esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Simulations
### Channel Performance as a Function of Different Temperatures  
Another environmental parameter whose variations are of great interest for studying on how it affects the capacity of the acoustic channels is the temperature. The temperature fluctuation is simulated between 17-29 \({}^{\circ}\)C. Other parameters were kept fixed are: salinity at 35%, pH = 8, \(\mathrm{w}\) = 5 m/s and frequency 78 kHz. Figure 7 shows the performance of capacity, as obtained from Equation (8), versus temperature where the capacity is an average value for all communications that may have occurred in a network, when temperature varies between 17-29 \({}^{\circ}\)C, with step of 0.5 \({}^{\circ}\)C.  
Capacity increases with the increase of temperature values, because the temperature affects the absorption coefficient by decreasing it. Thereby it helps in reducing the attenuation in the acoustic communication path and consequently by bringing an increase of SNR ratio in the receiver. At higher temperatures, this would increase the capacity of the acoustic communication channel by allowing more data to be transmitted per unit of time. Figure 8 shows the performance of the total delay Equation (22) versus temperature changes.  
Figure 8: Delay versus Temperature.  
Figure 7: Average capacity versus temperature.  
The delay decreases with the increase of temperature values, because it decreases both the transmission delay (the modem takes less time to transmit the packet as the acoustic channel capacity is increased) and the propagation delay (as the temperature increases the acoustic signal spreads faster along the path). Reflections are not taken in consideration during these simulations as those will be estimated in the next section. Figure 9 shows the performance of transmission lifetime as a function of increasing temperature. These metrics are increased with the increase of the temperature values, because it affects the overall capacity of the acoustic channel where more data can be transmitted per unit of time.  
The time needed for the acoustic modem to transmit the packet in this way reduces energy consumption (longer lifetime) and leads to a larger number of packets transmitted.
# A Random Forest-Based Precipitation Detection Algorithm for FY-3C/3D MWTS2 over Oceanic Regions
## 5 Discussion  
The _RF_SI_ method employs multispectral data as inputs to simulate the nonlinear relationships between infrared and visible light data and microwave precipitation scattering. This method offers a new approach for studying the complicated nonlinear problem concerning microwave precipitation scattering. However, its performance exhibits measurable limitations under complex meteorological regimes (e.g., cirrus clouds, multilayer clouds). To address these constraints, future iterations could integrate alternative machine learning methods (e.g., deep learning, CNNs, U-Net) to enhance sub-pixel feature extraction. Due to the lack of window channels in the MWTS2 instrument, the current validation of _RF_SI_ relies on AMSU-A and MWTS3 as alternative test platforms, representing a notable methodological limitation. The future research will focus on integrating _RF_SI_ into WRFDA data assimilation systems to rigorously assess its practical utility. By quantifying improvements in FY-3C/D MWTS2's data assimilation accuracy and numerical weather prediction skill, this approach will enable direct evaluation of _RF_SI_'s operational performance while addressing the instrument's inherent technical constraints. Notably, the algorithm demonstrates marked cross-platform compatibility, with prototype implementations successfully deployed across FY-2F/G/H VISSR and FY-4A/B AGRI sensors, thereby establishing foundational infrastructure for satellite constellation-based precipitation monitoring networks.
