esa-sceva/satcom-chunk-collection huggingface dataset:
# Farm Monitoring System with Drones and Optical Camera Communication
## 2 Related Work  
### Smart Agriculture with Drones  
Recent advancements in drone technology have enabled applications across many industries. In agriculture, drones have significantly improved efficiency and productivity [9]. Their high mobility and ability to collect large amounts of data make them essential tools for monitoring and data collection in farming [10; 11]. Research on the use of drones in agriculture continues to grow [12]. [PERSON] et al. [13] highlighted the innovative role of drones in agriculture. They demonstrated that drones can collect and analyze data with high precision, improving efficiency and productivity. [PERSON] et al. [14] proposed the use of drones for spraying pesticides and fertilizers. They found that drone-based spraying provides more uniform coverage and greater efficiency than traditional methods. [PERSON] et al. [15] studied crop condition monitoring using drones equipped with multi-spectral and temperature sensors. They calculated the Normalized Difference Vegetation Index (NDVI) through field tests. [PERSON] et al. [16] developed a crop management system using real-time drone data, IoT, and cloud computing. This system optimizes irrigation by analyzing sensor data to provide water at the right time and in the required amounts. [PERSON] et al. [17] tackled the problem of limited drone flight time by developing wireless power transfer (WPT) technologies. [PERSON] et al. [18] proposed a routing algorithm for efficient and accurate data collection. This algorithm considers both flight time and speed. [PERSON] et al. [19] created a drone-based system for monitoring large cornfields. Their drones, equipped with high-resolution cameras and sensors, allowed for real-time monitoring and efficient management of the fields. [PERSON] et al. [20] introduced a communication protocol for drones to monitor leaf temperature data using infrared thermometers. Their system combines wireless sensor networks with drones. This setup allows for real-time monitoring of large areas and rapid data collection. Drones in this system extend the communication range of sensor networks and improve crop yield monitoring.
# PFC Inductor Design Considering Suppression of the Negative Effects of Fringing Flux
## 1 Introduction
### Experimental Verification of Fringing Flux Suppression--Delimitation of the Space around Airgap  
After a previous discussion about the possibilities of fringing flux suppression, the experimental verification was realized. As was mentioned, the consequence of fringing flux is the generation of the eddy currents which increases the losses and thus the thermal performance of the coil's winding. The experiments were therefore oriented on evaluation of the thermal performance of the analyzed coil's air gap alternatives, operated under nominal conditions of power factor correction (PFC) converter. The interleaved step-up converter operating as a PFC had an input voltage of 3 \(\times\) 120 V (L-L), an output voltage of 480 V, and an output power of 4 kW. Table 1 lists the main properties of the inductor, while Figure 8 shows practical application within the heatsink of the converter. The figure shows two inductors, while PFC is of the interleaved type. Both alternatives were prepared, i.e., inductor with one air gap located in the center of the core (Figure 4a) and with one centered air gap but excluded (Figure 2).  
\begin{table}
\begin{tabular}{c c} \hline
**Core type** & PQ35/35 \\
**Inductance** & 215 \(\upmu\)H \\
**Max. current** & 11.5 A \\
**Airgap length** & 2.6 mm \\
**Saturation induction** & 330 mT \\
**Nr. of turns** & 42 \\
**Nr. of winding layers** & 4 \\
**Wire** & 2 \(\times\) 20 \(\times\) 0.2 mm litz wire \\ \hline \end{tabular}
\end{table}
Table 1: Main parameters of PFC inductor v1 for the case study of delimitation of the space around airgap.  
Figure 7: Magnetic induction distribution in dependency on the distance from the air gap and the length along the air gap for inductor described by situation Figure 4b.  
Figure 9 shows the temperature distribution results for both investigated alternatives of air gap type. The left side refers to the result for the core with one centered air gap. If temperature field distribution is analyzed, it is seen that the maximum value was located around the space, where the air gap was concentrated, while the value reached 72.7 \({}^{\circ}\)C (temperature of the winding). During infrared measurements, the temperature of the core was also evaluated, while from Figure 9 left is seen that its value approached 54.8 \({}^{\circ}\)C. For the case with excluded space around the air gap, Figure 9 right should be observed. It is apparent that the winding temperature decreased to 68.8 \({}^{\circ}\)C, while the temperature of the core dropped to 40 \({}^{\circ}\)C. Based on these results, it is evident that the effect of air gap modification on the temperature performance was significant while winding temperature dropped by more than 5% and the temperature of the core dropped by 27%. Therefore, the effect of fringing flux was suppressed as well.
