esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Micro-sprinkling irrigation is a small-flow irrigation technology that uses the grouped outlets on the micro-sprinkling hoses to spray the pressure water evenly in the field. Plants' barriers during the middle to late growth period of winter wheat significantly reduce the irrigation quality of the micro-spray system. It is still unclear whether soil border width in wheat fields can alleviate the negative effect. In this study, a popularly-used variety (c.v. ZM 369) was adopted to test the mitigation effect of soil borders on irrigation quality, as well as soil moisture distribution, in wheat fields. Two irrigation quotas (i.e., 75 mm and 45 mm per time) and three border widths (i.e., 2.3 m, 3.3 m, and 5.3 m) were arranged in a randomized block design in the experimental years of 2020-2022. Soil moisture distribution and irrigation quality during the middle to late growth period of winter wheat (i.e., jointing to heading stage and grain filling stage) were investigated, as well as the effects on grain yield and water use efficiency (WUE). The results showed that irrigation water distribution in the direction perpendicular to micro-spray tapes generally decreased with the distance from tapes increasing. The maximum difference between the irrigation amount and water collected under the canopy was 134 mm. The uniformity coefficient of soil moisture distribution was increased by 25.8% with a 5.3 m border width compared to a 2.3 m width. Although an irrigation quota of 75 mm was beneficial for ensuring better irrigation uniformity and more stable grain yield, grain yield and WUE were produced with an irrigation quota of 45 mm. In conclusion, it is appropriate to increase border width and adopt a small quota for the micro-spray system in the North China Plain for wheat crops.  
Keywords:uniformity coefficient; canopy interception; water saving; water use efficiency +
Footnote †: journal: Applied Sciences
## 4 Discussion
In forest regions with low FMI efficiency, first, the amount of FMI should be reasonably controlled, and limited funds should be allocated to forest regions with higher efficiency. Second, the management and supervision of the use of forestry funds should be strengthened, disease and insect pests and drought should be prevented in a timely manner, and timely thinning and replanting should be carried out to improve forest quality in SOFRs. This paper verified that the effect of increasing the carbon sink of FMI reflected the law of diminishing marginal benefits. According to the results of the model, when the FMI was greater than CNY 100 million, the marginal benefit remained at a stable low level. This result means that when the FMI reached CNY 100 million, the carbon sink volume did not change significantly. However, the marginal benefit curve did not intersect at 0, indicating that FMI has not yet reached the optimal investment scale. Therefore, the government should reasonably increase the amount of FMI when planning FMI in various forest regions. However, since all FMI is used to improve forest quality, the growth potential of each unit area of forest in a certain period of time is limited. Therefore, even without considering the problems in the process of fund management and use, there is a diminishing marginal benefit for each share of funds to increase the carbon sink. Generally, after the forest quality reaches a certain level, even if the FMI gradually increases, the forest quality tends to have a stable and slow growth state. Therefore, the effect of increasing the carbon sink of FMI shows a law of diminishing marginal benefits. The main contribution and innovation of the research lies in the establishment of an evaluation system for FMI efficiency. In addition, natural factors and forest resource characteristics are incorporated into the system to measure the utilization efficiency. Our research will help to explore the reasons for the differences in FMI efficiency, promote forest management according to local conditions, and improve the utilization efficiency of SOFRs. Furthermore, our research constructs a calculation method for the optimal investment scale for the purpose of ecological benefit. It plays an important role in improving government budget and final accounts, and provides a decision-making basis for forest management, fund allocation, and high-quality forest development. Of course, our research has limitations. Our research area was limited to SOFRs in Heilongjiang Province, and the results of the study have directional policy significance for SOFRs. However, due to regional heterogeneity, the applicability of this result to other SOFRs remains to be further verified. Future research can use the methods described in this paper to explore the difference in the efficiency of state-owned FMI and collective FMI in increasing carbon sinks. In addition, future research can subdivide the efficiency of increasing the carbon sink in various SOFRs and provide targeted suggestions for government FMI management and decision making.
