esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Numerical Investigations and Remarks  
In this paper, the accuracy of the present analytical approach for the critical buckling loads of non-corrugated FG-CNTRC cylindrical shells under radial loads are compared with the results reportedby [PERSON] [22]. In these comparisons, the SWCNT is reinforced in the longitudinal direction of shells. As can be seen in Table 1, the very small differences between the present results with the corresponding results of [PERSON] [22] are recognized. Numerical examples are given to investigate the nonlinear buckling and postbuckling behavior of spiral corrugated FG-CNTRC circular cylindrical shells under radial loads. The mechanic properties of the isotropic Poly methyl methacrylate matrix (PMMA) material are considered to be \(\
u^{m}=0.34\), \(\alpha^{m}=45(1+0.0005\Delta T)\times 10^{-6}/\text{K}\) and \(E^{m}=(3.52-0.0034T)\times 10^{12}\) Pa in which \(T\) is the temperature of the environment. The CNT is reinforced in the circumferential direction of shells. The mechanic properties of CNT are presented in the work of [PERSON] [23] as follows:  
\[ \begin{array}{l}\
u^{CNT}_{12}=0.175,\\ E^{CNT}_{11}=\left(6.18387-0.00286T+4.22867\times 10^{-6}T^{2}-2.2724\times 10^{-9 }T^{3}\right)\times 10^{12}\text{ Pa},\\ E^{CNT}_{22}=\left(7.75348-0.00358T+5.30057\times 10^{-6}T^{2}-2.84868\times 10^{-9 }T^{3}\right)\times 10^{12}\text{ Pa},\\ G^{CNT}_{12}=\left(1.80126+7.7845\times 10^{-4}T-1.1279\times 10^{-6}T^{2}+4.93 484\times 10^{-10}T^{3}\right)\times 10^{12}\text{ Pa},\\ \alpha^{CNT}_{11}=\left(-1.12148+0.02289T-2.88155\times 10^{-5}T^{2}+1.13253 \times 10^{-8}T^{3}\right)\times 10^{-6}/\text{K},\\ \alpha^{CNT}_{22}=\left(5.43874-9.95498\times 10^{-4}T+3.13525\times 10^{-7}T^{2}-3. 56332\times 10^{-12}T^{3}\right)\times 10^{-6}/\text{K}.\end{array}  \tag{30}\]  
The coefficients \(\eta_{1}\) and \(\eta_{2}\) are estimated by using the elastic constants \(E_{11}\) and \(E_{22}\) of CNTRC shells and can be applied with the rule of mixture to those from molecular dynamics simulations, as reported by [PERSON] and [PERSON] [50]. According to results of [PERSON] and [PERSON] [24], \(\eta_{1}=0.137\), \(\eta_{2}=1.022\) applies for the case of \(V^{*}_{CNT}=0.12\); \(\eta_{1}=0.142\), \(\eta_{2}=1.626\) applies for the case of \(V^{*}_{CNT}=0.17\); and \(\eta_{1}=0.141\), \(\eta_{2}=1.585\) applies for the case of \(V^{*}_{CNT}=0.28\) and \(\eta_{3}:\eta_{2}=0.7:1\). The FG-CNTRC corrugated cylindrical shells are considered with the geometrical parameters given by \(L=0.75\) m, \(R=0.5\) m, and \(h=1\) mm. In this paper, the numerical results are investigated at room temperature (\(T=300\) K). Table 2 presents the critical buckling loads \(q^{\sigma\tau}_{0}\) for non-corrugated and corrugated FG-CNTRC cylindrical shells with these three types of distribution (UD, FG-X and FG-O distributions), under radial loads. To validate the effect of corrugations, the thickness of non-corrugated cylindrical shell is calculated so that the material quantity of non-corrugated shell is equal to the corrugated shell, respectively.