## 3 Results
### Residual Trend Analysis of the Vegetation and Its Related Factors  
The mean annual TEM, total annual PRE, and ecosystem indicators were used for residual analysis (RA1). The residual analysis showed that ET, GPP, and LAI responded differently to climate change and human activities, and the relative contributions of climate change and human activities to the changes in the trend of the ecosystem indicators are shown in Figure 12. These relative contributions in different climate zones of Xinjiang are shown in Figure S5 and Table S4. Overall, in Xinjiang, climate change accounted for 19.1%, 23.8%, and 23.2% of the total variation in ET, GPP, and LAI, respectively, while those of human activities are 80.9%, 78.2%, and 76.8%, respectively. The ET, GPP, and LAI trends are obviously dominated by human activities, of which the contributions are greater than 70%.  
Figure 11: Spatial pattern of the correlation between precipitation, temperature, and ecosystem indicators from 2001 to 2015. (**a**) Precipitation-ET, (**b**) Precipitation-GPP, (**c**) Precipitation-LAI, (**d**) Temperature-ET, (**e**) Temperature-GPP, and (**f**) Temperature-LAI.  
The contribution of climate change and human activities to the changes in the ecosystem indicators vary considerably across different climate zones.  
For the ET trends, human activities contributed the most to the changes in the ET trends in the arid zone, accounting for 83.8%, and climate changes contributed to 16.2%. The impact of human activities weakened as the climate became suitable for vegetation growth. There was minimal impact of human activities on ET in the humid zone; the impact of human activities had a relative contribution of 56.2%, while the impact of climate change had a relative contribution of 43.8%.  
For the GPP trends, human activities contributed the most to the changes in the GPP trends in the hyper-arid zones, accounting for 80.1%, and climate changes contributed to 19.9%. The impact of human activities in the arid and semi-arid zones had relative contributions of 76.3% and 75.4%, while those of climate change were 23.7% and 24.6%, respectively. The impact of human activities weakened in the dry sub-humid and humid zones; the impact of human activities had relative contributions of 68.2% and 69.4%, while those of climate change were 31.8% and 30.6%, respectively.  
Figure 12: Spatial distribution of the relative role of climate change and human activities on the variation in the ecosystem indicators from 2001 to 2015. (**a**) Relative role of climate change in ET, (**b**) Relative role of climate change in GPP, (**c**) Relative role of climate change in LAI, (**d**) Relative role of human activities in ET, (**e**) Relative role of human activities in GPP, and (**f**) Relative role of human activities in LAI.  
For the LAI trends, the impact of climate change and human activities on LAI is similar to GPP, but the impact of human activities on LAI is enhanced, especially in the hyper-arid and humid zones. The relative contributions of human activities increased by 2.6% and 6.8% in the hyper-arid and humid zones, respectively, compared with GPP.
## 3 Results
### VapC Influences M. snegmatis Susceptibility to Some Stressful Conditions  
The observed proteomic rearrangements associated with the abundance of proteins involved in the primary metabolic processes as well as in the adaptation to stressful conditions should also lead to phenotypic manifestations at the level of bacterial physiology. Therefore, we conducted a study on the resistance of _M. snegmatis_ strains with overexpression of the VapC toxin, as well as with the deletion of the _vapBC_ locus, to heat shock and antibiotic treatment.  
Preliminary determination of the minimum inhibitory concentrations (MICs) of several antibiotics (tetracycline, ciprofloxacin, isoniazid) was conducted for all the recombinant strains of _M. snegmatis_ included in this study and obtained during the course of this research (Table 1). Based on the results of this determination, no differences in the minimum inhibitory concentrations were found for exponential cultures of the investigated strains. Therefore, a single inhibitory concentration of each antibiotic was used to evaluate the resistance of _M. snegmatis_ strains with overexpression and deletions of target toxins, and it was greater than the minimum inhibitory concentration by at least 10 times.  
