4 mol\(\%\). The 9 mol\(\%\) CSZ showed a mixture of grains around 2 \(\upmu\)m and 10 \(\upmu\)m, while the MnO\({}_{2}\)-doped CSZ exhibited only grains larger than 30 \(\upmu\)m, suggesting that MnO\({}_{2}\) acted as a sintering aid. After thermal cycling, increasing the MnO\({}_{2}\) content from 2 to 4 mol\(\%\) led to an increase in the monoclinic phase fraction (from 7.8\(\%\) to 17.2\(\%\)) and a decrease in the tetragonal phase fraction (from 53.6\(\%\) to 21.8\(\%\)). The Vickers hardness and wear resistance of MnO\({}_{2}\)-doped CSZ were superior to those of undoped 9-CSZ, and improved as the MnO\({}_{2}\) doping level increased. These mechanical properties were maximized in the CSZ doped with 3 mol\(\%\) MnO\({}_{2}\), and this trend persisted after thermal cycling. These results demonstrate that MnO\({}_{2}\) doping effectively enhances the phase stability and mechanical performance of CaO-partially stabilized zirconia under thermal stress cycling conditions.  
calcium partially stabilized zirconia; phase stabilization; phase volume fraction; thermal expansion; mechanical properties +
Footnote †: journal: Applied Sciences
# Reliability by Using Weibull Distribution Based on Vibration Fatigue Damage
###### Abstract  
In this paper, a Weibull probabilistic methodology is proposed with an approach to model vibration fatigue damage accumulation using two parameters: Weibull distribution and a nonlinear fatigue damage accumulation model. The damage is cumulated based on the application of a vibration stress profile and is used to determine both the Weibull \(\beta\) and \(\eta\) parameters, and the corresponding component reliability R(t). The vibration fatigue damage is analyzed to accumulate the damage as a stress function for a fatigue life exponent derived with the assistance of the acceleration's force response. The steps to determine the Weibull \(\beta\) and \(\eta\) parameters are estimated based only on the principal vibration stresses \(\sigma_{1}\) and \(\sigma_{2}\) that allow the reproduction of the vibration fatigue damage. The method's efficiency is based on the probabilistic approach by using the vibration fatigue damage as the \(Y_{i}\) vector that covers the arithmetic mean as well as the \(\beta\) parameter. Finally, the procedure proposed is applied in a practical case where a mechanical component is used as a support for telecommunication connections and is submitted to vibration stress. The results show that using the damage accumulated as the \(Y_{i}\) vector to estimate the parameters allows for the analysis of dynamic and individual applications.  
random vibration; mechanical fatigue; damage; Weibull distribution; reliability +
Footnote †: journal: Applied Sciences  
1
Footnote 1: Department of Mechanical Engineering, University of California, Berkeley, California 10004-8000, USA
# Fungi-Templated Silver Nanoparticle Composite: Synthesis, Characterization, and Its Applications
## Materials and Methods
### Antibacterial Studies  
Agar well diffusion studies were used to analyse the antibacterial properties of the developed composite against Gram negative Escherichia coli (_E. coli_) and Gram positive _Staphylococcus aureus_ (_S. aureus_) bacteria. To perform antimicrobial studies, Muller-Hinton (MH) agar media plates were prepared. _E. coli_ and _S. aureus_ were cultured in Luria Bertani broth and its growth was monitored at 600 nm. The spread plate method was used to inoculate on MH media. A gel puncture was used to make wells of 10 mm in each petri plate. To assess the antibacterial property, various concentrations (50-400 \(\upmu\)g) of FH-AgNPs were used. The compound for investigation was prepared in water (2 mg/mL) and using a sterile micropipette it was added into different wells as 50, 100, 200, and 400 \(\upmu\)g, respectively. The plates were then incubated at room temperature for 24 h and after incubation the zone of inhibition was measured.
# An Optical and SAR Based Fusion Approach for Mapping Surface Water Dynamics over Mainland China
## 5 Discussion  
To the author's knowledge, this is the first assessment of surface water over mainland China at a 10 m resolution using an optical-SAR sensor fusion approach. The results convincingly demonstrate that the use of 10-m resolution Sentinel data offers significant improvements and reveals new insights over Landsat based products at a 30 m resolution, both in terms of spatial detail and better and more consistent seasonal monitoring of surface water extent.
