esa-sceva/satcom-chunk-collection huggingface dataset:
# Hybrid Mode Reconfigurable Antenna with V-Shaped Extrudes for Cognitive Radio Applications
## 2 Antenna Design
When both diodes get switched OFF, the main lobe appears at 344 degrees, as shown in Figure 11d, with a dielectricity of 3.56 dB. The presence of the p-i-n diodes affects the surface current and electric field distribution of the patch antenna. When the diodes are off, the patch antenna behaves like a conventional microstrip patch antenna, with a uniform electric field distribution and surface current. However, when the diodes are on, the electric field distribution and the surface current are altered. In Figure 12, surface currents at 3.5 GHz and 4 GHz are observed when changing the state of both diodes. When D1 is ON and D2 is ON, as shown in Figure 12a at 3.5 GHz, the surface current mainly flows in the feedline, while when D1 is ON and D2 is OFF, it flows from feedline to the right side of the V-shaped extrude defined in Figure 12c. With conditions of D1-OFF and D2-ON, flow is observed from the feedline to the left side of the V-shaped extrude presented in Figure 12b. Switching both diodes OFF causes the current to flow from the feedline to both arms of the V-shaped extrudes, as explained in Figure 12d. Similarly, the surface current flow can be observed at 4 GHz. With  
Figure 2:2 Radiation pattern at 3.5 GHz with DGS: (**a**) D1(ON) and D2(ON); (**b**) D1(OFF) and D2(ON); (**c**) D1(ON) and D2(OFF); (**d**) D1(OFF) and D2(OFF). both diodes in the ON mode, the surface current mainly flows in the feedline defined in Figure 12e, causing the main beam at \(11^{\circ}\). When switching the state of D1 to OFF and D2 to ON, defined in Figure 12f, the current changes its direction towards the right edge of the V-shaped groove through the feedline, leading to a change the main beam direction at \(165^{\circ}\). Similarly, the main lobe appears to switch at \(15^{\circ}\) due to the change in direction of the surface current from the feedline to the left edge of the V-shaped groove under conditions of D-1 ON and D-2 OFF, as presented in Figure 12g. By changing both diodes to the OFF mode, defined in Figure 12h, the current direction changes again around the ground plane to the feedline, with the main lobe at \(344^{\circ}\). Figure 2:3 Radiation pattern at 4 GHz with DGS: (**a**) D1(ON) and D2(ON); (**b**) D1(OFF) and D2(ON); (**c**) D1(ON) and D2(OFF); (**d**) D1(OFF) and D2(OFF).
# Using an Uptake Enhancer to Mitigate Nitrogen Leaching While Enhancing Uptake Efficiency
## 1 Introduction
A study conducted by [PERSON] and [PERSON] [21] suggested that improved wetting of foliar fertilizer on the leaves increases the probability of foliar fertilizer uptake. They added that lower wetting leads to lower absorption rates of the fertilizer formulation. To improve the effectiveness of foliar absorption, adding adjuvants to the fertilizer formulation is often necessary [21]. Adjuvants are defined as any material added to a spray solution to enhance the absorption of the spray's active ingredient, whether the spray is a fertilizer, herbicide, or pesticide or to alter the properties of the spray [22]. When dealing with adjuvants, identifying the specific products available and their primary function is key. Adjuvants can be broadly categorized into several types based on their use, including wetter-spreaders, stickers, emulsifiable oils, foliar nutrients, and compatibility agents. Among these, nearly half of the available products are wetter-spreaders or stickers, with emulsifiable oils, foliar nutrients, and compatibility agents accounting for another third of the registrations. Consequently, even though there are 17 categories of adjuvants, 80% of the array of products available are in only five categories. Seven of the categories comprise trivial uses with minor purposes. Of the major uses, all but foliar nutrients, buffers, drift retardants, and possibly oils usually depend on surfactants to perform their major function. It is, therefore, important to understand the role of the surfactant chemical or principal active ingredients in performing the functions expected of an adjuvant and to be able to read the active ingredient statement on the label when comparing adjuvants and selecting the one most appropriate for your specific situation. This research focused on a product that is classified as a penetrant/uptake enhancer because it is categorized as a compound that penetrates the skin of a plant. By examining the efficacy and mechanisms of this uptake enhancer, the study aimed to evaluate the performance of the uptake enhancer added to (NH4) (NO3) fertilizer in increasing N uptake and preventing N losses in the soil profile during and after the vegetative period. In this study, we hypothesized that using an uptake enhancer can significantly increase N uptake while reducing N leaching in the soil profile. By improving the mechanisms of N absorption and assimilation in the plant root system, this uptake enhancer will thus lead to better N retention in the soil and more efficient utilization by the plant, which will then result in increased crop yields and reduced environmental impact.