## 2 Materials and Methods
### Experimental Protocols and Data Acquisition
Caffeines doses were prepared using stick coffee (Kanu Mini Mild-Roasted Coffee Sticks; Dongsuh Foods Corporation, Incheon, Republic of Korea), containing 33 mg of caffeine per stick. For each trial, three (approximately 100 mg) or six sticks (approximately 200 mg) were dissolved in 200 mL of water. In the first experiment, the participants were randomly assigned to consume either 100 mg or 200 mg of caffeine, and the alternate dose was consumed in the second experiment. Therefore, a single-blind method was used, in which the participants were unaware of the intake amount. Ultrasound images of the CCA were saved in DICOM format and analyzed using DICOM viewer software (Radiant DICOM Viewer Version 2021.2.2 (64-bit), Medixant, Poznan, Poland). The maximum diameter (MaxD) and minimum diameter (MinD) were measured from the B-mode images, while the average peak systolic velocity (PSV) over 5 s was calculated from the Doppler-mode images. HR and SpO\({}_{2}\) values were averaged over 30 s of measurement, and systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded using the smartwatch application. The pulse wave velocity (PWV), a measure of arterial stiffness, was calculated using SBP, DBP, MaxD, and MinD according to Equations (1) and (2). Cognitive performance data, including accuracy rate and response time from the 2B test, were extracted using the DMDX software. \[\text{Stiffness Index }(\text{SI})=\text{ln}\bigg{(}\frac{\text{SBP}}{\text{ DBP}}\bigg{)}\times\bigg{(}\frac{\text{MinD}}{\Delta\text{D}}\bigg{)} \tag{1}\]  
Figure 1: Brightness mode image of CCA measured using ultrasound. where DD = MaxD \(-\) MinD  
\[\text{Pulse Wave Velocity (PWV)}=\sqrt{\frac{\text{SI}\times\text{DBP}}{2\times\text{BD}}} \tag{2}\]  
where blood density (BD) = 1.050 g/cm\({}^{3}\)  
The raw data for BP, diameter, PWV, PSV, HR, SpO\({}_{2}\), accuracy rate, and response time were normalized using Equation (3) to calculate the change rates for statistical analysis. \[\text{Change Rate (CR)}=\frac{\text{Value at 0,30, or 60 min}}{\text{Value at 0 min}} \tag{3}\]
## 3 Results and Discussion
### Prevalence of Coliform and E. coli
coli_ was the most frequently isolated bacterium with 45.4% contamination rate among all tested samples collected from pig slaughterhouse in South Africa [23]. The current study revealed a higher level of contamination in comparison with the study conducted in Ethiopia by [PERSON], [PERSON], [PERSON], and [PERSON] (2014) [26] who found that the prevalence of _E. coli_ in meat samples collected from abattoirs at 15.89%. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**No. **} & \multirow{2}{*}{**Enterobacteriaceae**} & \multicolumn{3}{c}{**Camels**} & \multicolumn{3}{c}{**Catel**} & \multicolumn{3}{c}{**Sheep**} \\ \cline{3-8}  & & **Slaughterhouses** & **Butcher Shops** & **Slaughterhouses** & **Butcher** & **Slaughterhouses** & **Butcher** & **Total \({}^{*}\)** \\  & & **(\%)** & **(\%)** & **(\%)** & **Shops (\%)** & **(\%)** & **(\%)** & **Shops (\%)** & **(\%)** \\ \hline
1 & _Escherichia coli_ & 20 (100) & 14 (70) & 17 (85) & 12 (60) & 6 (30) & 15 (75) & 84 (70) \\
2 & _Salamuela Paratyph A_ & 4 (20) & 11 (55) & 9 (45) & 10 (50) & 5 (25) & 8 (40) & 47 (39) \\
3 & _Salamuela arzione_ & - & 1 (5) & - & - & - & - & 1 (0.8) \\
4 & _Proteins maribilis_ & 4 (20) & 3 (15) & 3 (10) & 1 (5) & - & 3 (15) & 14 (12) \\
5 & _Proteins vulgaris_ & 1 (5) & - & - & - & - & 1 (5) & 1 (0.8) \\
6 & _Citrobacter treadmill_ & - & 1 (5) & 1 (5) & - & - & 3 (15) & 5 (4.1) \\
7 & _Citrobacter youngae_ & - & - & 1 (5) & - & 2 (10) & - & 3 (2.5) \\
8 & _Raukleit ennihrodididi_ & - & 1 (5) & 1 (5) & - & 1 (5) & - & 3 (2.5) \\
9 & _Raukleit terrigena_ & - & - & - & - & 1 (5) & - & 1 (0.8) \\
10 & _Seratia diorifera_ & - & 1 (5) & - & 1 (5) & - & 1 (5) & 3 (2.5) \\
11 & _Serentia liaughterica_ & - & - & 1 (5) & - & - & - & 1 (0.8) \\
12 & _Ledricia alexterhydate_ & - & 1 (5) & - & 2 (10) & - & - & 3 (2.5) \\
13 & _Entroberuclear claace_ & - & 1 (5) & - & - & 1 (5) & - & 2 (1.6) \\
14 & _Kle