# Strain Transfer Analysis of a Clamped Fiber Bragg Grating Sensor
## 2 Basic Theory  
An FBG sensor consists of a fiber core, cladding layers and coating layers. The main component of the fiber core is SiO\({}_{2}\), which is usually mixed with some infinitesimal amount of GeO\({}_{2}\) to change the refractive index of the sensor. As the refractive index of the fiber core is larger than that of the cladding layer, the light is totally reflected through the fiber core to achieve a long distance transmission of the signal with little energy loss. When the broadband light is transmitted to an FBG sensor, the light with a specific wavelength is reflected, which is satisfied with the Bragg condition [15; 16], that is,  
\[\lambda_{\text{B}}=2n_{eff}\Lambda \tag{1}\]  
where \(\lambda_{\text{B}}\), \(n_{eff}\) and \(\Lambda\) are the FBG wavelength, the refractive index of the fiber core and the FBG period, respectively.  
When the strain and temperature change simultaneously, the wavelength shift equation is expressed as follows:  
\[\Delta\lambda/\lambda=[(1-P_{e})\varepsilon+(\alpha+\xi)\Delta T] \tag{2}\]  
where \(\Delta\lambda\) is the FBG wavelength shift; \(P_{e}\) is the FBG strain-optic coefficient; \(\alpha\) is the FBG thermal expansion coefficient; \(\xi\) is the FBG thermo-optic coefficient; and \(\Delta T\) is the temperature variation [17].
# Numerical Modeling for Tunnel Lining Optimization
## 2 Case Study
### Geotechnical Conditions  
Four standard penetration tests SP-1, SP-2, SP-3, and SP-4 were conducted at the site to characterize the subsurface conditions. The average exploration depth was around 40 m.  
Figure 1: Project trace and geotechnical zoning of Mexico City.  
In addition, index properties were obtained from disturbed samples retrieved at several depths, which were used to establish the geotechnical units according to the Unified Soil Classification System (USCS). Strength and deformability parameters were determined from unconfined compression tests and triaxial UU tests conducted in undisturbed samples, as well as in situ phicometer and pressuremeter tests. Figure 2 shows the soil profile characterization. In addition, empirical correlations [41] based on SPT blow counts (N\({}_{\text{SPT}}\) values) were also used to determine strength and deformability parameters (i.e., cohesion c, internal friction angle \(\varphi\), and Young's modulus at 50% strain E\({}_{50}\)). In the cases where N\({}_{\text{SPT}}\) values were larger than 50, the values used in the correlation were extrapolated according to the LRFD Bridge Design Specifications [42] AASHTO (Equation (1)).  
\[N_{SPT}=\frac{(50+N_{2})\times 30}{15+N_{3}} \tag{1}\]  
where N\({}_{\text{SPT}}\) is the extrapolated number of standard penetration test blow counts and N\({}_{2}\) and N\({}_{3}\) are the second and third advances of the standard penetration test.  
The geotechnical properties of the soil profile estimated initially are summarized in Table 1. Poisson's ratio \(\
u\) was defined from typical values for similar materials. The water table was not detected until the maximum explored depth.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Layer**} & \multirow{2}{*}{**USCS**} & \multirow{2}{*}{
\begin{tabular}{c} **N\({}_{\text{SPT}}\)** \\ **(Blows Counts)** \\ \end{tabular} } & \(\gamma\) & c & \(\varphi\) & **E\({}_{50}\)** & \(\
u\) \\  & & & **(kN/m\({}^{3}\))** & **(kPa)** & **(\({}^{\circ}\))** & **(MPa)** & **(\({}^{\circ}\))** \\ \hline UG-1 & ML & 42 & 15.8 & 18 & 28 & 120.8 & 0.32 \\ \hline UG-2 & SM & 167 & 18.2 & 45 & 29 & 900.4 & 0.28 \\ \hline UG-3 & CL-ML & 40 & 17 & 13 & 27 & 97.5 & 0.34 \\ \hline UG-4 & ML & 126 & 18.2 & 40 & 28 & 470.5 & 0.28 \\ \hline UG-5 & SC & 80 & 19.2 & 33 & 31 & 303.2 & 0.27 \\ \hline \hline \end{tabular}  
\({}_{\text{SPT}}\) = extrapolated number of standard penetration test blow counts; \(\gamma\) = unit weight; c = cohesion; \(\varphi\) = friction angle; E\({}_{50}\) = Young’s modulus at 50% strain; \(\
u\) = Poisson ratio.  
\end{table}
Table 1: Initial geotechnical properties at the studied site estimated with correlations.  
Figure 2: Soil profile and tunnel at the studied site.