Our findings revealed that _M. snegmatis_ cells with induced VapC toxin production exhibited increased resistance to heat shock at 70 \({}^{\circ}\)C (0.354% viable cells) when compared to the empty vector control culture (0.0373% viable cells). In contrast, the \(\Delta\)vapBC strain demonstrated decreased resistance to higher temperatures when compared to the wild type (0.0939% vs 0.207% viable cells, respectively) under the conditions studied (Figure 1a).  
We observed no difference in the viability of _M. snegmatis_ VapC overexpressing and \(\Delta\)vapBC strains compared to their corresponding control cultures when treated with ciprofloxacin and isoniazid, as measured by relative CFU numbers. However, after 24 h of tetracycline supplementation, a significant decrease in CFU number (two orders of magnitude) was observed in the \(\Delta\)vapBC strain (Figure 1b). It should be noted that no changes in viability were found in the VapC overexpressing culture, suggesting that the antibiotic effect was likely indirect or influenced by another factor. Since there is a _mazEF_ TA system in _M. smegmatis_ that could also be involved in the response to antibiotic stress, we investigated the effect of tetracycline on a \(\Delta\)mazEF strain to further explore this assumption.
# Towards Client Selection in Satellite Federated Learning
## 3 System Model
### Coverage and Access Time Model  
#### 3.2.1 Satellites to GS  
Figure 4 explains the space geometric relationship between LEO satellites and the GS [25], where \(L\) is the arc length that the GS can communicate with a satellite, and \(v_{s}\) is the satellite's speed (uniform on the circle orbit). Then, we have the visibility time \(T\) between the GS and a satellite:  
\[T=\frac{L}{v_{s}} \tag{1}\]  
In addition, \(v_{s}\) and \(L\) can be calculated as follows:  
\[v_{s}=\sqrt{\mu\frac{1}{(R_{e}+h)}}\qquad(\rm{km/s}) \tag{2}\]  
\[L=2\times(R_{e}+h)\times\gamma \tag{3}\]  
where \(\mu\) = 3.986013 \(\times 10^{5}\) km\({}^{3}\)/s\({}^{2}\) is the Kepler constant, \(R_{e}\approx\) 6371 km is the earth's radius, and \(h\) is the distance between the orbit plane and the Earth's surface.
# Denoising Directional Room Impulse Responses with Spatially Anisotropic Late Reverberation Tails
## 4 Denoising by Tail Resynthesis
### EDR Analysis  
The EDR is a time-frequency extension of [PERSON]'s reverse-integrated broadband Energy Decay Curve (EDC), from which frequency-dependent characteristics of the RIR can be extracted by analyzing each frequency bin individually [5]. In particular, we are interested in the decay envelope parameters, the decay rate \(\delta(f)\) (more commonly represented as the 60-dB reverberation time \(T_{60}=3\ln(10)/\delta\)), and the initial power spectrum \(P_{0}(f)\), as well as the noise floor time limit \(t_{\text{lim}}(f)\) from which point onward the nondecaying noise floor is to be replaced with a synthesized prolongation of the late reverberation tail.  
As presented in [7], the analysis method consists of three main steps applied in turn to each frequency bin of the dB-scale EDR: first, the noise floor is determined by fitting the theoretical profile of a reverse-integrated constant power noise; then, the exponential decay region of the curve is determined by allowing for a certain headroom above this noise floor and avoiding nonexponentially-decaying early reflection regimes; and finally, the decay parameters are determined by fitting an exponential decay model to the determined region.
