esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods  
### Study Area and Datasets  
We selected Beijing, the capital of China, as our research area (Figure 1). Beijing covers an area of 16,410.54 square kilometers and has a population of 21.7 million. Over the past few decades, Beijing has experienced rapid development, with significant growth in both population and GDP [34; 35]. Meanwhile, Beijing's urban built-up area has expanded from 471 km\({}^{2}\) to 1642.52 km\({}^{2}\) at an average annual rate of expansion of around 31.19 km\({}^{2}\) per year. This rapid urbanization has led to the emergence of extensive urban-rural fringe areas, where urban and rural characteristics mix in a complex way.  
Our research integrated multiple geospatial data sources, including nighttime light (NTL), high-resolution remote sensing images, building footprints, and Points of Interest (POIs). This multidimensional approach aimed to reveal and distinguish urban, rural and urban-rural fringe areas within Beijing. We obtained 4.8 m resolution remote sensing imagery for 2019 from Google Earth [36], and nighttime light data for the same year from the Luojia-1 satellite [37]. Building footprint data covering 656,563 structures were retrieved from Baidu Maps [38]. We also collected 994,300 POI data points of various types via the Amap API [39]. Our analysis was standardized by dividing the study area into 250 m \(\times\) 250 m grids, resulting in 272,528 grids for Beijing. All data sources were resampled to fit within this grid framework.
# Metabolic Profiling of _Conyza sumatrensis_ ([PERSON].) [PERSON] from Lugazi, Uganda
## 2 Materials and Methods
### Antimicrobial Testing with Agar Diffusion and Microdilution Assays  
We conducted antimicrobial assays to evaluate the efficacy of plant extracts against three distinct microorganisms (_Escherichia coli_ DSM498, _Bacillus subtilis_ DSM109511, and _Pseudomonas fluorescens_ DSM289), which were chosen for their diverse characteristics and relevance. _B. subtilis_ was used as an indicator for activity against Gram-positive bacteria. _E. coli_ and _P. fluorescens_ are indicators for activity against Gram-negative bacteria. The genus _Pseudomonas_ is known for its nonsusceptibility against a variety of antibiotics and is thus of particular clinical interest. The use of these strains allows a comprehensive evaluation of the antimicrobial activity of the extracts against both Gram-positive and Gram-negative bacteria, as they exhibit different properties. For the antimicrobial activity testing in the agar diffusion test, 50 \(\mu\)L of an overnight culture was spread out on Luria-Bertani (LB) medium (10 g/L tryptone, 5 g/L yeast extract, 5 g/L NaCl) or nutrient medium (5 g/L peptone, 3 g/L meat extract, 15 g/L agar). The dry extracts were dissolved in the respective solvent (water or 70% (\(v/v\)) ethanol) in a concentration of 50 mg/mL, and 10 \(\mu\)L were applied to filter paper discs (5 mm) and placed on top of the agar medium. Gentamycin (for _E. coli_ and _P. fluorescens_) or erythromycinocin (for _B. subtilis_) at 25 \(\mu\)g/mL was used as a positive control and purified water was used as a negative control. The assay was incubated at 37 \({}^{\circ}\)C (_E. coli_, _B. subtilis_) or 30 \({}^{\circ}\)C (_P. fluorescens_) for 24 h. Then, the inhibition zones were measured and recorded. To evaluate the minimal inhibition concentration (MIC), the bacteria were grown in a 5 mL preculture overnight at 30 \({}^{\circ}\)C for _P. fluorescens_ and 37 \({}^{\circ}\)C for the other two strains. Then, the bacteria were diluted with media to approx. 5 \(\times\) 10\({}^{5}\) colony-forming units (CFU) per milliliter. The MICs were measured in microtiter plates in a final volume of 200 \(\mu\)L and final extract concentrations of 5, 2.5, 1.25, 0.625, 0.313, and 0.156 mg/mL dissolved in the respective solvent (water or 70% (\(v/v\)) ethanol) incubated for 14 h with shaking. To monitor the growth of the bacteria, the optical density at 600 nm was measured every 15 min. _P. fluorescens_ was cultivated in glass tubes with a final volume of 2 mL and final extract concentrations from 2.5 to 0.078 mg/mL at 30 \({}^{\circ}\)C for 2 days.
