esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Magnetic and Electrical Fields on Yield, Shelf Life and Quality of Fruits
## 2 Effect of Magnetic Fields and Electrical Fields on the Growth, Development, and Yield of Fruit
### Effect of Magnetised Irrigation Water on Plant Growth and Crop Yield
The percentage increments in tomato yields were 39.9 and 68.7% with magnetic flux densities of 124 and 719 G, respectively. They also showed increased concentrations of calcium, potassium, sodium, nitrogen, phosphorus, and organic carbon when water was treated [56]. Changes in water properties by magnetic fields can alter the characteristics of plant growth and production. Many researchers have concluded that magnetic treatment of irrigation water increases plant growth and crop yield [16, 30, 61, 80, 87, 88, 89, 90].
# Optimized Downlink Scheduling over LTE Network Based on Artificial Neural Network
###### Abstract  
Long-Term Evolution (LTE) technology is utilized efficiently for wireless broadband communication for mobile devices. It provides flexible bandwidth and frequency with high speed and peak data rates. Optimizing resource allocation is vital for improving the performance of the Long-Term Evolution (LTE) system and meeting the user's quality of service (QoS) needs. The resource distribution in video streaming affects the LTE network performance, reducing network fairness and causing increased delay and lower data throughput. This study proposes a novel approach utilizing an artificial neural network (ANN) based on normalized radial basis function NN (RBFNN) and generalized regression NN (GRNN) techniques. The 3 rd Generation Partnership Project (3 GPP) is proposed to derive accurate and reliable data output using the LTE downlink scheduling algorithms. The performance of the proposed methods is compared based on their packet loss rate, throughput, delay, spectrum efficiency, and fairness factors. The results of the proposed algorithm significantly improve the efficiency of real-time streaming compared to the LTE-DL algorithms. These improvements are also shown in the form of lower computational complexity.  
LTE network; resource allocation; ANN; normalized model +
Footnote †: journal: _computers_  
0
Footnote 0: Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))).
# Assessment of Spatial Variability in Ground Models Using Mini-Cone Penetration Testing
## 2 Theoretical Background
### Mini-Cone Penetration Test (Mini-CPT)  
The Cone Penetration Test device was first developed in the Netherlands in the 1930s, and since then, many features have been added with the development of various measurement sensors. Currently, it is used as a representative method for soil investigation alongside the Standard Penetration Test (SPT) [26; 27]. The Cone Penetration Test (CPT) is typically conducted in the field and involves inserting a cone with a diameter of 35.7 mm, a penetration area of 100 mm\({}^{2}\), and a tip angle of 60\({}^{\circ}\) into the ground at a constant speed to continuously measure the sleeve friction and cone resistance. The CPT allows for the measurement of cone penetration resistance, sleeve friction, and pore water pressure as the cone is inserted into the ground.  
However, the cone penetration equipment used in the field has aspects that make it difficult to use in laboratory experiments due to its size and the complexity of its operation. Due to these difficulties, experiments were conducted using a Mini-CPT developed in the laboratory [28; 29; 30]. When conducting experiments with this Mini-CPT, four major influencing factors must be considered for cone penetration:  
* Cone penetration speed; The cone penetration speed in sandy ground should be maintained between 2.5 and 20 mm/s [31].
* Distance from the bottom surface of the ground model; The penetration depth should be far from the distance greater than 10 times the diameter of the cone from the bottom surface [32].
* Distance from the soil tank walls; The penetration point should be set at a distance greater than 11 times the diameter of the cone from the walls of the soil tank [32].
* Particle size effect (\(B/d_{50}\)); A cone with a diameter at least 20 times greater than the average particle size (\(d_{50}\)) of the ground model should be used [33].