## 4 Materials and Methods
### Transcriptome Assembly and Annotation  
The raw reads obtained from RNA sequencing were filtered by trimming adapters and removing low quality reads (reads containing more than 10% of unknown nucleotides (N) or 40% of low quality (Q-value \(\leq\) 10) bases) to obtain the high-quality clean reads. All data generated in this study have been deposited in the National Center for Biotechnology Information (NCBI) and can be accessed in the Short Read Archive (SRA) Sequence Database under accession number SRP132644. Then, Trinity program was used to perform de novo assembly of the clean data [51]. After assembly, unigenes were obtained and functional annotation was carried out using BLASTx program ([[http://www.ncbi.nlm.nih.gov/BLAST/](http://www.ncbi.nlm.nih.gov/BLAST/)]([http://www.ncbi.nlm.nih.gov/BLAST/](http://www.ncbi.nlm.nih.gov/BLAST/))) with an \(E\)-value threshold of 1 \(\times\) 10\({}^{-5}\). Public databases including the NCBI non-redundant protein database (Nr) ([[http://www.ncbi.nlm.nih.gov](http://www.ncbi.nlm.nih.gov)]([http://www.ncbi.nlm.nih.gov](http://www.ncbi.nlm.nih.gov))), the SwissProt database ([[http://www.expasy.ch/sprot](http://www.expasy.ch/sprot)]([http://www.expasy.ch/sprot](http://www.expasy.ch/sprot))), the KEGG ([[http://www.genome.jp/kegg](http://www.genome.jp/kegg)]([http://www.genome.jp/kegg](http://www.genome.jp/kegg))), and the COG/KOG database ([[http://www.ncbi.nlm.nih.gov/COG](http://www.ncbi.nlm.nih.gov/COG)]([http://www.ncbi.nlm.nih.gov/COG](http://www.ncbi.nlm.nih.gov/COG))) were used to annotate the _M. canadensis_ unigenes. TFs were identified by aligning unigenes to the PlantTFDB database [52].
## 4 Results and Discussion  
### Measurement Setup  
To verify DoA estimation performance of the two-row ESPAR antenna using the generalized PPCC-MCP method 18 available antenna radiation patterns were measured in our 11.9 m \(\times\) 5.6 m \(\times\) 6.0 m anechoic chamber, shown in Figure 10, at 2.44 GHz using P9374A Keysight Streamline USB Vector Network Analyzer. The antenna was mounted at \(H\) = 4.1 m on a precise and equipped with a digital encoder turntable, which is able to set any 2D position with 0.1\({}^{\circ}\) precision in both horizontal and vertical directions. The transmitting antenna was placed on a pole stand at the same height \(H\) = 4.1 m, 8 m from the two-row ESPAR antenna. Every radiation pattern was measured with the angular step \(\Delta\varphi=1^{\circ}\) in the horizontal plane for \(0^{\circ}\leq\varphi<360^{\circ}\) and with the angular step \(\Delta\theta=1^{\circ}\) in the vertical plane for \(0^{\circ}<\theta\leq 90^{\circ}\). As a result, \(I\) = 360 calibration points were produced for every elevation plane and M = 90 calibration planes were created, namely \(\{\theta_{1}=90^{\circ},\ \theta_{2}=89^{\circ},\ \ldots,\theta_{90}=1^{\circ}\}\).
## 3 Results and Analysis
### Case Study I: 69-Bus Test System
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Decision** & **(PV)** & **(W)** & **(H)** & **(PV)** & **(W)** & **(H)** & **\(C_{instal}\)** & **\(LAE_{dayly}\)** & **\(EqCO_{2}EF\)** & **NPV** \\
**Criteria** & **Bus** & **Bus** & **Bus** & **NDG** & **NDG** & **NDG** & **NDG** & **(10\({}^{6}\) USD)** & **(MWh)** & **(ton/10** & **(10\({}^{6}\) USD**)** \\  & & & & & & & & & & & & **Years)** & **10 Years** \\ \hline Min. losses & 13 & 68 & 62 & 4 & 5 & 6 & 4.74 & 1.93 & 2.28 & 1.742 \\ Max. NPV & 29 & 68 & 62 & 0 & 5 & 6 & 4.20 & 1.95 & 2.26 & 1.844 \\ MMA & 13 & 68 & 62 & 2 & 1 & 3 & 2.80 & 2.30 & 1.11 & 1.290 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Case study I: final solution phenotypes of minimum power losses, maximum NPV and MMA decision criteria. Figure 4: Graphic comparison among objective functions for conflict checking—case-study I.  