## 3 Results
### Influence of Metformin in PLC\(\gamma\)2-Mediated Downstream Signals  
Collagen receptor glycoprotein VI (GPVI) forms a complex with the Fc receptor \(\gamma\)-chain (FcR\(\gamma\)) containing immunoreceptor tyrosine-based activation motifs (ITAM) and is phosphorylated by Src-family kinases, such as Fyn or Lyn [19]. In platelets, cross-linking of the GFVI/FcR\(\gamma\) complex would enable the GFVI-bound Fyn or Lyn to move to a position close enough to FcR\(\gamma\) that it would catalyze the phosphorylation of FcR\(\gamma\) ITAM. In turn, this triggers the phosphorylation of downstream signals, leading to the activation of a kinase cascade (i.e., PLC\(\gamma\)2). PLC, a phosphatase, hydrolyzes phosphatidylinositol 4, 5-bisphosphate, which yields two key secondary messengers, diacylglycerolcerol (DAG) and inositol trisphosphate (IP\({}_{3}\)). DAG activates PKC, triggering 47-kDa protein phosphorylation (pleckstrin or p47). This triggers granule secretion, which results in an increased ATP release; the main role of IP\({}_{3}\) is to elevate calcium influx [16]. Metformin decreased significantly PLC\(\gamma\)2 phosphorylation and PKC activation (p-p47) in collagen-activated platelets (Figures 3A and 4A). In addition, confocal microscopy revealed that metformin (1.8 mM) reduced the phosphorylation of both PLC\(\gamma\)2 and PKC (green fluorescence) in activated platelets (Figures 3B and 4B). However, metformin did not significantly reduce phorbol 12,13-dibutyrate (PDBu; PKC activator)-induced platelet aggregation (Figure 4C), indicating that metformin did not directly affect PKC activation. These results suggest that metformin blocks PLC\(\gamma\)2-mediated downstream signaling (i.e., PKC).  
Figure 3: Effectiveness of metformin in phospholipase Cy2 activation in platelets. Washed platelets were preincubated with PBS or metformin (1.2 and 1.8 mM) and treated with collagen (1 mg/mL) for immunoblotting of (**A**) phospholipase Cy2 (PLC\(\gamma\)2) activation or (**B**) detecting confocal images of phosphorylated PLC\(\gamma\)2 (green fluorescence) and \(\alpha\)-tubulin (blue fluorescence) using goat anti-rabbit CF\({}^{\text{TM}}\) 488A and anti-mouse CF\({}^{\text{TM}}\) 405M Dyes, respectively. Data are presented as mean \(\pm\) standard error of the mean (\(n\) = 4). ***\(p\) \(<\) 0.001 vs. [PERSON]’s solution group; ***\(p\) \(<\) 0.01 vs. PBS + collagen group. The confocal images are the representative of four independent experiments. Bar: 5 \(\upmu\)m.
# Airline Network Planning Considering Climate Impact: Assessing New Operational Improvements
## 2 Materials and Methods
### Integrated Network Planning Model
#### 2.3.1 Pre-Processing Data  
The set of served ODs per season and their associated average weekly demand can be derived from itinerary- and passenger-related data. In addition, demand distribution on the travelling demand is required throughout the days and hours of the week to develop the flight schedule. To tackle the complexity involved in the passenger preference modelling, it was assumed that most of the passengers are willing to travel at the time that flights are currently provided. Based on this assumption, the passenger demand was modelled as an accumulated distribution near the actual flight time.  
Given the actual departure times, the demand distribution associated with each flight was assumed to follow a normal distribution with a 2 h standard deviation. Its mean value equals the departure time for that flight. Aggregating demand distributions for all flights operated by an airline in a route results in the weekly demand distribution function for that route. _Passenger demand distribution_ is a demand distribution function in which the summation of demand distribution values for all the time steps in a week is equal to the weekly average number of passengers the airline serves. In this approach, standard deviation represents the passengers' willingness to change their flight departure time within an interval of the departure time. Figure 2a depicts the weekly _Passenger demand distribution_ for KLM's AMS-ATL route in 2018.  
It was also assumed that each flight being scheduled would be taken by passengers available within a maximum of a 4 h interval of the scheduled flight (2 h on each side), which is shown with a dashed line in Figure 2b. This interval is called the _attraction band_ and is an input parameter of the framework. _Passenger flow_ is a part of passenger demand captured within the _attraction band_ and constrained by the capacity of the aircraft whenanalysing each aircraft type. In the pre-processing stage, _passenger flow_ is calculated for all aircraft types available per time step in the model and passed on to the fleet allocation agents to calculate the flight revenue and profit. Along with _passenger flow_ input, airfares, DOC, flight time, and climate impact (ATR20) are provided to fleet allocation agents. DOC and ATR20 are calculated according to all aircraft types that can operate in the routes and are assumed to be fixed during the season. Calculating the input for all possible aircraft types results in diverse potential solutions and significantly improves the profit and climate impact objectives in the partial fleet assignment problem solutions.