## 3 Results and Discussion
### The Effects of Helix Angle on Scaffling Load Capacity  
#### 3.3.1 Gearsets Geometry Parameters Planning  
Previous research has investigated the influence of varying the module and pressure angle on flash temperature, load distribution, contact ratio, and specific sliding of the tooth surface. These investigations were conducted under conditions of a fixed center distance and gear ratio. The subsequent phase of the investigation will entail an examination of the impact of the helix angle on the aforementioned meshing performance. Accordingly, five sets of gear pair parameters were designed and are presented in Table 10. Each gearset is composed of 26 and 75 teeth, a pressure angle of 19.5\({}^{\circ}\), and a normal module of 1.62 mm. The helix angles for the five sets were designed to be 10\({}^{\circ}\), 15\({}^{\circ}\), 20\({}^{\circ}\), 25\({}^{\circ}\), and 30\({}^{\circ}\), respectively, with all pinions being right-handed. The corresponding center distances are calculated as 83 mm, 85 mm, 87 mm, 90.2 mm, and 94.4 mm, respectively. In designing the profile shift coefficient, addendum coefficient, and dedendum coefficient, the fundamental objective is to achieve balance in the specific sliding of the pinion and wheel.
## 3 MALDI Non-Imaging MS Analysis of GSLs
### The Influence of Matrices Used in MALDI Non-Imaging MS Analysis of GSLs
The THAP and DHB matrices produced Gb4 Cer spectra of excellent quality. Nevertheless, employing the ATT matrix and introducing sodium chloride into the sample proved to be the most optimal approach for effectively characterizing the Gb4 Cer content in the kidneys of the ADPKD rat model [126]. As chemical noise develops when background ions are formed, various matrices were employed to identify the optimal variant in terms of the signal acquisition and with the minimal background noise. Zarei et al. [117] discovered that the highest signal intensity and S/N ratio for the expected mono-, di-, and trisialylated ion species of mouse brain gangliosides were achieved when employing THAP/DAC and ATT/DAC matrices. DHB and ATT matrices notably and effectively mitigated sialic acid loss. CHCA necessitated maximal laser attenuation (minimal fluence) to achieve partially sialylated ganglioside peaks. In the positive ion mode, all peaks manifested as ions substituted with Na\({}^{+}\) or K\({}^{+}\), whereas in the negative ion mode spectra, only [M \(-\) H]\({}^{-}\) ions were observed [131].
## 2 Materials and Methods
### Word Embedding  
An embedding process is required to convert natural languages into machine-readable languages. In other words, this process presents the results of changing natural languages to vectors, in the form of numbers that machines can understand, or a series of these processes. FastTextis an embedding method that is an enhanced version of the Word2 Vec [34] model and an example of the distribution hypothesis. The distribution hypothesis assumes that the distribution of each word differed depending on its location in a sentence and the other words that appeared around it. It assumes that a pair of certain words might have similar meanings if they appeared in sentences that had similar meanings. FastText represents each word based on an \(n\)-gram, the unit of a word. The term \"\(n\)-gram\" refers to a sequence of \(n\) word(s). In other words, a certain word is divided based on \(n\). For example, when the word \"teach\" is divided based on an \(n\)-gram (\(n=3\)), it could be expressed as [te, tea, eac, ach, ch], and [teach]. FastText uses the symbols \"[\" and \"]\" to indicate the boundaries of a word, including its beginning and end. Consequently, the sum of the vectors divided based on the unit of \(n\)-gram is adopted to represent an embedding of the term \"teach\". FastText uses a skip-gram model to train a pair of target words and context words. If the context word was located near the target word, then this model increased the dot product of the vectors of both words to increase the cosine similarity and correlation between both words. If the context word was not located near the target word, then this model reduced the dot product of the vectors of both words to decrease the cosine similarity. Via this process, the distribution information, which was the peripheral context of the target word, was included in the embedding. The \"[te, tea, eac, ach, ch]\" vector, which was obtained via the representation of the word \"teach\", based on the unit of \(n\)-gram, underwent embedding. Accordingly, if the word \"teacher\" did not exist in a dataset, FastText could infer that these words were similar to each other because both words had the same \(n\)-gram vectors and the context word \"study\" was located nearby. This method was advantageous because it could respond flexibly to changes in verbs or nouns, and it performed well when dealing with spacing, spelling, and out-of-vocabulary words. It was especially effective in the Korean language, which had a wide range of postpositions and endings [35].