# Mono Camera-Based Optical Vehicular Communication for an Advanced Driver Assistance System
## 3 Proposed Scheme
### Transmitter
Furthermore, the bit period of the low-rate data stream was chosen so that the modulation frequency did not fall below 100 Hz.
## 3 Results and Discussion  
### AgNPs-Dye Synthesis  
In the synthesis procedure schematized in Figure 1, the choice of FITC or RITC as a capping agent makes it possible to optimize the proximity between the fluorescent xanthene-based dye and AgNPs. Three different silver/dye M ratios were initially used:1/2, 1/1, and 1/0.1. The best result in terms of size, monodispersity, yield, and reproducibility of the samples was obtained with the 1/1 M ratio, which is the one on which the most in-depth characterizations were conducted (see Table S1a,b).  
The choice of FITC and RITC is related to their widespread use in biotechnological applications, such as protein markers and sensors [60; 61], and to their maximum absorption that is partially overlapped (FITC \(\lambda_{\text{max}}\) = 485 nm) or not (RITC \(\lambda_{\text{max}}\) = 555 nm) with respect to the localized surface plasmon resonance (LSPR). The AgNPs LSPR band occurs typically in the range of 380-480 nm, and its intensity and spectral width are controlled by the size, concentration, and monodispersity of AgNPs. In Figure 2a-d, the UV-Vis spectra of FITC, RITC, AgNPs-FITC, and AgNPs-RITC are shown. In particular, the absorption band of FITC is mostly overlapped with the LSPR at about 398 nm, producing a shoulder in the AgNPs-FITC sample with a slight shift compared with the free dye. The absorption peak of the AgNPs-RITC sample showed the presence of an LSPR due to the AgNPs at about 414 nm and a well-separated peak arising from the dye at about 560 nm.  
The DLS measurements from water suspensions confirmed the nanosize of both prepared AgNPs, as can be observed in Figure 3a,c. AgNPs-FITC have \(<\)2R\({}_{\text{H}}\)> = 78 \(\pm\) 12 nm  
Figure 1: Scheme of silver nanoparticle–fluorescein isothiamate (AgNPs–FITC) and silver nanoparticle–rhodamine B isothiamate (AgNPs–RITC) synthesis.  
Figure 2: UV–Vis spectra of (**a**) FITC; (**b**) RITC; (**c**) AgNPs–FITC; (**d**) AgNPs–RITC samples in water solution.  
and AgNPs-RITC have <2R\({}_{\rm H}\)> = 68 \(\pm\) 20 nm, with low or no aggregation as eVidenced by repeating the measurements up to 3 months after synthesis. An eVidence of the colloidal stability can also be obtained by looking at the zeta potential measurements, where both systems have a typical negative zeta potential, as shown in Figure 3b,d, with values indicating quite stable suspensions [57; 62; 63]. In this way, stable and monodispersed AgNPs were prepared [7; 64; 65].  
It is important to underline that both AgNPs-FITC and AgNPs-RITC are hydrophilic systems; on the particles, other molecules can be conjugated on the surface. As such, these investigations open vast opportunities by creating a new generation of fluorescent markers with immense promise and potential in biological analysis and detection.
## 3 Data-Constrained Modelling for the Samples
### Comparison of DCM and Threshold Segmentation Methods  
A sub-region of 796 \(\times\) 796 pixels with distinct porous structures was cropped from the 1150 th CT slice of sample 1. In this sub-region, the result of DCM was compared with those of four automatic image threshold segmentation algorithms, including Shanbhag [36], Triangle [37], Otsu [38], and Percentile [39]. The calculation of the image threshold segmentation was performed using ImageJ software. Figure 7 shows the original slice of the sub-region and the results of DCM and the automatic image threshold segmentation algorithms. It is seen from Figure 7 that for this type of sample image, with unimodal intensity distributions, the results obtained from threshold segmentation severely deviate from reality and are difficult to apply practically. The DCM not only accurately extracted the prominent cracks present in the CT slice but also identified numerous pixels occupied by partial pores. DCM, especially under the constraints of known information, can be effectively applied to the processing of similar images.  