## 3 Methods
### Wavelet Transform  
Existing studies usually convert birdsong signals into STFT spectrograms [34] and Mel spectrograms [35]. However, a fixed STFT window function results in time resolution and frequency resolution not being optimized at the same time. In addition, Mel spectrograms are significantly affected by amplitude variations, which means that different intensities of the same sound can produce different features [36].  
On the other hand, the wavelet transform has good time-frequency resolution and can provide local information of the signal in both time and frequency domains. It is also more suitable for non-stationary signals. Therefore, in this paper, wavelet transform is used to convert birdsong signals into spectrograms. The formula of wavelet transform is defined as follows:  
\[WT(a,\tau)=\frac{1}{\sqrt{a}}\int_{-\infty}^{\infty}f(t)*\psi(\frac{t-\tau}{a })dt \tag{1}\]  
where a is the scale parameter, which controls the scale of the wavelet function; \(\tau\) is the time shift that controls the translation of the wavelet function; \(\psi(\frac{t-\tau}{a})\) is a wavelet basis function. The choice of wavelet basis function directly affects the time-frequency resolution and spectral characteristics of the wavelet transform. Therefore, the Morlet wavelet [37], with a higher response to birdsong, is selected in this paper, and its definition is shown in Formula (2).  
\[\psi_{Morlet}(t)=\frac{1}{\sqrt{\pi f_{b}}}\cdot e^{|2\pi f_{c}t-(t^{2}/f_{b})} \tag{2}\]  
where \(f_{c}\) is the center frequency and \(f_{b}\) is the bandwidth.
## 4 Discussion
### Limitations  
This study has several limitations. First, although the dominant window detector is convenient to implement, additional data combination procedures were needed to calculate the alert dwell times. An automated, AI-based alert classification method will be applied in the next version of the dominant window detector. Second, the present study onlyshowed the impact of fundamental alert characteristics on the alert dwell time; more variables such as medical specialties, individual variables (age, gender, clinical experience), categories, and clinical importance of alerts should be explored. Third, we focused on the alert dwell time, although alert acceptance is also an efficiency indicator of APOE alert system performance and could not be recorded through our current program. Lastly, although we have collected and analyzed a large number of alerts, our data were collected from a single academic medical center in Taiwan. This may limit the generalizability of our findings. To address this, datasets of alerts collected in other hospitals should be used for external validation.
# A Two-Stage Routing Protocol for Partitioned Underwater Wireless Sensor Networks
## 2 Literature Review
The use of source routing enables the source node to determine the whole path from itself to the destination. The scheme takes cross-layer approach by a Stop-and-Wait Automatic Repeat Request (ARQ) which enables it to identify overloaded links and unpredictable routes. All the above-mentioned protocols assume limitedly mobile or static sensor nodes. Therefore, when faced with mobility induced issues such as network partitioning, the performance of the protocols may suffer setbacks. Moreover, many of these protocols deploy nodes according to predetermined deployment patterns and then design the protocol accordingly. If the topology changes, for instance due to mobility, the performance of such protocol may go down.
# The Performance and Fouling Control of Submerged Hollow Fiber (HF) Systems: A Review
## 8 Submerged HF Membrane Integrity and Failure
### Foreign Bodies  
Membrane damage and integrity compromise also can be caused by unexpected water-quality fluctuations together with the failure of the pretreatment processes, leading to the inadequate removal of foreign material [314]. These foreign bodies, coupled with the effects of strong aeration, can score or puncture the membrane fibers. A membrane autopsy performed by [PERSON] et al. concluded that the unexpected presence of silicon dioxide spicules (needle-like structures) resulted in multiple membrane occlusions and punctures, leading to a loss in membrane integrity [321]. The erosive effect of fluidized particles [322; 323; 324; 325] in the feed stream is also known to compromise the membrane integrity by impacting the membrane surface [123; 242; 326; 327; 328; 329]. Patterns of particle scraping was clearly observed [238; 279], as well as a decrease in the membrane rejection for the larger fluidized glass beads (3 mm) [242]. As a result, care is needed for submerged HF processes that deliberately introduce scouring by suspended or fluidized media (Section 5.3.2) to control fouling.