###### Abstract  
Globally, unhealthy dietary behaviours are consistently seen to significantly contribute to the burden caused by diet-related diseases (DRDs). This is particularly evident among adolescents, a demographic that are at a critical stage of development for lifelong eating habits. This study aims to map the efficacy of post-primary school-based nutritional education (NE) interventions in the modification of adolescent dietary behaviours. A scoping review methodology was implemented, following the Joanna Briggs Institute framework, and adhering to PRISMA-ScR guidelines. Peer-reviewed research from 2015 to 2024 was thoroughly searched using the PubMed and Scopus databases, with inclusion criteria centred on school-based NE interventions aimed at changing post-primary students' eating habits. In total, 50 studies were selected for analysis, which were then further categorised into five key intervention approaches: knowledge and behaviour-focused programmes, DRD-specific interventions, gamified or interactive learning methods, peer-led or externally facilitated programmes, and school food environment modifications. The findings indicate that structured NE interventions, particularly those incorporating behavioural theories, show positive outcomes in enhancing adolescent dietary knowledge and self-efficacy. The gamified interventions and interactive approaches demonstrated high engagement among participants, but the success of long-term changes was varied. The interventions addressing DRDs, especially obesity, showed significant impacts when combining educational components with structural modifications to school food environments. Peer-led models improved relatability and participation rates but faced challenges in terms of standardisation and repeatability. While school-based NE interventions effectively improve adolescent nutritional knowledge and behaviours, future research should focus on long-term follow-up assessments to determine the sustainability of these changes. These findings offer valuable insights for educators designing curricula, policymakers developing school health strategies, and practitioners seeking to implement feasible, evidence-based nutrition programmes in diverse educational settings.  
Keywords: nutritional education; diet-related disease; adolescence; intervention; scoping review +
Footnote †: journal: Applied Sciences
# Design of a Compact Ultra-Wideband Microstrip Bandpass Filter
## 1 Introduction
In this paper, a novel UWB bandpass filter based on MPCB structure is proposed. The bandpass filter is made of Rogers RO4350 dielectric substrates and pieces of RO450F prepreg. The upper surface of each dielectric substrate is coated with copper according to different design patterns and is grounded through two blind metalized holes. The transmission zeros and the resonance points are produced by using two groups of quarter-wavelength terminal-open stubs and DGS, respectively, which enhances the stopband suppression and reduces the return loss (RL) in passband of the filter. The measurement results show that the 3 dB FBW of the filter is 40.33%, the in-band reflection is better than 18 dB and the insertion loss at the center frequency of 12.795 GHz is 0.58 dB. Compared with some UWB bandpass filters designed with single-layer planar structures, the proposed multilayer laminated filter is relatively small in size. The three-layer coupling patterns of the filter in this paper are all simple SIR structures and extensions. The design of the DGS consists of three simple rectangles, all the design patterns are not complicated and there are only two blind holes in the interlayer via design. Generally speaking, the design method is relatively simple.
# A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models
## 4 Empirical Evaluation
### Main Results
#### 4.3.3 Three-Dimensional Reconstruction
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Method** & **Runtime (s)** & **GPU Usage (GB)** \\ \hline YOLOv4 [20] & 2235 & 12.5 \\ \hline GAN-LSTM-3D [22] & 2560 & 10.2 \\ \hline GAN-GK-LSTM [55] & 2185 & 15.6 \\ \hline GAN-ResNet-3D [52] & 3895 & 13.9 \\ \hline ANN-GGO [53] & 2069 & 13.7 \\ \hline Proposed & 2475 & 10.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Computational efficiency comparison of models. a noticeable regression in precision. The HD and ED measurements of these models exceed those of VGG-16 by substantial margins, ranging from 88% to over 100% for HD and 59% to 104% for ED. This trend makes it clear that the sophistication of the architecture of a model does not inherently translate to superior performance in specialized tasks such as 3D tumor reconstruction. Most strikingly, MobileNet, which is optimized for efficiency on devices with limited computational power, shows more than a doubling of the HD and ED values compared to those of VGG-16, translating to a decline in performance by over 100%. These results illustrate the compromise between efficiency and precision, with the streamlined structure of MobileNet sacrificing the latter. Figure 7 presents the distribution of decision-making times for the proposed 3D reconstruction model utilized in real-time bidding (RTB) environments. The histogram illustrates decision-making times ranging from approximately 350 milliseconds (ms) to 650 ms. A noticeable concentration of decision times falls between 500 ms and 550 ms, signifying the modal interval where the model demonstrates optimal efficiency. The right-skewed distribution suggests that while most decision-making instances are grouped around the median range, fewer significantly prolonged decision times extend toward the upper limit of 650 ms. This skew indicates that the model occasionally experiences delays, possibly due to complex input data or computational constraints within the RTB system. Furthermore, the wide range of the distribution, covering a 300 ms interval, indicates a considerable variability in the model's response times across different RTB scenarios. This variation could stem from inherent differences like the input data or the model's computational process dynamics. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Model** & **HD** & **ED** \\ \hline AlexNet & 2.462 & 1.832 \\ \hline GoogleNet & 2.682 & 2.259 \\ \hline ResNet & 2.756 & 2.349 \\ \hline DenseNet & 2.852 & 2.536 \\ \hline MobileNet & 2.920 & 2.896 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Performance of different pre-trained models for the reconstruction of 3D lung tumors. Figure 7: Distribution of decision-making times for 3D reconstruction in RTB environments.