served in the solution based on maximum net present value criterion, since the DG owner seeks to sell the highest amount of energy aiming a shorter payback time. Concerning the solution of the Max-Min approximation criterion, the comparatively lower number of generation modules reflects the needs for negotiations among conflicting goals to support a more efficient decision-making process. The solution based on the criterion of minimum losses presents daily active power losses \(LAE_{daily}\) = 1.93 MWh, which results a power loss reduction of 36.7% in comparison to the daily active power losses \(LAE_{daily}\) = 3.05 MWh when no dispersed generation is allocated in the distribution network, although a installation cost of 4.74 \(\times\) 10\({}^{6}\) USD will be necessary. Regarding the maximum NPV criterion, a minimum attractiveness rate MAR = 15% and energy price 0.15 \(\$\)/kWh are adopted in this work, so that the chosen solution presents a net benefit of 1.844 \(\times\) 10\({}^{6}\) USD. If the DisCo will be the DG owner, \(LAE_{dayly}\) = 1.95 MWh can be converted in USD using the same energy price and MAR as interest rate, which will result in savings of 7.4 \(\times\) 10\({}^{6}\) USD to the DisCo. In this case, both minimum losses and maximum NPV can be adopted as preference criteria to the DisCo. MMA decision criterion presents daily active power losses \(LAE_{daily}\) = 2.3 MWh, which results in a power loss reduction of 24.6% (DisCo savings: 4.95 \(\times\) 10\({}^{6}\) USD) compared to the case with no dispersed generation in the distribution network. MMA solution represents approximately 60% of installation cost and 50% of equivalent CO\({}_{2}\) emission compared to the minimum losses and maximum NPV criteria. Therefore, MMA can be adopted as a non-preference decision criterion aiming at common good among perspectives of concern.
# Effects of Adding Batteries in Household Installations: Savings, Efficiency and Emissions
## 4 Case Study  
The average demand data for electrical appliances in the United Kingdom collected by Intertek was selected [1]. The case considered is a house inhabited by a family with children; a moderate use of electrical appliances was assumed, with an installed power of 4.6 kW.  
Electrical appliances were evaluated under the same conditions, so the prices of AC devices were considered to be the same as those of the equivalent models in DC. It has also been considered that DC voltage levels tend to a constant value, due to technological trends.  
A lithium battery was selected in order to optimize its use, since it covers the household energy demand, allows high depth of discharge with high efficiency and does not need much space. The characteristics of the battery used in the study are those of the Tesla Powerwall [45]. The capacity is 13,500 Wh, the maximum discharging and charging powers are 7000 and 5000 W for AC and DC respectively and the efficiency in the complete cycle is 90%.  
The differences in energy demand in different months were obtained from Red Electrica de Espana (REE) data [23]. It was established that the habits in the house are different on working days (from Monday to Friday) and non-working days (Saturday and Sunday). The following days were considered as holidays: 1 January, 6 January, 13 April, 1 May, 31 May, 1 June, 15 August, 1 November and 25 December.  
Winter and summer schedules were also distinguished; the time change was set according to official time change dates, i.e., 31 March and 27 October. In order to determine the costs, Iberdrola's Plan Noche--a charging system proposed by that company--was chosen [22]. Consequently, a time discrimination price was established with a fixed term of 45 \(\upxi\)/kW per year and where peak hours' cost is 0.183101 \(\upxi\)/kWh and off-peak hours' cost is 0.091863 \(\upxi\)/kWh. Following Spanish standards, peak hours in the summer period are from 1 p.m. to 11 p.m. and in the winter period, from 12 p.m. to 10 p.m., being the off-peak hours the supplementary hours for each period.  
For the comparison of greenhouse gas emissions in both cases, the average European CO\({}_{2}\)-emission-intensity levels in the EEA [20] were used.
# The Effect of Slow-Release Fertilizer on the Growth of Garlic Sports and the Soil Environment
## 2 Materials and Methods
### Testing of the Physiological Indicators of the Garlic Sprouts
#### 2.4.4 Determination of the Vitamin C (Vc) Content Using UV Spectrophotometry  
The vitamin C (Vc) content in the garlic sprout leaves was determined using ultraviolet (UV) spectrophotometry [38]. Fresh leaf samples were homogenized with a known volume of oxalic acid solution and transferred into a 100 mL volumetric flask, where the volume was adjusted with oxalic acid solution to prepare the extract for analysis. Subsequently, a dual-system measurement was performed. For the acidic system, 0.2 mL of the extract was placed into a 10 mL graduated test tube, followed by the addition of 0.8 mL of 2% oxalic acid solution, and the volume was adjusted accordingly. The absorbance (A_acid) was measured at 243 nm, using oxalic acid solution as the blank. For the alkaline system, another 0.2 mL of the extract was added to a separate 10 mL graduated test tube, mixed with 0.8 mL of 1 mol/L NaOH solution, and allowed to react for 15 min. The solution was then diluted with distilled water, and its absorbance (A_alkali) was measured at 243 nm, using NaOH solution as the blank. The vitamin C content was calculated based on the difference in the absorbance between the alkaline and acidic systems (\(\Delta\)A = A_alkali \(-\) A_acid), using a pre-established standard curve.  
