esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
It allows the user to run that application in a different private or public cloud environment. This allows the user to switch from one cloud provider to another without any difficulty. CaaS is positioned in the middle between Infrastructure as a Service (IaaS) and platform as a service (PaaS) in the hierarchy of cloud computing services. CaaS is considered a subset of Infrastructure as a Service (IaaS). Two popular CaaS orchestration platforms are Google Kubernetes and Docker Swarm. The main objective of task scheduling is to efficiently utilize all the resources and organize all the incoming requests so that all requests complete their execution before the deadline. Multiple tasks may be executed simultaneously in a cloud computing system, and the same resource is allocated to several clients. So, if the system does not use a proper scheduling algorithm, smaller tasks may miss their deadline in the waiting queue for a long time. The main contribution of this paper is as follows:  
Figure 1: Virtualization Technology. (**a**) VM Architecture. (**b**) Container Architecture. * Proposed a Grey Wolf Optimization (GWO) based Simulated Annealing approach to counter the problem of load balancing in the containerized cloud that also considers the deadline miss rate. * The Simulated Annealing algorithm was implemented along with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). * The efficiency of each algorithm has been compared in terms of load variation and makespan. The rest of the paper is organized as follows. Section 2 describes the related work on load balancing and resource allocation in the cloud. In Section 3, we represent different components of CaaS cloud architecture such as container mapper, container scheduler, resource manager, migration manager, etc. We present our proposed system model and algorithms in Section 4. Section 5 represents the experimental analysis and results. Finally, in Section 6, we draw the conclusion with some future directions.
# Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin
## 1 Introduction
Several studies have quantitatively assessed various precipitation products over the MRB [27; 28]. Analysing its potential in water balance assessment has not, however, received much attention. As a trans-boundary river basin, the economies and societies along the Mekong River have different priorities for water resources management. Changing the global climate and the trans-boundary nature of the river adds complexity to water-related issues in the catchment [28; 29; 30; 31]. Therefore, with the aim to further analyze which GPP is the most appropriate for water balance component analysis under the complex features of the MRB, this study: (1) evaluates and compares the performance of four GPPs (CPC, TRMM 3B42, GSMaP_Gauge, CMORPH--from here, the term GPPs only refers to the four selected GPPs) on variant time and spatial scales to characterize the precipitation patterns over the whole MRB; and (2) investigates the water balance components across different regions using these products as inputs for the SWAT model.
# X-ray Spectroscopies of High Energy Density Matter Created with X-ray Free Electron Lasers
## 3 Intensity-Dependent EUV and X-ray Transmission
In the hard X-ray regime, a similar effect was reported in iron [17]. The SACLA XFEL pulse (>7113 eV) was focused to 50 nm to achieve a peak intensity of \(1\times 10^{20}\) W/cm\({}^{2}\) and the increased X-ray transmission beyond the light intensity 10\({}^{18}\) W/cm\({}^{2}\). At this intensity, K-shell photoionization rate can compete with KLL Auger decay rate of mid-Z element. As discussed in the case of SA, the excited states have smaller absorption than the ground states. In contrast, a nonlinear absorber in which the excited state absorption is larger than the ground state can undergo an opposite process, RSA. The first observation of decreasing X-ray transmission was also reported for an aluminum foil [35]. As shown in Figure 3c, tuned at K-L transition (1487 eV), which is below the K-edge of cold aluminum, XFEL transmission decreased in the intensity ranges of 10\({}^{16}\)-10\({}^{17}\) W/cm\({}^{2}\). Here, X-ray photon energy is insufficient for a direct K-shell photoionization and the initial absorption channel of the ground state (K2L8) is L-shell photoionization. Although the ionization rate is small, a significant portion of atoms are excited to the K2L7 state owing to the large number of photons in the FEL pulse. The excited ion will absorb 1487 eV photons effectively via resonant K-L excitation. Intense femtosecond XFEL pulse could deliver the second photon to the excited ion before it decays to the ground state in 40 fs, resulting in decreased transmission at higher intensity. With extensive collisional radiative population kinetic calculations, [PERSON], [PERSON], and [PERSON] further discussed this phenomena in wide ranges of photon energy and intensity [34]. As shown in Figure 3c, at 1487 eV, a transition from RSA to SA is also predicted at higher intensities along with reproducing the experimental observations of RSA. RSA and the transition to SA can also occur at other resonant photon energies (1501 and 1515 eV) for higher charge states (K2L6 and K2L5). To produce multiple L-shell vacancies prior to the resonant excitation, higher XFEL intensities will be required. In the SA experiment for iron, an improvement in the wave front of the transmitted hard X-ray FEL beam was observed [17]. [PERSON] et al., also reported X-ray lasing at 1.5 Angstrom from Cu which was irradiated by intense two-color XFEL pulses [36]. These results give rise to the inference that similar to optical science, the nonlinear responses in short-wavelength regimes possess great potential for photonics applications.