# Application of a MEMS-Based TRNG in a Chaotic Stream Cipher
## 6 Conclusions  
In this work, a secure stream cipher system was proposed and tested. This system presents a robust STM-LFSR architecture using a MEMS accelerometer with a conditioning stage to generate true random keys. The stream cipher module was implemented in a Xilinx Virtex 7 FPGA using a 64-bit fixed point arithmetic. The stream cipher algorithm was implemented for a throughput of 1.072 Gbps using 805 LUTs, 40 registers and 16 DSPs.  
For the seed generation block, the usage of a MEMS accelerometer was studied. We proved that the noise generated by this inertial MEMS accelerometer at rest has random properties, especially when it is sampled at a low sampling rate. However, in order to pass all of the NIST tests, a conditioning stage is necessary. In this work, SHA-512 function was used for this purpose, getting random sequences that pass the NIST test.  
An in-depth cryptanalysis was made studying different aspects of our cryptosystem such as randomness, sensitivity dependence on the key and the plaintext, key space, and chaotic reconstruction of the map. This study allows us to conclude that our system can be considered secure, i.e., the amount of computation time needed to hack the cipher is impracticable with current computational equipment and known cryptanalysis algorithms.  
On the other hand, although a MEMS accelerometer was proposed to generate the keys, other MEMS and microsensors, such as gyroscopes, light detectors, magnetic sensors, cameras, etc., which are often present in IoT devices, could have been used instead or in a combined way. It is necessary to take into account that in real designs, one must take advantage of the presence of several entropy sources to guarantee the generation of true random numbers. Relating this fact with the low area and high security of our system, we can conclude that this system is suitable for IoT applications.  
This work has been supported by the \"Ministerio de Economia y Competividad\" MINECO-FEDER (TEC2014-52840) and the \"Formacion de Profesorado Universitario\" FPU fellowship to [PERSON] (FPU14/03523). [PERSON] carried out the main research and wrote the paper. [PERSON], [PERSON], and [PERSON] set up the experiment to measure the accelerometer data. [PERSON] and [PERSON] implemented the algorithm in the FPGA. This work was carried out under the supervision of [PERSON]. All authors were involved in modifying the paper, the literature review, and the discussion of the results. The authors declare no conflict of interest.