## 1 Introduction
Combining RL with DL, a Double-Deep Q Network (DDQN) is proposed in [18], which is more excellent for handling a large number of states than Q-Learning, and solved the problem of overestimating Q function value in traditional DQN. In this paper, we analyze the link status of the LEO satellite network. We use the deep learning method to enable satellite nodes to learn the link status within two hops. Therefore, each satellite node can make the next hop selection autonomously according to the link status. Our main contributions in this paper are summarized as follows. * A two-hops state-aware routing strategy based on deep reinforcement learning (DRL-THSA) is proposed for LEO satellite networks. In DRL-THSA, each node collects link state information within two-hop neighbors and makes routing decisions based on the information. The link state information is interacted between nodes through Hello packets; therefore, the DRL-THSA discover the node failure event in time and change the next hop node. * A setup and update method of link state is proposed. The link state is divided into three levels, and the traffic forwarding strategy for each level is presented, which allows DRL-THSA to cope with link congestion. * The routing decision method based on the DDQN network is proposed, and the DDQN is analyzed from three aspects: model setting, training process and running process. The remainder of this paper has the following structure: In Section 2, the LEO satellite networks model, which includes the satellite networks topology, setup and update of link state, and two-hops state aware updating, are described. In Section 3, the deep reinforcement learning model setting and routing algorithm are presented in detail. The experimental results are discussed in Section 4, and Section 5 draws the conclusions.
## 1 Introduction
This system is similar to the electrical power circulation-type test rig. The input of the gearbox is driven by a motor, and the output is torque induced into the gearbox by a pump. The torque can be changed during the test by adjusting the flow rate and pressure of the pump [5]. [PERSON] et al. introduced electrical and mechanical power circulation type test rigs. A method for applying torque to the mechanical power circulation-type test rig and a torque-applying device similar to a rotary actuator was introduced. This device was equipped with a two-stage planetary gear train and a motor, which was installed on the standard Forschungsgstelle fur Zahnrader und Getriebebau of the Technical University Munich (FZG) back-to-back test rig. They also demonstrated that the test torque and rotation speed could be varied. However, they did not include the test results of their torque-applying device. It was also described as a method applicable to small mechanical power circulation-type test rigs [4]. [PERSON] et al. introduced a failure analysis and test evaluation process for analyzing and evaluating the performance of a torque generator. The rig for the evaluation was of the electrical power circulation type, and the input was an electric motor while the output was a powder brake [6]. [PERSON] introduced the general process requirements for the simulation, test rig, testing, and verification of WTGBs. The paper describes the purpose of the gearbox test (assuming design factors, noise, vibration, temperature) [7]. [PERSON] et al. introduced a 2.5-MW electrical power circulation-type test rig, which is installed in NREL(National Renewable Energy Laboratory) [3]. The test rig was designed with the components and operational characteristics of a real wind turbine drivetrain. The test rig was equipped to apply a non-torque load to the main shaft connected to the gearbox by using a bearing and an actuator. Previous studies have described the configuration of test rig, test procedures according to gearbox test items and how to apply torque by using powder brakes, pumps or rotary actuators. However, previous studies introduced a method of applying torque to an electric or mechanical power circulation test rig for small gearboxes, and in the case of a mechanical power circulation test rig, there was no device capable of applying variable torque during the test. In addition, in most studies for MW class large gearbox tests, an electric power circulation test rig was used, and no mechanical power circulation test rig capable of controlling variable torque during the test could be found. In this study, we developed a mechanical power circulation test rig that can test gearboxes up to 5.8 MW. The rig is equipped with a variable torque-applying device with a planetary gearbox and linear actuators. The performance of the test rig, as well as the variable torque-applying device, was validated. A resonance analysis was performed on the test rig by changing the rotational speed of the motor.
# Model Predictive Control and Its Role in Biomedical Therapeutic Automation: A Brief Review
## 3 MPC in Biomedical Applications
### Cancer
#### 3.5.2 Hyperthermia Therapy
Investigators [142] developed a model-based thermal dose controller for hyperthermia treatment explicitly based on a dynamic patient model that predicted the future thermal dosage. This model also computed optimum corrective actions to minimize output errors and control costs. Precise temperature control in the target tissue is the major factor affecting the quality of treatment in the case of local hyperthermia. Researchers [143] have explored an MPC algorithm providing voxel-level temperature control in MR-HIFU hyperthermal treatment. In this method, the system state variables, i.e., voxel temperatures, were measured at all sampling instants. Appropriate control actions were determined for the subsequent instants based on the system state variables of the previous instant. These control actions were aimed to minimize deviations from the desired temperatures of the target region voxels. More investigations are needed to further improve the efficacy of MPC-led automated hyperthermia therapies.