## 3 Results and Discussion
### Experimental Design and Analysis of Variance
#### 3.2.2 Estimation of the Model Precision  
Figure 2A showed the comparison between the actual value and the model predicted value. It could be seen that the distribution of each experimental value was a straight line, indicating that the predicted value of the model was highly consistent with the actual experimental value. Normal probability plot of the studentized residuals was shown in Figure 2B, the distribution of the data points was almost on a straight line, and no serious deviation occurred, suggesting that the model had a good fitting effect. The data in Figure 2C confirmed that all the data were distributed within satisfactory ranges (\(\pm\)3).
# Energy Efficient Management of Pipelines in Buildings Using Linear Wireless Sensor Networks
## 5 Conclusions  
The paper presents an algorithm to set up a network of straight pipeline segments crossing each other and efficient deployment of sensor nodes by using the Lion Optimization Algorithm. The pipeline setup using the proposed algorithm exhibits better delay, lifetime and throughput of the network as compared to the ant colony optimization and genetic algorithm for varying length of pipeline. The proposed approach is particularly suitable for the pipelines used inside a large building as clear from the simulation results. Although the proposed approach has been validated using simulation experiments, the field study of the proposed approach is left as future work. One may explore the suitability of other meta-heuristic techniques and hybrid meta-heuristic techniques for node placement in crossing pipelines inside a large building.  
All authors contributed to the design of the work, assessment of the proposed method performance and to the writing of the manuscript.  
This work has been supported National Funding from the FCT--Fundacao para a Ciencia e a Tecnologia through the UID/EEA/50008/ 2013 Project; by the Government of Russian Federation, Grant 08-08; by Finep, with resources from Funtlet, Grant No. 01.14.0231.00, under the Centro de Referencia em Radiocommunicacoes--CRR project of the Institution Nacional de Telecomunicacoes (Inatel), Brazil; and by Brazilian National Council for Scientific and Technological Development (CNPq) via Grants No. 309335/2017-5, 305805/2017-7, and 304315/2017-6.  
The authors declare no conflict of interest.  
Figure 11: Comparison of Normalized Lifetime (Range 100 m).
## 3 Results
### Optimization of the EO Treatment  
The inhibition percentage, obtained in GAC on MEA, was higher for 420 \(\upmu\)EO, nevertheless the duration of inhibition was comparable for the two tested EO volumes, until 42 days. For this reason, in the second set of tests we applied the lower EO volume (210 \(\upmu\)L). One or three Petri dishes (55 mm \(\O\)) with CZ\({}_{\text{mod}}\) medium were positioned in GAC before the EO volatilization as in MAM test. The growth of _A. alternata_ was inhibited starting from the 1 st day of treatment, correlated to the lower time necessary to reach the maximum EO concentration in the vapor phase (Figure 7A). In both the treated containers, the maximum mean diameter value, reached at the 3 rd day, was very similar (i.e., 1.62 \(\pm\) 0.23 and 1.56 \(\pm\) 0.13 cm for 1 and three colonies, respectively); in the same day, the diameter of the control was 2.76 \(\pm\) 0.41 cm and, at the 6 th day, it reached the plate boundary.  
Figure 5: Vaporization of different EO volumes on _A. alternata_ colonies in GAC: mean colony diameters.  
In the third set of experiments, pure EO was diffused as microparticles and inocula of different ages, 24, 72 and 96 h were tested.  
The results, reported in Figure 7B, clearly show that the EO treatment has a different efficacy depending on the inoculum age: more precisely, a higher inhibition was observed in the case of the 24- and 72- hours inoculum. In these samples, the mean diameter value, after 7 days of incubation, was 0.68 and 1 cm, respectively. In the case of 96 h inoculum, the EO inhibition was lower, in fact the colony diameter reached the edge of the paper sheet at the 7 th day of incubation.  