# Life Cycle Assessment for the Production Phase of Nano-Silica-Modified Asphalt Mixtures
## 2 Literature Review and Definitions
### Nanomaterials and their Application as a Modifier in Asphalt Mixtures
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Author** & **Type of Nanomaterial** & **Effect on Asphalt Binder and Mixtures** \\ \hline [32] & Nano-silica & Improves the self-healing of HMA \\ \hline [10] & Nano-silica & Improves marshal stability, resilient modulus, and fatigue life \\ \hline [29] & Nano-silica & Enhances antiaging property and rutting and fatigue \\  & & cracking performance \\ \hline [30] & Nano-silica & Improves temperature stability, decreases temperature \\  & & cracking resistance and reduces susceptibility to \\  & & moisture damage \\ \hline [28] & Nano-silica & Enhances the complex shear modulus and improves the anti-rutting performance of asphalt mixture \\ \hline [34] & Nanosilica & Reduces the susceptibility to moisture damage and increases \\  & & the strength of asphalt mixes \\ \hline [35] & Nano-silica & Improves the performance and durability of asphalt mixtures \\ \hline [36] & Nano-silica & Improve rutting and fatigue performance of asphalt binder \\ \hline [37] & Nano-silica & Decreases the interaction between asphalt molecules and \\  & & increases free volumes in the configuration \\ \hline [38] & Nano-silica & Decreases the consistency, rate of water absorption and \\  & & porosity of the roller compacted concrete pavement \\ \hline [39] & Nano-silica & Improves the rheological characteristics, toughness, and \\  & & viscosity of bitumen \\ \hline [40] & Nano-silica & Reduces the creep strain deformation and increases the \\  & & dynamic shear modulus \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Review of previous studies on modification of asphalt binder with nano-silica.
## 3 Surface-Based In-Situ Measurement Techniques
### Pressure Anemometers  
Pressure anemometers can be divided into groups of pressure plate anemometers and pressure tube anemometers. As pointed out in Section 1, pressure plate anemometers have not been used in meteorological applications since the first half of the 20 th Century, mainly because of their complex dynamic response to wind speed fluctuations. Instead, pressure tube anemometers, called Pitot tubes, are widely used in meteorological research, especially on board aircraft (five-hole probes) and in wind tunnels. The basic Pitot tube is an L-shaped tube consisting of two pressure ports and the sensing tip [70]. The differential pressure transducer provides as output the difference between the total and static pressures, which represents the dynamic pressure caused by the wind. In other words, the pressure difference is proportional to the wind speed squared. The Pitot tube equation for a standard instrument type and for incompressible flow (small Mach number) is:  
\[v_{p}=44.72136\sqrt{\frac{h_{\text{kPa}}}{\rho_{a}}}, \tag{21}\]  
where \(v_{p}\) is the measured wind speed, \(h_{\text{kPa}}\) is the pressure difference from the transducer and \(\rho_{a}\) is the air density, which is estimated based on barotropic pressure and the absolute air temperature measurements from parallel instruments [70]. In addition, \(\rho_{a}\) can also be corrected for the effect of water vapor content, if relative humidity is measured. However, the magnitude of this correction is typically of the same order as the accuracy of the instrument [70].  
The Pitot tube calibration is complex because of the non-linear relationship between the (dynamic) velocity pressure and the air flow rate. The calibration has to be done in a wind tunnel and is typically based on a look-up table that provides the ratio of the true flow rate and the measured flow rate. This ratio varies by the tube design and for example by inflow angles. In case of a five-hole probe, typically used on board aircraft to measure the 3D wind vector, the calibration is extremely complicated, and various calibration algorithms have been introduced (e.g., [71]). However, the advantages of the Pitot tube are the high frequency of the measurements, very good accuracy and an almost linear calibration for strong wind speeds, which makes it suitable for aircraft measurements, where the true air speed is high. However, in laboratory conditions in wind tunnels, where even very small pressure differences can be measured accurately, it can provide accurate turbulence measurements [19]. Pitot tubes have not been used much to investigate wind gusts, but they can provide wind gust measurements when used on board aircraft (Section 5, [38]).
## 3 DCPSO with Cooperation
### Distributed Cooperative Particle Swarm Optimization with Cooperation
#### 3.2.2 Update of Velocities and Positions  
According to the standard PSO algorithm, the velocity and position of particle \(z_{ij}\) can be updated with Equation (8) and Equation (9), respectively. What is more, the value of inertia weight \(\omega\) plays an important role in creating a balance between global exploration and local exploitation. A large value for \(\omega\) facilitates global exploration, which is useful in the initial stages of an optimization. However, a small value allows for better local searching, which is particularly useful in the later stages, as the swarm moves toward the neighborhood of the optimum.  