# Evolution of Water-in-Oil Droplets in T-Junction Microchannel by Micro-PIV
###### Abstract  
Water-in-oil droplets have huge importance in chemical and biotechnology applications, despite their difficulty being produced in microfluidics. Moreover, existing studies focus more on the different shape of microchannels instead of their size, which is one of the critical factors that can influence flow characteristics of the droplets. Therefore, the present work aims to study the behaviours of water-in-oil droplets at the interfacial surface in an offset T-junction microchannel, having different radiuses, using micro-PIV software. Food-grade palm olein and distilled water seeded with polystyrene microspheres particles were used as working fluids, and their captured images showing their generated droplets' behaviours focused on the junction of the respective microfluidic channel, i.e., radiuses of 400 \(\upmu\)m, 500 \(\upmu\)m, 750 \(\upmu\)m and 1000 \(\upmu\)m, were analysed via PIVlab. The increasing in the radius of the offset T-junction microchannel leads to the increase in the cross-sectional area and the decrease in the distilled water phase's velocity. The experimental velocity of the water droplet is in agreement with theoretical values, having a minimal difference as low as 0.004 mm/s for the case of the microchannel with a radius of 750 \(\upmu\)m. In summary, a small increase in the channel's size yields a significant increase in the overall flow of a liquid.  
microfluidics; droplets; microchannel; flow characteristics; micro-PIV +
Footnote †: journal: Applied Sciences
# Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser
## 3 Proposed Fog-Based CDN Framework
### Fog-Based CDN Framework Components
#### 3.1.3 Event Channel  
The cloud providers need to provide at least one communication channel for all the fog nodes. This communication channel is built using the pub/sub messaging protocol, where different nodes can subscribe to services and the cloud providers can publish updates on specific topics. The cloud providers can provide more event channels for load balancing purposes or more latency optimization if they are geographically distributed.
# Enhancing Impact Localization from Fluid-Pipe Coupled Vibration under Noisy Environment
## 2 Materials and Methods
### Noise Features in the CWT  
In practice, noise is inevitable when we take measures. The noises we frequently observe when we measure vibration signals could be grossly classified into three kinds: white Gaussian noise, banded noise, and burst noise. The power of white Gaussian noise and banded noise is distributed in a certain frequency range, in accord with their statistical properties. These kinds of noises are easily discriminated from signals that have resonant characteristics, such as the coupled wave. Figure 4a shows a typical example of a waveform buried by excessive white noise, of which the signal-to-noise ratio (SNR) is \(-30\) dB. The blue line in Figure 4a is the same signal as in Figure 3a, and the black line is the signal added by white noise. As can be seen in Figure 4b, it is not hard to recognize the impact signal around \(0.1\) s in time and \(730\) in scale, in spite of the other peak lines at different times and scales. The banded noises have features similar to those of white noise, except for the band range. Therefore, it is not hard to tell the difference between a coupled wave signal and white noise.  