## 5 Medical Imaging-Based Kinematics
### Ultrasound Technology (US)
#### 5.1.1 Echo and Vector Doppler  
Echo Doppler estimates the velocity of blood and tissue through the use of the Doppler equation. By measuring the frequency shift from the original ultrasound wave and the reflected echo, the local velocity can be determined. The main shortcoming of this technique is its dependence on the angle between the original ultrasound wave (position of the transducer) and the displacement direction, which can introduce large intra- and inter-observer variability. Dependency on the transducer angle was solved by the introduction of vector Doppler techniques, which additionally provide in-plane velocity components. This is achieved by the simultaneous measurement of two doppler signals, either from two crossing beams from different transducers, or from a single transducer with two different in-plane receivers [159]. This technique is of great use in clinical practice for the qualitative assessment of blood flow and tissue displacement [160] and used in early studies of patient-specific hemodynamics to impose inlet and outlet flow boundary conditions [161; 162].
## 1 Introduction  
The use of glasses in various industries, including displays, lasers, optical fibers, upgrading converters, photonics and medicine, has been growing in everyday life in recent years [1, 2, 3]. Borate and phosphate are the most frequent glass-tech network formers because they offer beneficial physical qualities for the formation of glass, such as a low temperature of glass transition, a low melting point, and a high refractive index [3, 4]. In addition, it has been found to boost glass chemical stability by combining both network formers. Mixed glass formers (MGFs) of alkaline and alkaline such as boro-phosphates [4, 5], boro-silicates [6, 7], and telluro-phosphate [8, 9] are thoroughly investigated since the structure of a glass that is formerly used for host-glass is accessible and, according to the study, provides favorable places for cations. Glasses with borosilicate have specific and enhanced qualities, including capacity to transmit UV-NIR, high clarity, mechanical strength, resistance to corrosion, strong chemical stability, high transitional glass temperature and low optical losses in the near and mid-infrared range [10, 11]. The main subject of spectroscopic investigations on Ho\({}^{3+}\)-doped ternary glasses [4, 11, 12] were fluorescence characteristics of near-infrared and visible wavelength regions. Due to long persistent intermediate metastable levels, the energy levels of the trivalent Ho\({}^{3+}\) ion are favorable to population inversions (\({}^{5}\)I\({}_{6}\), \({}^{5}\)I\({}_{7}\)). In optical fiber communication, medicines and gas sensors [13], the 2 mg emission corresponding to the \({}^{5}\)I\({}_{7}\)\(\rightarrow\)\({}^{5}\)I\({}_{8}\) transition of the ion Ho\({}^{3+}\) was utilized [13]. In numerous oxide hosts Ho\({}^{3+}\) can lead to fascinating light behaviors [3; 14; 15; 16]. Ho\({}^{3+}\) stages \({}^{5}\)S\({}_{2}\) and \({}^{5}\)F\({}_{5}\): oxides have both green and red emissions. The host, temperature and Ho\({}^{3+}\) concentration are the main determinants of green and red emission intensity. Ho\({}^{3+}\): oxides study is also predicated on the promise of a shortwave laser powered by a long wavelength optical pump as a solid-state longitudinal laser [17; 18]. Low-phononamorphous glasses, with rare earth ions, have been said to be very promising in the development of near-infrared laser sources. The glasses exhibit better thermal stability, reduced phonon energy and a decreased OH absorption coefficient with the addition of Holmium ions into the basic composition [17; 18]. This leads to a greater stimulated emission cross-section and a longer emission life when rare earth ions undergo a near-infrared laser transition [19; 20]. Boro-phosphate glasses are commonly used for the purpose of solid-state lasers and optical fiber amplifier and have a low melting-point. This investigation soughtto identify the structural, thermal and optical properties of lithium boro-phosphate glasses, as well as the optimal concentration for future uses in solid-state lasers, for holmium integration and concentration.