Figure 6: The distribution of compositions computed by DCM in the X-ray CT slices, as shown Figure 2. Different colors represent different compositions, and the color intensity of each composition is proportional to its volume fraction in the voxel. Compositions coexisting in one pixel are shown as mixed colors. (**a**) Sample 1; (**b**) sample 2; (**c**) sample 3; (**d**) sample 4; (**e**) sample 5; (**f**) sample 6.  
Figure 7: Original CT slice and composition distribution maps obtained by different methods. (**a**) The sub-region of the CT slice of sample 1; the pore distribution results obtained by (**b**) DCM; (**c**) Shanbhag; (**d**) Triangle; (**e**) Otsu; (**f**) Percentile. In the DCM results, the pixel gray value is proportional to the porosity, and black represents the pore in other image threshold segmentation results.
# Resource Allocation and Offloading Strategy for UAV-Assisted LEO Satellite Edge Computing
## 1 Introduction
* A UAV-assisted air-space integrated task offload architecture is proposed in emergency scenarios, which jointly considers resource allocation and offloading schemes under the lack of ground resources of computing;
* A multi-satellite joint task offload scheme is proposed, which takes full advantage of satellite computing resources to complete the task with low delay and energy consumed;
* A Deep Reinforcement Learning (DRL) algorithm is proposed, and simulation experiments prove the functionality of the algorithm, reducing the weighted sum of the energy consumed and delay by an average of 64.5%. The remainder of this paper is organized as listed below. Section 2 showcases related work, including LEO satellite task offloading and UAV-assisted task offloading. Section 3 presents the model, problem description, and optimization objective. The satellite selection and the DDPG-LSTM algorithm are presented in Section 4. Section 5 analyses the experimental findings. Section 6 summarises the thesis.
## 4 Conclusions  
This article studied the effect of different technological factors on the compressive strength and fracture parameters of concrete with increased strength. A previously optimized amount of zeolitic tuff, different types of fibers and air-entraining agent were used to improve the behavior of concrete under load. The following conclusions can be drawn from the results obtained in the study:  
* The compressive strength of concrete increases by 27% after 1 day of hardening when different types of polypropylene fibers are added to concrete. The partial replacement (10% by mass) of Portland cement with zeolitic tuff and the addition of air-entraining agent result in the reduction of early strength, but over time, after 28 days of hardening, the strength of concretes R+F+A and R+Z+F+A is even greater than the strength of concrete R+F by 3.5 and 3.2%, respectively.
* Using zeolitic tuff results in the formation of a tight microstructure and particle-armored bubble shell in the concrete with an air-entraining agent. Low-base calcium hydrosilicates strengthen this shell and are formed in the non-clinker part of the cement matrix due to the excellent pozzolanic activity of zeolitic tuff.
* The concrete incorporating zeolitic tuff, different types of fibers, and an air-entraining agent, despite having a lower Portland cement content (by 10% by mass), exhibits enhanced mechanical properties and fracture parameters, with a 35.1% increase in fracture energy and a 61.5% increase in characteristic length, compared to the reference concrete. This improvement in concrete incorporating an air-entraining admixture is attributed to the even distribution of stresses around the armored bubble shell when the concrete is loaded.
* Both concrete R+F and concrete incorporating an optimized amount of zeolitic tuff, different types of polypropylene fibers, and air-entraining agent R+Z+F+A behave similarly under load in the post-cracking stage. This confirms the efficiency of the proper selection and the optimization of different technological factors, which allow one to obtain economically effective high-quality concrete incorporating a lower cement content. However, a comprehensive life-cycle assessment should be conducted to evaluate the sustainability of the developed concrete.  