Burst noise is also prevalently observed in a vibration signal with accompanying white and banded noises. Here, a transient refers to any abrupt change that briefly stays positive or negative. Figure 5a shows an example of a burst noise model following the coupled wave signal. Even though the shape looks quite extreme, substantial burst noise can be generated from minor pressure changes in conjunction with various anomalies, such as irregularity in the pipe and discontinuities. The burst noise has features similar in CWT to the waveform of the coupled wave. In other words, the burst noise has a sharp modulus and temporally local ridges across the scales, like the coupled wave signal in CWT [19]. However, this noise has an obviously distinguishable feature from the coupled wave signal that we are looking for. The abrupt change of burst noise gets larger as the scale increases, but the signal of a coupled wave has a maximum modulus with respect to a certain scale band of the corresponding system, as shown in Figure 5b. It is worth noting that the discrepancy between the signal of interest and burst noise in CWT makes it possible to detect the presence of anomalous impacts that generate waves propagating along the pipeline from lots of background operating noises.  
Figure 4: An impact signal with white noise (SNR: \(-30\) dB) (**a**) and its continuous wavelet transform (**b**); the blue line in (**a**) is the same signal as in Figure 3a.
## 2 Overview of Old BWSCs with a Large Height Difference  
Salt companies mostly adopt directional butted wells for brine extraction and salt production. A directional butted-well system consists of a vertical well and a directional well, with the distance between the two wells typically ranging from 250 to 400 m. Initially, a vertical well is drilled, and a single-well cavity building system is installed. This system is operated for a period to create a small cavity of a specific volume. Then, a directional well is drilled to enter into the small cavity. The production casing is directly lowered into the inclined wellbore section in the salt formation, cemented, and used as the cavity-building pipe. Following this, an alternating water-injection method between the two wells is used to extract brine. As salt production aims to achieve economic viability, the companies typically require that the extracted brine reaches a saturated concentration. Consequently, the water injection displacement is generally at a low level, averaging around 60 m\({}^{3}\)/h, and the production period can last from over a decade to several decades. Additionally, the salt mining companies usually use a solvent-free cavity-dissolution method to control the entire production process based on empirical methods and convert the salt extraction volume accordingly. During this process, the duration of alternating water injection significantly affects the development morphology of the cavities on both sides. On the side with a longer water injection time, the cavity expands more extensively. Due to the absence of solvent at the cavity roof, the dissolution rate of the cavity roof is faster than that of the cavity periphery, causing the salt cavity to continuously dissolve and expand upward. Additionally, on the brine-discharging side, the high brine concentration results in a lower dissolution rate. Ultimately, under this unbalanced brine-extraction method, large-height-difference butted-well salt caverns are formed. The longer the cumulative water injection time on one side, the greater the height difference between the two cavities. A schematic diagram illustrating the formation of a large-height-difference butted-well salt cavity is presented in Figure 3. As shown in Figure 2, the maximum height difference between the cavity roofs on both sides of the measured butted-well salt cavity approaches 200 m, representing a typical cavity with a large height difference.  
Figure 2: Schematic diagram of the large-height-difference butted-well salt cavern in Pingdingshan.
## 1 Introduction
### Objectives and Scope  
The purpose of the current review paper is to organize the literature on terahertz-bandwidth free-space optical communication and to investigate the possibilities regarding its role in the evolution of high-speed communication networks. The key objectives are:  
* To foresee the fundamental and physical aspects of terahertz frequencies;
* To assess the development of enabling technologies that facilitate the development of THz systems, such as THz sources, detectors, and adaptive systems;
* In this paper, some of the issues regarding this technology, such as future research directions, its massive energy consumption, and its susceptibility to abnormal weather conditions, will also be discussed, with a focus on the limitations and challenges, such as atmospheric attenuation and hardware limitations in implementing THz-FSO systems;
* To analyze THz-FSO communication and other systems, comparisons are made here to microwave and optical systems;
* To explore possible use cases that include inter-satellite links, the sixth generation network, and safe communications.  
This review aims to cover the interrelated fields of material chemistry, signal processing, and mixed communication systems. By analyzing more than 100 recently published articles, this paper attempts to present the current state of and findings related to the technological readiness of terahertz-based free-space optical communication and its future outlook.