# Miniaturized Arrow-Shaped Flexible Filter-Embedded Antenna for Industrial and Medical Applications
## 2 Filtering Antenna Design and Analysis
### Antenna Design  
Figure 2 illustrates the steps involved in the design of the proposed arrow-shaped flexible antenna. The obtained S-parameter results for each design step are shown in Figure 3a, whereas Figure 3b shows the expanded view to get a closer look at the effects of various design optimizations on the ISM band. The S-parameter, also referred to as the reflection coefficient, is a critical parameter as it shows that loss in power, which consequently explains how much power is successfully transmitted [46]. For modern-day devices, the rule of S11 < \(-10\) dB is utilized, and bandwidth is the frequency having the value that satisfied the rule.  
_Step 1_: Initially, a rhombus-shaped antenna with an overall geometrical size of \(30\) mm \(\times\)\(30\) mm is designed by rotating the square-shaped patch at \(45^{\circ}\). The antenna is fed by a coplanar waveguide feedline. The antenna dimensions at this stage are obtained by using standard mathematical formulas [47]. The antenna designed in this step offers  
Figure 3: (**a**) Return loss of various antennas involved in design methodology; (**b**) close-up shot.  
Figure 2: Antenna design methodology steps.  
dual resonances at 2.45 GHz and 11 GHz, as depicted in Figure 3a. The obtained results exhibit that the impedance matching is not good at the targeted frequency band of 2.45 GHz.  
_Step 2_: In the second step, the design is modified into an arrow-shaped antenna by truncating the lower half of the patch. Also, the antenna design is miniaturized at this step to obtain the overall dimensions of 25 mm \(\times\) 33 mm. This modification results in the improvement of bandwidth and impedance matching. However, minor shifting is observed from 2.45 GHz to 2.6 GHz for the lower band, whereas the upper band is also shifted from 11 GHz to 6.8 GHz, as shown in Figure 3.  
_Step 3_: In this final step, the proposed antenna is further miniaturized to 23 mm \(\times\) 30 mm. Two rectangular slots are etched from the lower end of the arrow-shaped patch antenna. Furthermore, two additional triangular-shaped slots are etched from the lower side of the antenna. As a result, a third resonance is obtained at 9 GHz, as illustrated in Figure 3a, in addition to further improvement in impedance matching of already obtained bands.
# Recent Advances in Tunable External Cavity Diode Lasers
## 4 Prospects  
High power external cavity diode lasers have important applications in precision machining and cutting. The output power of the external cavity semiconductor laser is mainly determined by the structure of the gain chip and the fabrication process. The power of a single laser diode is limited. Quantum dot lasers are limited by the self-assembly preparation method, and the power is very small. It is difficult to obtain small-sized quantum dot structures and achieve output in the visible light band for QD laser. Researchers try to use optical amplifiers to achieve high power output, but the tunable range is very small [77]. It is expected that the power of the laser can be further improved by optimizing the fabrication process of the laser diode.  
Mode-hop-free tuning is also one of the key research contents at present. Although it has been found that the mode-free tuning of ECDL can be achieved by selecting an appropriate tuning pivot point, the tuning range is still limited. Another approach is to synchronously tune the optical components in some external cavity configurations. However, this method is limited by the external cavity structure and needs further study. For some commercial lasers, the laser, power, and cooling devices will be tightly integrated together, which is beneficial to avoid mode hopping due to mechanical vibration and temperature drift.  
As a high-efficiency light source, the external cavity diode laser will also be deeply integrated into the intelligent control system. By embedding sensor and control system, the real-time monitoring and accurate control of the laser working state can be realized, which can effectively improve the operation reliability and stability of the laser.  