## 2 Study Area and Method
### The InTEC Model  
The InTEC model divides the whole ecosystem carbon pool into four vegetation carbon pools (coarse root, fine root, stem, and leaf), five litter carbon pools (surface structure litter, surface metabolism litter, soil structure litter, soil metabolism litter, and woody litter), and four soil carbon pools (surface microorganism, soil microorganism, slow pool, and inert carbon pool) to analyze the long-term ecosystem carbon balance. The vegetation carbon pool is calculated according to annual NPP and a certain carbon allocation ratio. The four vegetation carbon pools are calculated based on the initialized annual NPP combined with different carbon allocation ratios, and the four vegetation carbon pools are added to obtain the total biomass carbon pool. The carbon of litter increases soil carbon pools, while soil heterotrophic respiration leads to a reduction in soil carbon pools. The carbon of litter is calculated based on the turnover rate of different parts of the vegetation; the turnover rate is shown in Table 1. Soil heterotrophic respiration is the amount of soil carbon pool decomposition to the atmosphere, which is determined by the decomposition rate of each carbon pool. The forest ecosystem NEP is the difference between annual NPP and heterotrophic respiration, where NPP varies with climate, atmospheric composition, soil conditions, and disturbance factors [25; 26; 34; 35]. The InTEC model includes four core processes: (1) The Farquhar photosynthetic model, based on leaf photosynthesis, is used to simulate gross primary productivity (GPP) [25; 36]; (2) Reconstruct the historical NPP according to the normalized _NPP-age_ relationship and meteorological data, distributed to each vegetation carbon pool through different distribution ratios; (3) Simulate soil moisture and temperature according to the three-dimensional distributed hydrological model [37]; and (4) the CENTURY soil model and net nitrogen mineralization model of [PERSON] et al. [38] is used to simulate the C\(\backslash\)N cycle. The InTEC model takes the effects of man-made and natural disturbances on forest NEP into consideration. Therefore, this study assumes that forest growth is affected by falling, forest recovery processes, forest age change, climatic factors, and soil factors.
## 4 Trajectory Optimization Problem
### Model Predictive Control (MPC) Optimization
**Remark 5**: _Despite the advantage of MPC optimization in obtaining the global optimal trajectory, it imposes a greater computation cost, particularly when the number of samples increases in the finite receding horizon to achieve more optimality. Furthermore, obstacle-free navigation as well as the validation of UAV-IoVs LoS links to maximize communication performance are extra concerns that are not considered in \(\mathcal{P}2\) in this work. Therefore, the current paper considers \(\mathcal{P}2\) a basic MPC optimization problem that can be completed by embedding objectives and constraints associated with the wireless communication performance and proposing a solution considering crash-avoidance navigation. Hence, we will not evaluate the performance of MPC optimization in the simulation results in this paper, as this requires an appropriate solution, which can be considered to extend the research._  
**Remark 6**: _The rotational dynamics are disregarded in the trajectory optimization problems \(\mathcal{P}1\) and \(\mathcal{P}2\), which may result in a sharp transition in the vehicle states after each sampling. Although heading change has been limited, using input jerks \(\mathfrak{U}[k]\) as real motion primitives may not adequately satisfy rotational dynamics. To make the generated trajectory dynamically feasible, smoothing the trajectory is required, which is addressed in the next subsection._
## 2 Requirements of Collectively Watching Real-time Contents  
With wideband optical modulation techniques like D-WDM, the core of the Internet (mainly fibre-optics with OC-192/768 SONET) is observed to be congestion free (currently a considerable percentage of the Internet core fibres are believed to be dark) and it is trouble-free and economical for expansions. Also, access network technologies like VDSL2, FTTH, WiMaX and IEEE 802.11n ensure affordable fast last-miles. However, edge networks (_i.e._, networks connecting access networks to the core, Figure 1) could remain a bottleneck, especially with the onset of bandwidth intensive applications like HD and 3D video. Such links are usually over a long distance and network providers face many difficulties in installing and maintaining the underground fibre-optic cables like OC-1/3. In many cases, long-distance radio links such as T1/E1 may be used. It has also been experimentally determined that congestion bottlenecks mostly exist in the Internet edge networks [9].  
This adversely affects an operator's ability to provide services to rural and suburban users. Also, the return-on-investment is less for network operators due to low and unpredictable subscriber density (increasing urbanization). This situation is clearly noticeable in the developing countries where high-speed broadband is mostly restricted to urban areas. Mobile operators have been largely hit by backhaul congestion problems, and future ISPs will not be exempt.  
Figure 1: Existence of an edge network bottleneck.  
In VoD using unicast, a congestion control mechanism can be used without degrading the performance to the end-users (_i.e._, smoothly responsive DCCP or even aggressive TCP) by large data buffering. By contrast, multicast congestion control remains an open issue and therefore QoE degradation in live channels will become a grave concern for IPTV service providers where such channels anticipate a large number of concurrent participants. Current IPTV networks have, to a large extent, national coverage and mostly watched during the peak hours of 17:00 to 22:00. As a result, ISPs may look into prioritising all or a set of multicast channels using QoS mechanisms like Differentiated Services (DiffServ) [10].  