In [40], a value for \(\omega\) dynamically decreasing from 0.9 to 0.4 is recommended for better performance. Hence, a dynamically changed \(\omega\) is adopted in this paper, which is updated by the following equation:  
\[\omega(t)=\omega_{start}-(\omega_{start}-\omega_{end})(\frac{t}{T})^{2}, \tag{10}\]  
where \(\omega_{start}=0.9\), \(\omega_{end}=0.4\), and \(T\) is the maximum number of iterations.
## 2 Overview of Supplementary Damping Systems
### Classification of Damping Devices
#### 2.1.2 Classification by Activation Method  
Passive systems: These systems do not require an external power source and respond solely to the motion of the structure. Examples include viscous dampers, friction dampers, and metallic yield dampers.  
Active systems: These systems use external power to drive actuators that apply forces to the structure based on feedback from sensors. Examples include active mass dampers and active tendon systems.  
Semi-active systems: These systems combine aspects of both passive and active systems. They require minimal external power to adjust their properties but do not directly input energy into the structure. Examples include magnetorheological (MR) dampers and variable orifice dampers. Semi-active systems occupy a balanced position, requiring minimal external energy while still offering a certain level of adaptability. For instance, magnetorheological (MR) dampers can modify their damping characteristics by changing the magnetic field applied to specialized fluids. This feature allows for the real-time optimization of damping properties, all while avoiding the high energy demands typical of fully active systems.  
Hybrid systems: These systems combine passive devices with active or semi-active components to enhance performance and reliability.
## 2 Materials and Methods
### Experimental Design  
A popularly used tartary buckwheat variety (_cv._ Yunqiao No. 2) was used in the experiment. The seed rate was applied at 90 kg ha\({}^{-1}\). Four fertilizer application treatments were set as follows: high fertilization level (N 120 kg ha\({}^{-1}\) + P\({}_{2}\)O\({}_{5}\) 90 kg ha\({}^{-1}\) + K\({}_{2}\)O 60 kg ha\({}^{-1}\), HF), moderate fertilization level (N 80 kg ha\({}^{-1}\) + P\({}_{2}\)O\({}_{5}\) 60 kg ha\({}^{-1}\) + K\({}_{2}\)O 40 kg ha\({}^{-1}\), MF), low fertilization level (N 40 kg ha\({}^{-1}\) + P\({}_{2}\)O\({}_{5}\) 30 kg ha\({}^{-1}\) + K\({}_{2}\)O 20 kg ha\({}^{-1}\), LF), and zero fertilization (none of N-P-K, ZF). The abovementioned four treatments were all plastic film mulched, in comparison with zero fertilization with no mulching taken as the control (CK) (Figure 2). All treatments were repeated three times and arranged in a completely random block design. The plot area was 35 m\({}^{2}\) (5 m \(\times\) 7 m) in a south-to-north direction. Fertilization and film mulching were carried out in late March each year. Field operations, including hole sowing, film mulching, and fertilization, were completed using an integrated seed drill and mulching machine (Sanniu Agricultural Machinery Manufacturing Co., Ltd., Dingxi, China). The size of the polyethylene plastic film (Golden-soil Plastic Products Co., Ltd., Lanzhou, China) was 0.01 mm thick and 110 cm wide. Urea (N \(\geq\) 46.0%), diammonium phosphate (P\({}_{2}\)O\({}_{5}\)\(\geq\) 46.0%, N \(\geq\) 18.0%), and potassium chloride (K\({}_{2}\)O \(\geq\) 51.0%) were applied as base fertilizers. Sowing depth was 3\(\sim\)4 cm, with 5-7 seeds per hole. The row spacing was 30 cm, and plant spacing was 12 cm (equivalent to 18 rows in each plot), giving rise to a plant density of 1.8 \(\times\) 10\({}^{6}\) plants ha\({}^{-1}\). In order to reduce white pollution, the plastic film was recycled after crop harvest, leaving the land uncovered until the second year's soil preparation. Tartary buckwheat was sown on 6 May 2015, 29 May 2016, and 26 May 2017 and harvested on 31 August 2015, 5 September 2016, and 12 September 2017,