Conceptualization, T.M. and Y.B.; methodology, Z.B., T.M. and J.S.; validation, Z.B., Y.B. and J.S.; formal analysis, Z.B., T.M. and J.S.; investigation, Z.B., T.M., Y.T., O.H. and J.S.; supervision, T.M., Y.T., Y.B. and O.H.; writing--original draft preparation, Z.B., [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON]; writing--review and editing, [PERSON], [PERSON], [PERSON] and [PERSON]; visualization, [PERSON], [PERSON] and Y.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 4 Results and Discussion  
### Microwave Frequency  
Microwave energy is absorbed as it passes through the material, and the ability to convert to heat energy is related to the microwave frequency. The depths of microwave heating road materials with different frequencies are different, which will cause different microwave energies to be concentrated on the surface of the road surface, thus changing the time when the junction between the ice layer and the road reaches 0 \({}^{\circ}\)C, and change the deicing efficiency. 2.45 GHz magnetron is widely used in microwave ovens or industrial microwave equipment, and its average market price is about 100 yuan, while the average price of 5.8 GHz magnetron is over 10,000 yuan, and the unit price is more than 100 times compared with that of 2.45 GHz magnetron. The cost is high, and the price comparison chart of different frequencies is as shown in Table 6. The working frequency of industrial microwave heating is 915 MHz or 2.45 GHz. Compared with 2.45 GHz radiation, the heating efficiency of 5.8 GHz radiation is higher and the penetration depth is smaller. Microwave de-icing efficiency increases with microwave frequency increasing. Combined with the current microwave deicing study, the frequency of 2.45 GHz is used, and the deicing of 5.8 GHz microwave is proposed to improve the microwave deicing efficiency. In this paper, the de-icing efficiency at the common microwave frequencies of 2.45 GHz and 5.8 GHz is studied from finite element simulations and indoor experiments.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Frequency (GHz)** & **Range (MHz)** & **Market Average Price (CNY)** & **Penetration Depth** \\ \hline
2.45 & \(\pm\)50 & 100 & Deeper \\
5.8 & \(\pm\)75 & 10,000 & Lighter \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of different microwave frequency prices.  
Figure 4: Microwave deicing test device.
# On Sharing an FIB Table in Named Data Networking
## 3 Proposed Work
### Packet Forwarding Procedure
In addition, the auxiliary FIB is much smaller than an ordinary FIB table, because it only has entries for name prefixes which produce positives in multiple faces, while the conventional FIB table has entries for all name prefixes. The memory consumption for storing F-BFs is also much smaller than that for storing an FIB table. Figure 4: An example of F-BFs merging-to reduce the time for querying F-BF[i], where \(i=1\cdots n\). F-BFs are merged into one functional Bloom filter [19; 26]. ```
FunctionOnInterest (Interest)  cachedData = ContetStore.Find( Interest ); ifcachedDatathen  Forward( cachedData, incomingFace ); return; else  PIT.Add( Interest );  end if faceFBF = F-BF.Query( Interest ); iffaces.cnt==1 then  Forward( Interest, faceFBF ); else  faceFIB = FIB.Find( Interest );  Forward( Interest, faceFIB );  end if  end for
```  
**Algorithm 3**Procedure for forwarding _Interest_ packets. The _Data_ packet handling procedure is shown in Algorithm 4 and in the lower part of Figure 5. When a _Data_ packet arrives as the response to an _Interest_ packet, the PIT is looked up. If the matching entry is found in the PIT, then the _Data_ is cached in the CS and forwarded to the faces in the matching PIT entry. The _Data_ packet handling procedure is the same as the conventional one, except that the auxiliary FIB table is updated according to the first arrived _Data_ if the _Interest_ has been forwarded to multiple faces as explained earlier. Figure 5: Packet handling procedure [5], where the upper part illustrates the _Interest_ packet handling procedure and the lower part describes the _Data_ packet handling procedure. ```
FunctionOnData(Data)  PITentry= PIT.Find(Data); ifPITentrythen  CS.Add(Data);  Forward(Data, face ); //update FIB table if there are multiple-matching faces ifPITentry.numForwarded>1 then  FIB.Add(Data, incomingFace );  end if else //actions based on policy  end if  end if
```  
**Algorithm 4**Procedure on handling _Data_ packets.
## 8 Conclusions  
A novel direction finding algorithm with low computational complexity is proposed in this paper. By combining the characteristics of the virtual baseline, the proposed algorithm adopts the sub-array divided technique and matrix inversion to acquire the course angle and the pitching angle. Four antenna elements are used as a combination, the elements do not need to be placed in the same plane. The simulations results demonstrate that there is little differences between the conformal array and the planar array in solving ambiguous probability and the RMSE. The proposed algorithm is suitable for direction finding based on conformal antenna in ultra-wideband. If the energy consumption of the direction finding system is fixed, the number of the direction finding of the proposed algorithm is much larger than that of MUSIC. The proposed algorithm has low energy consumption, which means one direction finding experiment based on the proposed algorithm can be completed in a very short time. It is suitable for real-time application.