In networks where such QoS is provided, premium service bandwidth is a scarce resource from the network operator's point-of-view and expensive service from user's point-of-view. This is because strict admission control is applied and the network may be over-provisioned. With the edge network bottlenecks, ISPs may not be able to simultaneously guarantee bandwidth throughout the network to satisfy all of its live channels or subscriber will not be able to afford for such premium channels (if over-provisioned). This may also result in IPTV providers limiting the number of available channels.  
Therefore, network providers need to look at solutions to tackle this problem by managing bandwidth effectively at edge networks. _ProxyTV_ approach is considered as a solution for the problem in future managed IPTV delivery over the public Internet in oppose to current over-provisioned walled-garden IPTV networks.
# Mechanical and Dielectric Properties of Aligned Electrospun Fibers
## 1 Introduction
### Applications of Electrospun Fibers  
The typical applications of electrospun fibers include filtration, energy, structures, biomedical, textiles, and others [6] as shown in Figure 4. Other applications include optical and chemical sensors, textiles, reinforcement of composites, health care, and defense and security. Electrospun fibers are projected to play an important role in the development of air filtration, energy storage devices, super-capacitors, and rechargeable batteries [20; 21; 22; 23; 24; 25; 26].  
The applications of nanofiber mats in the reinforcement of nanocomposites are discussed by [PERSON] et al. (2003), who executed mechanical characterization of nanofibrous membranes of various polymers and examined their potential applications [17]. Nanofibers can have better mechanical properties than microfibers and therefore superior structural properties can be anticipated. [PERSON] et al. (2018) provided an overview of nanofiber composite application [27]. [PERSON] and [PERSON] (1999) showed that smooth nylon-4, six electrospun fibers with diameters in the range of 30-200 nm can be produced from formic acid solutions. These fibers demonstrated reinforcement of transparent composites with an epoxy matrix [28]. Highly porous nanofibers with pore interconnectivity and relatively uniform pore distributions improve membrane performance in the application of desalination (water filtration) [29]. The large surface area of the constituent fibers provides high functionalization capability and mechanical bonding to limit delamination between laminae [30]. Biomedical applications include tissue engineering scaffolds, wound dressing,  
Figure 4: Applications of electrospun nanofibers.  
Figure 3: Working principle of electrospinning.  
drug delivery [31], and creation of artificial blood vessels. The non-woven nanofibrous mats produced by electrospinningning techniques mimic the extracellular matrix components.  
Some important issues and challenges in the 21 st century are addressed by using electrospun fibers in the domains of tissue regeneration, energy conversion and storage, and water treatment. Large surface areas, high porosity, and the unique mat structure of electrospun nanofibers have provided improvements over the last decade in the fields of tissue regeneration (skin [32; 33; 34], nerve [35; 36; 37], heart [38; 39; 40], and bone [41; 42; 43]), energy conversion and storage (solar cells [44; 45; 46; 47], fuel cells [48; 49; 50; 51], and batteries [52; 53; 54; 55]), and water treatment (adsorption [56; 57; 58], photocatalysis [59; 60; 61], and filtration [62; 63; 64]). Potential applications and promising advantages are overviewed by [PERSON] and [PERSON] (2010), who highlighted more than 200 polymers that are electrospun for various applications. [PERSON] and [PERSON] (2006) gave a detailed review on electrospinning design and nanofiber assemblies [65].