In a further test, which was extended up to 24 days, a 72 h inoculum was used (see Figure A2). Comparing the behavior of EO treated samples with that of the _A. alternata_ control, it is possible to highlight that, while the control reached the edge of the paper (4.6 cm) after 2 days of incubation, on the contrary, the EO treated sample was inhibited for all the incubation periods.  
Figure 6: _A. alternata_ growth on different CZ media (at the 7 th day ns, \(p=0.11\); at the 21 st day, \({}^{\star\star}\)\(p=0.037\) and \({}^{\star\star\star}\)\(p=1.08\times 10^{-6}\)).  
Figure 7: (**A**) Disk volatilization test in airtight container. (**B**) Cold diffusion test in airtight container.
###### Abstract  
Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets) offer a scalable backhaul option for collecting delay-tolerant data from sensors to gateways in order to enable efficient urban operations and services. While pervasive devices such as smartphones and tablets contribute significantly to the scalability of OppNets, closely following human movement patterns and social structure introduces network characteristics that pose routing challenges. Our study on the impact of these characteristics reveals that existing routing protocols subject a key set of devices to higher resource consumption, to which their users may respond by withdrawing participation. Unfortunately, existing solutions addressing this unfairness do not guarantee achievable throughput since they are not specifically designed for sensed data collection scenarios. Based on concepts derived from the study, we suggest design guidelines for adapting applicable routing protocols to sensed data collection scenarios. We also follow our design guidelines to propose the Fair Locality Aware Routing (FLARoute) technique. Evaluating FLARoute within an existing routing protocol confirms improved fairness and throughput under conditions that compromise the performance of existing solutions.  
opportunistic networks; delay tolerant data; sensed data collection; fair routing; wireless sensors; Smart City; Internet of Things; smartphones +
Footnote †: journal: Sensors. Actuator Netw. **2017**, \(6\), 31; doi:10.3390/jsan6040031  
1,2,2,3,4,5,6,7,8,9,10,11,1  
management [5], and meter readings [6]). Among the various possible backhaul solutions (e.g., cellular connectivity [7], mesh networks with ad hoc technologies [8], existing communication infrastructure in cities [1], and long-range transmission technologies), only OppNets achieve the desired coverage within the bounds of finite resources and limited budgets [9]. Based on the store-carry-forward (SCF) communication paradigm, data-bundles (or messages) are stored in device memory, carried from one point to another via user movement, and forwarded to another device (through available wireless communication interfaces such as Bluetooth and Wi-Fi) when they encounter each other (i.e., when the devices are within radio transmission range). In this manner, user devices act as routers that physically carry messages from their sources and eventually deliver them to their respective destinations in multiple hops. Not only does this eliminate costs related to procuring, installing, and maintaining network infrastructure (e.g., [10; 11; 12]), it also offloads infrastructure networks via direct device-to-device communication (e.g., [13; 14; 15]). These benefits have motivated various contributions including feasibility studies with mobility datasets [11], spatial analysis [16], evaluation testbeds [12], experiments with Bluetooth Low Energy [17], and duty-cycling mechanisms for extending sensor lifetime [18].