2.4.5. Determination of the Allicin Content Using the Phenylhydrazone Method  
The allicin content in the garlic seedling leaves was determined through the phenylhydrazone method [39]. Fresh leaf samples were thoroughly ground in a mortar to prepare a homogenate, which was then transferred into a 100 mL volumetric flask. The volume was adjusted with distilled water, and the mixture was maintained at a constant temperature of 25-35 \({}^{\circ}\)C for 1 h. Subsequently, 2 mL of the extraction solution was mixed with 8 mL of trichloroacetic acid solution. After centrifugation, 2 mL of the supernatant was collected and reacted with an equal volume of 0.2% 2,4-dinitrophenylhydrazine solution. The resulting precipitate was separated through centrifugation and dissolved in 7 mL of ethyl acetate. The solution was then extracted with 10 mL of ammonia water, and the ammonia water phase was retained as the test solution. Using ammonia water as the blank, the absorbance of the test solution was measured at 420 nm. The allicin content was calculated according to a pre-established standard curve.
# Progress in THz Rectifier Technology: Research and Perspectives
### THz Diode Technology: I-V Characteristics and Figures of Merit (FOM) for MIM Diode
#### 2.2.4 Zero-Bias Resistance (ZBR)  
Differential resistance \(r_{D}\) given by Equation (4) and zero-bias resistance (ZBR) given by Equation (5) influence the behavior of the diode. The first resistance is obtained as a differentiating current with respect to the applied voltage [7; 23; 27; 28; 29]:  
\[r_{D}=\frac{1}{I^{\prime}},\text{ where }l^{\prime}=\frac{dI}{dV} \tag{4}\]  
Its value increases exponentially with \(d\); therefore, to obtain low resistance, barrier heights and insulator thickness must be small.  
The second resistance ZBR, evaluated at zero-bias voltage, is obtained:  
\[R^{ZB}=\left(\frac{dV}{dI}\right)_{V=0} \tag{5}\]To ensure maximum transfer of energy captured by the antenna towards the load, the ZBR value must coincide with that of the antenna's resistance. This condition only occurs if the barrier heights on both sides of the metals are low and the insulator layer is very thin (typically less than 3 nm in the case of diodes with a single insulator layer).
## 3 Proposed Methodology  
The focus of this research study is on recognizing and characterizing the received radio frequency signals. To this end, a hierarchical classification design is proposed in which the first level deals with signal type recognition, and the second one automatically classifies the modulation type. Figure 1 presents the overview of the set-up, configuration, and framework of this study. It includes four main steps, namely data acquisition, feature extraction, feature selection, and classification. Each step is presented in detail in the rest of this section.  
Figure 1: Proposed RFI recognition and characterization methodology.
## 5 Performance Evaluation  
In this section, we provide extensive simulations by MATLAB to demonstrate the correctness of the theorems and the impact of ICI on the PSNE for the CS games with a large amount of densely-deployed devices in HCNs. The simulation area is a single macrocell with a radius equaling 1000 m. A small number of picocells are almost randomly deployed within the coverage of the macrocell, but assuming that they do not overlap with one another. This is achieved by randomly choosing the picocells' locations one-by-one and making sure each one is not overlapped with those already deployed.  
Since this study considers the uplink, the transmission power is set to 23 dBm for devices selecting the macrocell [71]. By contrast, the transmission power for the devices selecting picocells should be less than this because of power control, expanding from \(-9\)-\(10\) dBm, adjusted to fit for different picocell sizes and path loss exponents. Each macrocell uses the total uplink bandwidth of the system, _i.e._, 10 MHz, while picocells get part of the total uplink bandwidth because of the ICI coordination for picocells in HCNs. The AWGN spectral density is set to \(-174\) dBm/Hz, and the radio frequency is set to 1.9 MHz. We set the density to \(10^{5}\) devices/macrocell with a uniform distribution within its cell coverage. The maximum number of rounds of simulations for obtaining each point in the following figures is 100, and each round has newly deployed positions of the picocells, as well as the devices.  
In each round, we use the method proposed by [PERSON] in [72] to search for the PSNE. The method is to check each player's willingness to change strategy, and the searching process reaches a PSNE if no player feels like making further changes. This method guarantees the convergence to the PSNE in just a few iterations for congestion games, so it fits quite well for this study.