# A New Flexible Method for Solving Multi-Expert Multi-Criterion Decision-Making Problems
###### Abstract
: _The OWA operator is a mapping \(\text{OWA}:\ R^{n}\to R\) with dimension \(n\), which is associated with a weighting vector \(w=\left(w_{1},w_{2},\ldots,w_{n}\right)^{\text{T}}\) and \(\sum_{j=1}^{n}w_{j}=1\), and has the properties_  
\[OWA(a_{1},a_{2},\ldots,a_{n})=\sum_{j=1}^{n}w_{j}b_{j}, \tag{1}\]  
_where \(b_{j}\) is the \(j\)th largest element in the set \(\{a_{1},a_{2},\ldots,a_{n}\}\)._  
The OWGA operator is based on the OWA operator and geometric mean. **Definition 2**[41]. : _The OWGA operator is a mapping \(\text{OWGA}:\ R^{+n}\to R^{+}\) with dimension \(n\), which is associated with a weighting vector \(w=\left(w_{1},w_{2},\ldots,w_{n}\right)^{\text{T}}\) and \(\sum_{j=1}^{n}w_{j}=1\), and has the properties_  
\[\text{OWGA}(a_{1},a_{2},\ldots,a_{n})=\prod_{j=1}^{n}b_{j}^{w_{j}} \tag{2}\]  
_where \(b_{j}\) is the \(j\)th largest element in the \(\{a_{1},a_{2},\ldots,a_{n}\}\) set._  
For managing linguistic information, [PERSON] [42] proposed the LOWGA operator to extend the concept of the OWGA operator to a linguistic environment. It can be explained as follows. **Definition 3**[43]. : _The LOWGA operator is a mapping \(\text{LOWGA}:\ \overline{S}^{n}\rightarrow\overline{S}\) with dimension \(n\), which is associated with a weighting vector \(w=\left(w_{1},w_{2},\ldots,w_{n}\right)^{\text{T}}\) and \(\sum_{j=1}^{n}w_{j}=1\), and which has the properties:_  
\[\text{LOWGA}_{w}(s_{a_{1}},s_{a_{2}},\ldots,s_{a_{n}})=\left(s_{ \beta_{1}}\right)^{w_{1}}\otimes\left(s_{\beta_{2}}\right)^{w_{2}}\otimes \ldots\otimes\left(s_{\beta_{n}}\right)^{w_{n}}\] \[=\left(s_{\beta_{1}^{n}1}\right)\otimes\left(s_{\beta_{2}^{w_{2}} }\right)\otimes\ldots\left(s_{\beta_{n}^{w_{n}}}\right)=s_{\beta} \tag{3}\]  
_where \(\otimes\) expressed the product symbol for numbers, \(\beta=\prod\limits_{j=1}^{n}b_{j}^{w_{j}}\), and \(s_{\beta_{j}}\) is the \(j\)th largest element in the set \(\left\{s_{a_{1}},\ s_{a_{2}},\ldots,s_{a_{n}}\right\}\)._  
Extending the concept of the LOWGA operator, [PERSON] et al. [43] proposed the induced LOWGA operator (ILOWGA), and considered both the weights related to the weight of the attributes and that of the operators synchronously. **Definition 4**[44]. : _An induced LOWGA operator can be explained as follows._  
\[\text{ILOWGA}_{\overline{w},w}(s_{a_{1}},s_{a_{2}},\ldots,s_{a_{n}})=\left(s_{ \beta_{1}}\right)^{w_{1}}\otimes\left(s_{\beta_{2}}\right)^{w_{2}}\otimes \ldots\otimes\left(s_{\beta_{n}}\right)^{w_{n}}=s_{\beta} \tag{4}\]  
_where \(\overline{w}=\left(\overline{w}_{1},\overline{w}_{2},\ldots,\overline{w}_{n} \right)^{\
# Real-Time Guitar Amplifier Emulation with Deep Learning +
## 2 WaveNet-Style Model
### Convolutional Layer  
The convolutional layer used in the model is shown in Figure 2. The input signal is first processed by the dilated causal FIR filter \(H_{k}(z^{d_{k}})\), where \(k\) is the layer index and \(d_{k}\) is the integer-valued _dilation factor_ of the filter. Since the convolutional layers generally have multiple channels, the filtering is performed as a multiple-input and multiple-output (MIMO) convolution with a kernel \(H_{k}\). This means that a filter is learned for each pair of input and output channels. The individual filters in the kernel have impulse responses  
\[h[n]=\sum_{m=0}^{M-1}w_{m}\delta[n-md_{k}], \tag{1}\]  
where \(\delta[n]\) is the Kronecker delta function, and \(w_{m}\) are the non-zero coefficients of the filters learned by the network. Next, a nonlinear activation function \(f(\cdot)\) is applied to the biased convolution output, producing the layer output  
\[z_{k}[n]=f[(H_{k}*x_{k})[n]+b_{k}], \tag{2}\]  
where \(*\) denotes the convolution operator, and \(b_{k}\) is the learned bias term. The layers include a residual connection, which means that the input to the next layer is  
\[x_{k+1}[n]=W_{k}z_{k}[n]+x_{k}[n], \tag{3}\]  