# Research on Micro-Vibration Analysis of Segmented Telescope Based on Opto-Mechanical Integration
## 2 Segmented Telescope Imaging Theory  
### Segmented Mirror Imaging Optical Model  
The segmented telescope primary mirror consists of 18 hexagonal sub-mirrors segmented together in the arrangement shown in Figure 1. When the incident beam is parallel light of unit amplitude, the aperture function of the segmented primary mirror can be expressed as:  
\[\mathrm{f(x,y)}=\sum_{j=1}^{N}\mathrm{f_{j}}\left(x-x_{j},y-y_{j}\right)=\sum_ {j=1}^{N}\mathrm{a_{j}}\left(x-x_{j},y-y_{j}\right)\cdot\exp\left(\mathrm{i} \phi_{j}\left(x-x_{j},y-y_{j}\right)\right) \tag{1}\]  
where \(\left(x_{j},y_{j}\right)\) is the center coordinate of the jth sub-mirror, \(\mathrm{f_{j}}\left(x-x_{j},y-y_{j}\right)\) is the aperture function of the jth sub-mirror, and \(\phi_{j}\left(x-x_{j},y-y_{j}\right)\) is the phase function of the jthsub-mirror. When the sub-mirror has position error or face shape error, the phase \(\phi_{\rm j}\) of the corresponding sub-mirror will be changed accordingly. \(\rm a_{j}\Big{(}x-x_{j},y-y_{j}\Big{)}\) is the transmission intensity function, expressed as the following equation:  
\[\rm a_{j}\Big{(}x-x_{j},y-y_{j}\Big{)}=\Bigg{\{}\begin{array}{ll}1,&\text{ inside}\\ 0,&\text{outside}\end{array} \tag{2}\]  
The complex amplitude distribution in the image plane can be expressed as the Fourier transform of the aperture function, viz:  
\[\rm U(x_{\rm f},y_{f})=\frac{1}{\lambda\rm f}\iint\sum_{j=1}^{N}f_{j}\Big{(}x- x_{j},y-y_{j}\Big{)}\cdot\exp\big{[}i2\pi\big{(}xf_{x}+yf_{y}\big{)}\big{]}dxdy \tag{3}\]  
where \(\lambda\) is the wavelength, \(\rm f\) is the focal length, \((x_{\rm f},y_{\rm f})\) is the image plane coordinates, \(\big{(}f_{x},f_{y}\big{)}\) is the frequency domain coordinates, and the PSF of the system is the mode square of the complex amplitude.  
When the sub-mirrors are all in the ideal position, the phase error of the sub-mirrors \(\rm f\Big{(}x-x_{j},y-y_{j}\Big{)}=0\), the PSF of a segmented mirror can be represented as the product of two factors:  
\[\rm F_{PSF}(x_{\rm f},y_{f})=\!\left(\frac{AN}{\lambda\rm\cdot f}\right)^{2}G( x_{\rm f},y_{\rm f})F_{s\text{-PSF}}(x_{\rm f},y_{\rm f}) \tag{4}\]  
where \(\rm A\) is the area of the monolithic sub-mirror. \(\rm G(x_{\rm f},y_{\rm f})\) the Fourier transform of the segmentation grid, usually a periodic function of sharp peaks, each of which is the Fourier transform of the full telescope aperture. \(\rm F_{s\text{-PSF}}(x_{\rm f},y_{\rm f})\) is the PSF of the monolithic sub-mirror.
## 3 Results  
Figure 1a-e shows the morphological analysis (SEM) that the particles were spherical in shape with a smooth surface for all formulations. The morphology of the drug-loaded microspheres was not significantly different from that of the nonloaded PLGA-CS-PEG microspheres, which implies that the morphologies of the PLGA-CS-PEG microspheres were not significantly affected by drug encapsulation. Figure 2 reveals that the mean particle sizes of the microparticles ranged from 1.17 \(\upmu\)m to 1.39 \(\upmu\)m.  
FTIR analysis was used to confirm the existence of CS and PEG on PLGA-CS-PEG microspheres. It was also used to study the interactions between the drug and polymer matrix. A representative FTIR spectrum for the PLGA-CS-PEG microspheres is shown in Figure 3. There was no evidence of strong bonds between the respective drugs (PGS or PTX) and PLGA-CS-PEG microparticles. In the FTIR spectrum, the characteristic band at 3422 cm\({}^{-1}\) is attributed to -NH\({}_{2}\) and -OH groups stretching vibration in the chitosan matrix [52] and followed by a peak at -2995 cm\({}^{-1}\) due to the amino group. The strong band at 1749 cm\({}^{-1}\) corresponds to the C=O stretching vibration of the carbonyl in the lactic and glycoside structure [53]. The characteristic peak revealed at 1084 cm\({}^{-1}\) of the PEG polymer is attributed to the C-O-C stretching vibration of the repeated--OCH\({}_{2}\)CH\({}_{2}\)--units of the PEG backbone. That was were. The occurrence of these characteristic peaks indicates that PEG and CS were successfully blended in the microspheres. Other peaks obtained in the fingerprint region are shown in Figure 3.  