# Nonvolatile Organic Floating-Gate Memory Using N2200 as Charge-Trapping Layer
## 3 Results and Discussion
### Storage Characteristics
When the temperature is 40 \({}^{\circ}\)C, the memory window of the device is largest, reaching 32.7 V. With the increase in temperature, the memory window of the device gradually decreases, and when the temperature is \(\geq\)80 \({}^{\circ}\)C, the transfer characteristic curve of the device no longer changes. Through these temperature stability tests, the memory performance of the device in different temperature environments can be better understood, and some references for subsequent temperature effects on device performance can be provided. Table 2 summarizes the memory windows and P/E voltages of FG-OFETM with different FG layer and tunneling layer materials in the recent literature. The comparison results show that the N2200 FG-OFETM presented in this work has a relatively low P/E voltage and large memory window (\(V_{\text{P/E}}=\pm 45\) V, 5 s; memory window is 16.1 V). \begin{table}
\begin{tabular}{c c c c c} \hline
**FG Layer** & **Tunneling Layer** & \(V_{\text{P/P}}\)**(V)** & **Memory Window (V)** & **Reference** \\ \hline Gold nanoparticles & PMMA & \(+80/-150\) & 43 & [45] \\ Single-walled carbon nanotubes & PMMA & \(+60/-60\) & 26.7 & [29] \\ Polysilicon & PMMA & \(+60/-60\) & 9.28 & [46] \\ F8 BT & PMMA & \(+40/-40\) & 9.28 & [28] \\ C\({}_{60}\) & TTC & \(+40/-40\) & 8.0 & [47] \\ N2200 & PMMA & \(+45/-45\) & 16.1 & This work \\ \hline \end{tabular}
\end{table} 
Table 2: Comparison of FG-OFETM performance of different FG layer materials. Figure 5: Changes in the test transfer characteristic curve at different temperatures. (**a**) Programming; (**b**) erasing. For P-type OFETM, under a certain \(V_{\rm{DS}}\), when \(V_{\rm{GS}}\) is less than \(V_{\rm{TH}}\), \(I_{\rm{DS}}\) is almost zero and the transistor is in the off state (\(I_{\rm{OFF}}\)). When the negative \(V_{\rm{GS}}\) exceeds \(V_{\rm{TH}}\), a conductive channel is induced in the active layer, \(I_{\rm{DS}}\) increases rapidly, and the device is in the on state (\(I_{\rm{ON}}\)). P/E operation causes \(V_{\rm{TH}}\) drift, and at the same \(V_{\rm{GS}}\) and \(V_{\rm{DS}}\), the \(I_{\rm{DS}}\) may exhibit differences in order of magnitude. Based on the above-mentioned characteristics, the \(I_{\rm{DS}}\) of N2200 FG-OFETM with programming-read-erasing-read (PRER) cycles is investigated. The corresponding voltages are \(V_{\rm{P}}=-45\) V, read voltage (\(V_{\rm{R}}\)) = \(-20\) V, \(V_{\rm{E}}\) = 45 V, and \(V_{\rm{R}}=-20\) V at a time step of 5 s. After 200 PRER cycles, the memory characteristics of the device did not change significantly, indicating that N2200 FG-OFETM exhibits exceptional erasing endurance, as shown in Figure 6a. Figure 6b displays the retention characteristics of N2200 FG-OFETM. After a P/E voltage of \(\pm 45\) V, 5 s, is applied to the device, the read current on/off ratio reaches \(10^{3}\).
## 2 Materials and Methods
### Photocatalytic Experiment  
The MB solution was prepared using milli-Q water. The initial concentration was 5 mg/L. In total, 30 mL of the prepared MB solution was added to a quartz reactor with immobilised glass substrates. The adsorption-desorption equilibrium was conducted in the dark for 1 h. Then, the irradiation was turned on and aliquots (220 \(\upmu\)L) were collected in intervals of 30 min and the absorbance was monitored by UV-Vis spectroscopy on a Lambda 950 UV/VIS/NIR spectrophotometer (PerkinElmer, Waltham, MA, USA) in the 400-700 nm range using quartz cuvette (Hellma Analytics, Stuttgart, Germany) with a path length of 10 mm. The photocatalytic activity was investigated under ultraviolet A (UV-A) lamp (Supratec 18W/73, Osram) with a specified wavelength between 300 and 400 nm and a simulated solar lamp (Osram Ultra Vitalux 300W). The solution was stirred continuously with magnetic stirrer at 350 rpm for better homogenisation at a 15 cm distance from the light source.  
To determine the influence of possible catalytic species on the degradation process, different scavengers were utilised: 10 mol L\({}^{-1}\) of EDTA-2 Na, silver nitrate (AgNO\({}_{3}\)), and isopropanol (IPA) was added to the MB solution to catch hydroxyl radical hole (h\({}^{+}\)), electron (e\({}^{-}\)), and (\({}^{\bullet}\)OH), respectively [33; 34].  
To better simulate realistic conditions for possible water remediation, we also investigated the process in different water environments which were collected from river, lake, and sea. River water was collected at the source of the Soca river. Lake water was taken from Bled and seawater was collected on the coast near the city of Piran.  
The ability to reuse the glass functionalised with nanocomposite for removal of MB from the aqueous medium was evaluated after five consecutive cycles. After each performed photocatalytic test, the immobilised rGO/TiO\({}_{2}\) nanocomposite was washed with absolute ethanol and milli-Q water and then dried at room temperature over the night.
# Query-Based Cascade Instance Segmentation Network for Remote Sensing Image Processing
## 2 Methods  
### Overview  
Figure 2 provides an overview of the QCIS-Net framework. The EFE module can combine the global information-building module capability of Transformer to solve the long-term dependence problem in visual space. The MSCT head uses the dynamic convolution kernel and cascade structure to allow the detection and segmentation tasks to take advantage of each other. The elaborated joint loss function can guide QCIS-Net for training and generating the final instance mask.