## 2 Background and Key Features
### UAV Communication
#### 2.2.3 Cellular Network Communication  
With the popularity of 4G and 5G cellular networks, the application of cellular communication technology in UAVs has gradually increased. The advantage of cellular network communication is that it can utilize existing infrastructure, reducing construction costs while providing stable communication support. In [35], the authors studied the optimization of cellular network architectures that support high data transmission rates and wide area coverage for UAVs and proposed application scenarios and technical challenges for UAVs in diversified services (such as spectrum sharing and interference management). In [36], the authors looked forward to the development trend of cellular communication from 5G to 6G, introduced the key communication requirements of aerial platforms, including the latest progress in the 3 GPP standards, and discussed emerging needs in industrial and military applications. We expect that 6G will integrate future wireless access technologies, including OFDM-microwave, OFDM-millimeter wave, terahertz communication, URLLC, and seamless communication technology based on integrated space-air-ground networks. Unlike earlier generations that relied on narrowband, 6G will support ground broadband coverage and will also enhance regular broadband, ultra-broadband, and wireless internet technologies [37].
# Evaluation of Anti-Skid Performance of Asphalt Mixture Based on Accelerated Loading Test
## 1 Introduction
Consequently, it accurately assesses the long-term performance of the pavement structure or material under the negative impact of actual traffic loads over a prolonged period. It verifies the effectiveness of the pavement performance equation [5; 6; 7; 8; 9]. The present study employs a small accelerated loading test system, PAVEMLS11, to investigate asphalt mixtures' attenuation characteristics and anti-skid durability. This study investigates the anti-skid durability of asphalt mixtures using a 1/3 size accelerated loading test and various anti-skid surfaces. Key factors that affect the long-term anti-skid performance of asphalt mixtures, including aggregate lithology, gradation, and oil-stone ratio, are explored. The novelty of this study lies in the systematic analysis of the effects of different aggregates, such as diabase, on the anti-skid resistance of the asphalt mixture. Skid resistance is evaluated through texture depth and pendulum value tests on six groups of AC and SMA asphalt mixtures. An anti-skid performance index, measured by the British Pendulum Number (BPN), is established based on laboratory accelerated loading tests. The BPN and its attenuation rate (B) after the stability of the accelerated loading test are used as the index of the anti-skid durability of the asphalt mixture. The flowchart of the study is shown in Figure 1:
## 3 Experimental Section
### Measurements and Instruments  
The chemical structures of PDMAEMA and star PDMAEMA were studied by FT-IR and \({}^{1}\)H NMR spectroscopy. FT-IR spectroscopy on a Nicolet 6700 FT-IR spectrophotometer with the polymer samples dispersed in KBr pellets. \({}^{1}\)H NMR spectra were recorded on a UNITY-plus 400 M nuclear magnetic resonance spectrometer using CDCl\({}_{3}\) as the solvent and tetramethylsilane (TMS) as internal standard. XRD was used to test the crystallinity of the polymers. The number-average molecular weight (\(M_{\rm n}\)), weight-average molecular weight (\(M\)w), and polydispersity (\(M\)w/\(M_{\rm n}\)) of the polymers were determined by gel permeation chromatograph (GPC) with a set of a Waters 1515 isocratic HPLC pump and a Waters 2414 Refractive index detector under the control of Breeze software run by an external PC. DMF+0.05M LiBr was used as the mobile phase at a flow rate of 1.0 mL/min at 60 \({}^{\circ}\)C and monodisperse polymethyl methacrylate (PMMA) standards were used in the calibration of molecular weights.  
The permeation testing set-up used were similar to reported previously. The effective membrane area is 19.6 cm\({}^{2}\). The obtained membrane was tested by feed gas which was pure gas of CO\({}_{2}\) and N\({}_{2}\). The permeation rate of the gas was calculated from the flow rate of H\({}_{2}\) which is the sweep gas and the integral area of the penetrate gas, CO\({}_{2}\) and N\({}_{2}\), by the gas chromatograph with a thermal conductivity detector. The permeation rate and the selectivity are given by are given by \(\rm Ri=Ni/\Delta\rm pi\), \(\rm Sc_{CO2/N2}=R_{CO2}/R_{N2}\) where Ni is the permeation flux of permeate gas, \(\Delta\rm pi\) is the trans-membrane partial pressure difference. \(\rm R_{CO2}\), \(\rm R_{N2}\) are the permeation rate of CO\({}_{2}\) and N\({}_{2}\), respectively.