Figure 1: SEM pictures of PLGA-CS-PEG microsphere formulations: (**a**) PLGA-CS-PEG_PCS5, (**b**) PLGA-CS-PEG_PCS8, (**c**) PLGA-CS-PEG, (**d**) PLGA-CS-PEG_PTX5, and (**e**) PLGA-PEG_PTX8 microspheres.  
Figure 2: Mean particle size of PLGA-PEG microspheres using Image J Software.
# Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2
## 2 Materials and Methods
### Satellite Data
#### 2.3.3 Derived Soil Moisture Products  
Soil moisture maps were produced at a high spatial resolution, by combining SAR and optical images derived from the S-1 and S-2 constellations, respectively. Backscattering models have been used to retrieve soil moisture over different period. Combined models were used to invert the radar signals for soil moisture estimation: The Water Cloud Model (WCM) (WCM) (WCM) (WCM) (WCM) (IEM) (WCM) (WCM), using a Neural Network technique. The WCM has been used for area covered by the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Satellites** & **Dates** & **Polarization** & **Incidence Angle (0)** \\ \hline S-1A & 20/10/2017 & VV & 39–40\({}^{\circ}\) \\ S-1B & 26/10/2017 & VV & 39–40\({}^{\circ}\) \\ S-1B & 07/11/2017 & VV & 39–40\({}^{\circ}\) \\ S-1A & 13/11/2017 & VV & 39–40\({}^{\circ}\) \\ S-1A & 25/11/2017 & VV & 39–40\({}^{\circ}\) \\ S-1B & 01/12/2017 & VV & 39–40\({}^{\circ}\) \\ S-1A & 07/12/2017 & VV & 39–40\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Spectral Bands** & **Wavelength (nm)** & **Spatial Resolution (m)** \\ \hline Band 1 (Aerosol) & 443 & 60 \\ Band 2 (Blue) & 490 & 10 \\ Band 3 (Green) & 560 & 10 \\ Band 4 (Red) & 665 & 10 \\ Band 5 (Vegetation Red-Age) & 705 & 20 \\ Band 6 (Vegetation Red-Age) & 740 & 20 \\ Band 7 (Vegetation Red-Age) & 783 & 20 \\ Band 8 (NIR) & 842 & 10 \\ Band 8A (Vegetation Red-Age) & 865 & 20 \\ Band 9 (NIR) & 945 & 60 \\ Band 10 (MIR) & 1375 & 60 \\ Band 11 (MIR) & 1610 & 20 \\ Band 12 (MIR) & 2190 & 20 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Sentinel-2 (S-2) spectral band characteristics.  
vegetation, while the IEM for bare soils. Both coupled models have considered soil moisture and roughness as soil parameters and vegetation indicator (e.g., vegetation height, biomass, LAI, etc.) derived from optical images. In this study, the NDVI was used to describe the vegetation cover, derived from the red (R) and near infrared (NIR) bands of S-2 images.  
These models have been calibrated and validated in previous studies [8; 12; 32; 36], over different study sites. The backscattering coefficient is modeled as the sum of the soil and vegetation contributions. It is then inverted to estimate soil moisture over the study site. [PERSON] et al. [12] and [PERSON] et al. [14] have shown that the soil moisture can be estimated with an accuracy of 6% vol. over agricultural fields. The 14 images were thus used to produce soil moisture maps, which were averaged over the period of acquisition. Figure 2 shows an example of soil moisture map from 14 of September 2017 with the masked area, presented in white color and corresponding to urban areas, water bodies, and some reliefs. Both maps, presented in the upper right corner of the figure, display two different case of soil moisture. The first one (with green colors) correspond to a wet date (01/12/2017) and the second one (with red colors) to a dry date (20/09/2017).