where the \(1\,\times\,1\) convolution kernel \(W_{k}\) controls the mixing between the layer input \(x_{k}\) and the layer output \(z_{k}\) before the next layer.  
Each convolutional layer can be viewed as a Wiener model: a linear filter followed by a static nonlinearity. In previously proposed black-box and grey-box models of musical distortion circuits it has often been assumed that the device can be approximated by a Wiener model [8; 11], a Hammerstein model [9] or a Wiener-Hammerstein [10; 12] model. As a cascade of Wiener models, the WaveNet-style neural network makes fewer assumptions about the design of the modelled device, and so should be  
Figure 1: Proposed WaveNet-style neural network model.  
applicable to the modelling of a broad range of nonlinear systems. Furthermore, the deep learning approach optimizes the system response jointly, and not block-by-block, so not only the model but also the optimization makes fewer assumptions about the behavior of the device under study.
# Autonomous Wireless Sensor Networks in
## 1 Introduciton
Cloud cover and precipitation can significantly affect the availability in the SatCom link. The attenuation of the uplink and downlink signals due to rain depend on the precipitation rate as well as the droplet size relative to the frequency of the satellite communication band, with the degradation increasing with frequency. The principal effect behind this is the attenuation of electromagnetic radiation passing through a liquid water medium. The highest attenuation occurs at the Ku-band (downlink frequency 12 GHz) which corresponds to the wavelength of 25 mm, while the lowest attenuation occurs for the C-band frequency (downlink 4 GHz) with the wavelength of 75 mm [3]. The closer the wavelength is to the diameter of the raindrop, which averages around 5 mm, the higher the attenuation of the incoming electromagnetic radiation. With 10/10 cloud cover and precipitation present, the SatCom link will be unavailable. On the other hand, the terrestrial link, while also experiencing attenuation, does so in a lesser manner with GSM frequency bands spanning from 380-900 MHz [4]. To secure reliable data feeding into IPM spatial decision support systems we have developed the PentaSense WSN framework, which, coupled with EO at different spatial scales feeds into numerical models. The gateway is constructed with a dual-uplink module integrating both terrestrial and satellite communication. This creates the possibility to implement a back-up system where both options are available to increase reliability further and minimize operating costs. Moreover, embedded energy scavenging techniques can ensure long battery life. The aim of this research is not to replace the terrestrial communication strategy but to provide a dual mode on the gateway to accommodate the highest degree of technological flexibility, especially for implementations that need to be accommodating to different pest environments worldwide. This will allow the smart traps and sensors to operate even when the terrestrial systems are or become unavailable. Adding satellite communications on the gateway also allows for easier system deployment. Where using local 2G/3G/4G networks requires contracts with local providers which need to be closed in each country of operation, satellite communication allows operating everywhere on the globe under the same contract and provider. This can be a very useful feature for prospecting operations and pilot studies. Hence, in the PentaSense system the satellite communication is used a second communication link ensuring reliable, uninterrupted data transfer and redundancy for IPM applications. The dual-uplink can provide safe, cost-effective and secure communication even in areas where existing connections are overloaded, destroyed or not present. Moreover, this setup can provide a reliable transfer of payload meteorological data to the remote server in NRT regardless of the deployment location of the WSN.