# A Novel Self-Forming Virtual Sub-Nets Based Cross-Layer MAC Protocol for Multihop Tactical Network
## 4 Working of Algorithm
On completion of the control frames transmission, all SDRs built the same TRANS_table using Algorithm 1, which runs on each network node and forms virtual sub-nets based on the transmission information in the table. For sub-nets formation, Algorithm 1 (line no. 17 to 23) matches each transmission with every other transmission of the table. If a TX of any transmission matches with the TX or RX of any other transmission, then the TXs and RXs of both transmissions belong to the same sub-net. If no match is found, then the TX and RX of transmission \(i\) are the only members of the sub-net \(S_{v}\). For the above topology, two sub-nets are formed, \(S_{1}=\{1,2,3,7,9\}\) and \(S_{2}=\{4,5,6\}\), as shown in Figure 12, which also shows the roles of each node played for the transmissions. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Control Frame 01**} \\ \hline
**Slot no** & 1 & 2 & 3 & 4 & 5 \\ \hline \multirow{2}{*}{**Packet**} & REQ for 7 & REQ for 9 & combined_REQ & REQ for & REQ for \\  & via 3 & via 3 & for 7,9 and 2 & 5 via 6 & 6 \\ \hline \multirow{2}{*}{**Slot no**} & 6 & 7 & & 8 to 10 & \\ \hline \multirow{2}{*}{**Packet**} & Relay REQ & ACK to & & & \\  & of 4 for 5 & REQ of 3 & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: First control frame contains transmissions of all software-defined radios (SDRs). \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Control Frame 02**} \\ \hline
**Slot no** & 1 & 2 & 3 & 4 & 5 \\ \hline \multirow{2}{*}{**Packet**} & Relay REQ & ACK to & ACK to & \multirow{2}{*}{BRDCST} & ACK to \\  & of 2 for 9 & REQ of 3 & & REQ of 1 & REQ of 6 \\ \hline \multirow{2}{*}{**Slot no**} & 6 & 7 & 8 & 9 & 10 \\ \hline \multirow{2}{*}{**Packet**} & combined\_ACK & & & & \\  & to 4 and 5 & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Second control frame contains transmissions of all SDR. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Control Frame 03**} \\ \hline
**Slot no** & 1 & 2 & 3 & 4 to 10 \\ \hline \multirow{2}{*}{**Packet**} & ACK to & BRDCST & ACK to & \multirow{2}{*}{BRDCST} \\  & REQ of 3 & & REQ of 2 & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Third control frame contains transmissions of all SDRs. Figure 12: Sub-nets formation after control frames transmission.
# Investigation of Different Storage Systems for Solar-Driven Organic Rankine Cycle
###### Abstract  
The objective of the present work is the study of different thermal storage systems for a solar-fed organic Rankine cycle (ORC) system that operates with parabolic trough collectors. The conventional design with sensible thermal oil storage is compared with a storage configuration with thermal oil and ceramic rocks, as well as the use of latent storage with phase change materials (PCMs) is investigated. The initial system is studied parametrically, and it is properly designed to order for the cycle to have high performance. Different organic fluids are studied in the organic Rankine cycle and different rocks are investigated as storage materials. Toluene is found to be the best candidate in the cycle and ceramic rocks are found to be the best candidate energetically and financially. The final results proved that both the thermal oil-ceramic rocks and the PCM are better technologies than the simple sensible thermal oil storage. For the design with a 180 m\({}^{2}\) collecting area and 8 m\({}^{3}\) storage tank volume, the thermal oil-ceramic rocks design leads to 13.89% system efficiency and net present value (NPV) to 129.73 k\(\epsilon\), the PCM storage to 13.97% and 128.66 k\(\epsilon\), respectively, while the pure thermal oil case leads to 12.48% and 105.32 k\(\epsilon\), respectively. Moreover, it is useful to state that when the collecting area is varied from 160 m\({}^{2}\) to 200 m\({}^{2}\) with the tank volume at 8 m\({}^{3}\), the efficiency enhancement with ceramic rocks compared to pure oil ranges from 8.99% up to 12.39%, while the enhancement with PCM ranges from 7.96% to 13.26%. For the same conditions, the NPV is improved with ceramic rocks from 18.35% to 25.79%, while with PCM from 14.17% to 25.29%.  
solar concentrating power; parabolic trough collector; phase change materials; ceramic rocks; organic Rankine cycle +
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