Figure 6: (**a**) Experimental setup of the ECDL with a dual-period holograph grating [72]; ©Elsevier. Copyright 2006 Optics Communications. (**b**) Experimental setup of the dual-wavelength ECDL with a diffraction grating and a volume Bragg grating [74]; ©AIP Publishing. Copyright 2016 Applied Physics Letters. (**c**) Experimental setup of the dual-wavelength external-cavity laser with a DFB laser and a volume Bragg grating [76]. ©SAP. Copyright 2018 Japanese Journal of Applied Physics.
## 2 Materials and Methods  
### Experimental Design  
One hundred and twenty skinless fresh fillets from 120 different farmed rainbow trout (_Oncorhynchus mykiss_) were purchased at a local fish farm in Rio de Janeiro, Brazil (22\({}^{\circ}\)41\({}^{\prime}\)57\({}^{\prime}\) S 42\({}^{\circ}\)52\({}^{\prime}\)40\({}^{\prime}\) W) and then were immediately transported in styrofoam boxes containing ice (0 \({}^{\circ}\)C) to the laboratory. Fillets (114.76 g \(\pm\) 5.25 g each) were individually placed in nylon/polyethylene packages (80 \(\mu\)m thickness, 22 cm height and 15 cm width) with the following barrier properties according to manufacturer's specifications: O\({}_{2}\) transmission rate (OTR) of 66.31 cm\({}^{3}\)/m\({}^{2}\)/day and water-vapor transmission rate (WVTR) of 4.91 g/m\({}^{2}\)/day at 23 \({}^{\circ}\)C and 50% relative humidity (Gabrilina, Sao Paulo, Brazil). Then, packages were added or not of one oxygen absorber sachet and then were sealed (Engevac, Sao Paulo, Brazil). Fillets were randomly distributed into six different treatments according to packaging systems (air or oxygen scavenger) and UV-C doses (0.102 or 0.301 J/cm\({}^{2}\)), which are shown in Table 1. Immediately after each treatment, trout fillets were stored at 4 \(\pm\) 1 \({}^{\circ}\)C and analyzed in duplicate for lipid oxidation and protein oxidation, and in quadruplicate for instrumental color parameters and texture profile analysis on days 0, 3, 6 and 9. Each treatment was composed of 20 packages (5 replicates \(\times\) 4 days of storage; \(n=5\)) with a headspace of \(45.54\pm 1.15\) mL. The headspace was calculated by the difference of the total volume of the package and the sample volume of 114.76 g \(\pm\) 5.25 g of trout fillet. The days of storage were chosen based on the shelf life of refrigerated trout fillets treated singly with either O\({}_{2}\) absorber [7] or UV-C dose at 0.110 J/cm\({}^{2}\)[12]. Air packaging was chosen instead of vacuum packaging to evaluate the effects of the two UV-C doses and O\({}_{2}\) scavenger in the worst scenario for oxidative processes.
# A Survey of Advances in Landscape Analysis for Optimisation
## 2 Beyond Fitness Landscapes
### Dynamic and Coupled Fitness Landscapes  
Most landscape analysis assumes that the environment is constant, but there are many problems where the landscape is dynamic. Two scenarios where the dynamics of landscapes have been studied include applications where the objective function changes over time (due to changes in the problem environment) and in the case of coevolution, where landscapes are coupled [6] and influence each other.  
An early approach to dynamic landscape analysis involved using existing landscape analysis techniques and simply interspersing landscape changes at set intervals during the search space sampling [6]. As an alternative, [PERSON] [7; 8] proposed using coupled map lattices for constructing fitness landscapes and modelling landscape dynamics. This framework was used to characterise landscape features (such as ruggedness and epistasis) over time as well as features specific to dynamic landscapes, such as change frequency and dynamic severity. [PERSON] et al. [9] proposed an online approach to dynamic landscape analysis using a multipopulation method. In their framework, metrics are calculated basedon information collected by subpopulations tracking peaks for quantifying changes in the landscape (peak shift severity, height variance and fitness variance).  
In the context of coevolution, there are two distinct landscapes to consider: the objective landscape (the view of the problem to be solved) and the subjective landscape (the coevolutionary algorithm's view on the problem) [10]. It has been suggested that failure of coevolutionary algorithms could be due to disassociation between these two landscapes [11]. For coevolutionary games, [PERSON] [12] proposed a dynamic landscape model based on a fitness interpretation of player payoff and used existing fitness landscape analysis techniques to analyse the game dynamics.