## 4 Discussion
The half-life of peroxnitrite is about two seconds; hence, it is likely absent in the PTS, leading to less MDA formation. At the same time, PTS induced a more considerable decline in metabolic activity than the direct plasma treatment. This might be due to the reactive species being degraded by the blood's antioxidant during the direct treatment, ultimately leading to a lower overall concentration of plasma-derived oxidants, such as hydrogen peroxide that was shown to be toxic to white blood cells [53]. In the case of PTS, a higher concentration accumulates in the plasma-treated solution, which is then added to the blood cells at once, exposing a fraction of blood cells to that higher concentration during the mixing, and subsequently inducing more significant toxicity. The fact that not directly plasma-treated healthy leukocytes but CLL-derived leukocytes showed a decline in metabolic activity nevertheless suggests a particular specificity of the exposure-induced toxicity. This was also the case with PTS. Nevertheless, it should be mentioned that the PTS is radically different from the direct treatment in terms of reactive species generation and treatment application. In the PTS approach, a higher concentration of the long-lived oxidant hydrogen peroxide is added, but then quickly diluted in the matrix, leading to potentially different results than the direct treatment where more short-lived species are being deposited to the sample [54]. This study had several limitations. First, a preliminary plasma treatment time dose-escalation based on toxicity was not performed, ultimately leading to a modest decline in the blood cells' metabolic activity. However, at 120 s, the direct plasma treatment was already relatively long. Hence, the current plasma-jet-based treatment scheme might be unsuitable for therapeutic action in the blood due to practical treatment time constraints. However, the current study served as a proof-of-concept trial, rather than as a therapeutic attempt. Moreover, the current study lacks single-cell analysis data done via, e.g., flow cytometry with fluorescently conjugated antibodies staining individual cell populations to demonstrate that the decline in metabolic activity and, therefore, likely cell death induction was present in the leukemia cell population specifically. In addition, measuring reactive species concentrations immediately after exposure to plasma or PTS, as well as testing liquids with equivalent ROS/RNS concentrations, would have been desirable, but was not possible in our study. Moreover, the possibility of endogenous ROS/RNS production, as known for phagocytes generating, for instance, superoxide and/or nitric oxide after activation after direct gas plasma or PTS exposure was not explored.
## 4 Performance Comparison
### Signaling Cost
#### Signaling cost for hybrid NeMO operation  
Equation (3) describes the signaling cost for the hybrid NeMO operation, while Table 6 shows the parameter setup.  
\[\begin{split}\text{SC}_{\text{hybrid}}=\text{C}_{\text{prodAR}}+ \text{C}_{\text{accessrouter}}+\text{C}_{\text{consumerAR}}+\text{C}_{\text{ prodAR}}\\ =\text{S}_{\text{mobilityInterest}}\times(\text{a}+\text{c})+ \text{S}_{\text{Interest}}\times(\text{a}+\text{c})\end{split} \tag{3}\]  
Figure 8: Network topology setup for KITE, the PMSS, and hybrid NeMO.
## 2 Materials and Methods
### Analysis of Antioxidants from Leaves of Pepper Plants Grown on the Compostis  
To determine DPPH radical scavenging activity, 1 g of dried pepper leaves and fruits was used to extract and prepare a sample solution for the antioxidant test. The assay of 1,1-diphenyl 2-picryl-hydrazyl (DPPH) radical scavenging activity was performed following the methods in a previous report [34]. Briefly, 1 mL of ethanol extract and 5 mL of a freshly prepared DPPH ethanol solution (0.1 mM) were mixed thoroughly and kept in the dark. After 30 min of incubation at ambient temperature, the absorbance was read against a blank at 517 nm by using a UV-visible spectrophotometer (Model POP, Optizen, Inc., Seoul, Korea). The percentage of free radical scavenging activity was calculated as follows: scavenging activity (%) = (1 - (A517 nm of sample/A517 nm of blank)) \(\times\) 100.  