## 3 Results
### Screening for Efflux Pump Genes  
The great majority of biocide-tolerant isolates (n = 48, 92.3%) presented at least one of the two QAC efflux genes (\(smr\)-\(qacC/D\) and \(qacA/B\)), with greater prevalence of \(smr\)-\(qacC/D\), detected in 43 (89.6%) of these isolates. The \(qacA/B\) gene was observed in 14 (29.2%) of the isolates harboring efflux pump genes. Ten isolates (20.1%) presenting an efflux pump gene were simultaneously positive for the two tested genes.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Gene** & **Primers** & **Sequences** & **Amplicon (bp)** & **Reference** \\ \hline \multirow{2}{*}{_sea_} & SEA-1 & GAAAAAAGTCTGAATTGCAGGGAACA & \multirow{2}{*}{560} & [26] \\  & SEA-2 & CAAATAAAATCGTAATTAAACCGAAGGTTC & & \\  & SEB-1 & ACACCCAACGTTTACCAGAGAGCTA & & \\  & SEB-2 & TCCTGGCAGGCATCATGTCA & & \\  & SEC-1 & GTAAAGTTACAGGGTGCAAAACTTG & & \\  & SEC-2 & CATATCATCACAAAAAGTTTTCCGT & 297 & [26] \\  & SED-1 & GTGCTGAAATAAGAGACTAGC & & \\  & SED-2 & ATATGAAAGGGTCTGGG & & \\  & SEE-1 & CAAAGAATGCTTAAAGCC & & \\  & & ECE-2 & CACCTTACCGGCCAAAAGCTG & & \\  & SEG-1 & AATATGGAATGCCTAACCCGATC & & \\  & & SEG-2 & AAACTTATGGAACAAAGGTACTAGTTC & & \\  & & SEH-1 & CAATCACCATATATGCGAAAAGCAG & & \\  & SEH-2 & CATCATACCCAAAAACTTAGACC & & \\  & & SEH-1 & CTAAGCTGTAATTTGTTGTTG & & \\  & SEI-2 & AAAAAATTACAGGGTCCATTCC & & \\  & & SEI-1 & TAACCTCAGACATATATACTTTTAAACG & & \\  & & SEJ-2 & AGATATCATAAAAAGTTGATTTTTTCATGCAG & & \\ \hline \end{tabular}
\end{table}
Table 2: Primers used in the investigation of staphylococcal enterotoxin genes.  
Thirty eight out of 39 BC-tolerant isolates were positive for the _s smr-qacC/D_ gene, and 10 (25.6%) of them were also positive for the _qacA/B_ gene. Both genes were detected in nine (23.1%) BC-tolerant isolates.  
Eight HDP-tolerant isolates (n = 11) were positive for at least one of the two QAC efflux genes (72.8%). Among these isolates, _smr-qacC/D_ was detected in four, _qacA/B_ in five, and one isolate was positive for both genes.  
All HC-tolerant isolates (n = 5) were positive for the _qacA/B_ or _smr_ genes. Three (60%) isolates contained only _smr_, and two (40%) were positive for both markers.  
Among the isolates presenting at least one antibiotic resistance gene (n = 112), efflux pump genes were detected in 99 (88.4%), mainly _smr_, present in 92.9% of them. The _qacA/B_ was much less frequent, detected in 26 of these isolates (26.3%). Nineteen isolates (19.1%) were positive for both genes simultaneously.  
The majority of _S. aureus_ presenting tolerance to biocides and antibiotic resistance genes, simultaneously (n = 40), were positive for the _smr-qacC/D_ or _qacA/B_ genes (n = 37, 92.5%), with greater prevalence of _smr-qacC/D_, detected in 33 (82.5%). The _qacA/B_ gene was observed in 13 (32.5%) of these isolates. Nine isolates (22.5%) were positive for both genes.