The total phenolic content as an antioxidant material was determined by the Folin-Ciocalteu method using gallic acid as the standard following the methods in a previous report [34]. The extract was prepared from 1 g of dried and macerated leaf or fruit with the incubation time of 24 h and filtered. The ethanol extract solution was shaken for 1 min with 0.4 mL of Folin-Ciocalteu reagent (1 M) and mixed with 0.8 mL of Na\({}_{2}\) CO\({}_{3}\) (20%, _w_/_v_). After 8 min of incubation, the mixture was centrifuged at 15,000\(\times\)\(g\) for 10 min. The absorbance of the supernatant was measured at 730 nm using a spectrophotometer. The results are expressed as milligrams of gallic acid equivalent per gram of extract (mg GAE/g) based on the standard curve for gallic acid concentration versus absorbance (R = 0.873) [34].  
The total flavonoid content was determined following the method of [PERSON] et al. (2008) [35]. In a 10 mL test tube, 0.3 mL of extract, 3.4 mL of 30% methanol, 0.15 mL of NaNO\({}_{2}\) (0.5 M), and 0.15 mL of AlCl\({}_{3}\) 6H\({}_{2}\)O (0.3 M) were mixed. After 5 min, 1 mL of NaOH (1 M) was added. The solution was mixed well, and the absorbance was measured against the reagent blank at 506 nm. The standard curve for total flavonoids was obtained using rutin standard solution (0 to 100 mg/L) under the same procedure described earlier. The total flavonoids were expressed as milligrams of rutin equivalents per gram of dried fraction.  
For TEAC analysis, the ABTS reagent was prepared by mixing equal amounts of aqueous 7.4 mM ABTS and 2.6 mM potassium persulfate solutions, which were allowed to react overnight in the dark [36]. Trolox standard solution was prepared, and absorbance was recorded on the UV-visible spectrophotometer (Model POP, Optizen Inc., Seoul, Korea) at 730 nm.
## 2 Materials and Methods
### Reactive Oxygen Species (ROS) Production  
SiHa or HeLa cells were seeded at 8000 cells per well in dark 96-well plates and incubated under standard conditions for 24 h. The next day, the medium was changed with 100 \(\upmu\)L of [PERSON] balanced salt solution (HBSS) (0.137 M NaCl, 5.4 mM KCl, 0.25 mM Na\({}_{2}\)HPO\({}_{4}\), 0.1 g glucose, 0.44 mM KH\({}_{2}\)PO\({}_{4}\), 1.3 mM CaCl\({}_{2}\), 1.0 mM MgSO\({}_{4}\), 4.2 mM NaHCO\({}_{3}\)). Cells were incubated for 1 h. The solution was subsequently aspirated, and 100 \(\upmu\)L of HBSS with 5 \(\upmu\)M concentration of general oxidative stress indicator 5-(and-6)-chloromethyl-2',7'-dichlorohydrofluorescein diacetate, acetyl ester (CM-H\({}_{2}\)DCFDA; Invitrogen, Carlsbad, California, USA) was added. After 30 min the cells were washed twice and treated with 10 \(\upmu\)M ferrocenes or 50 \(\upmu\)M H\({}_{2}\)O\({}_{2}\), serving as a positive control, or 10 mM N-acetylcysteine (NAC), serving as a negative control. ROS production was measured after 2, 4, and 6 h.
# Limitations on the Use of Recycled Asphalt Pavement in Structural Concrete
## 4 Mechanical Behaviour of Concrete Containing RAP
### Modulus of Elasticity and Splitting Tensile Strength  
The percentage of substitution of natural aggregates by RAP aggregate also influences the modulus of elasticity: by increasing the percentage of substitution, the modulus of elasticity decreases. The variations of w/c ratios are limited by the fact that the modulus of elasticity is sensitive to the increase in the w/c ratio [3]. The higher the RAP replacement, the lower the Young's modulus. However, studies demonstrate that by reducing the w/c ratio (from 0.53 to 0.45) [3], it is possible to achieve a similar Young's modulus between concrete, with a 15% substitution of RAP and a reference concrete with no RAP.  
Similarly to the other mechanical parameters, splitting tensile strength was also investigated and it can be demonstrated that an increase in RAP content causes a decrease in splitting tensile strength [11; 16; 23]. The rate of strength reduction in the split tensile strength for RAP mixtures can be significantly lower than that of the compressive strength [11]. After 28 days, the reduction of compressive strength of concrete containing RAP was 58.7% of that of the reference concrete, while the reduction in the split tensile strength was 95.3% [11].