esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The soluble solids content (SSC) of blueberry is a key index for evaluating its quality. In view of the demand for rapid non-destructive testing of blueberry SSC and the shortcomings of the existing single-variety testing models in cross-variety applications, a universal prediction model construction method based on hyperspectral imaging (HSI) technology is proposed in this study. The spectral data of three blueberry varieties were obtained by using a 935\(\sim\)1720 nm hyperspectral imaging system. A partial least squares regression (PLSR) model was constructed by combining different preprocessing methods such as Savitzky-Golay (S-G), multiplicative scatter correction (MSC) and standard normal variable transformation (SNV). The results showed that the PLSR model pretreated by S-G-MSC-SNV had the best performance, and the determination coefficient, root mean square error and residual prediction deviation of the prediction set were 0.94, 0.33% and 3.94, respectively. The characteristic wavelengths were optimized in stages by uninformative variables elimination (UVE) and the successive projections algorithm (SPA), and the model was simplified by multiple linear regression (MLR). Finally, a high-precision UVE-PLSR model and a simple and efficient UVE-SPA-MLR hybrid model were obtained. The construction of this universal model effectively solves the limitation of the single-variety model and has important application value in the optimization of food industry production and quality control.  
blueberry; soluble solids content; hyperspectral imaging; universal model; PLSR; feature selection Article
# Devising Mobile Sensing and Actuation Infrastructure with Drones
## 2 Designing DaaG
### Main Functions of DaaG
#### 2.3.1 Communication Scheduling  
In sensor network, sensors and actuators use sleep mode to minimize their power consumption. This technique works in the traditional environment that many sensors are stationary, but it is not appropriate in the network environment where nodes are mobile. DaaG is mobile, so the sensors' communication interface uses sleep mode by default, and it should wake up in response to the beacon message of DaaG. Moreover, DaaG has many communication interfaces to support communicating with various sensors and actuators. There are certain advantages to reducing the energy consumption of every sensor, but DaaG consumes much energy to support beaconing for all communication interfaces.  
We propose and adopt a backoff-based beaconing algorithm to reduce the energy consumption. The detailed algorithm is introduced in Algorithm 1, where \(C\) is the set of communication interfaces, \(c_{i,bf}\) is the remaining backoff time and \(c_{i,bmx}\) is the maximum backoff time of the \(i\)-th communication interface, \(b_{max}\) is the maximum of the possible backoff time, \(\alpha\) is the increasing backoff factor and \(t_{period}\) is the time interval of the algorithm. The core idea of this algorithm is that each communication interface sends a beacon message with its inherent backoff time. Some communication interfaces increase their backoff time to reduce energy, when there are no nodes around using the same interface. Even if there are no nodes that use a certain communication interface at the current position, there is the possibility that the node appears when DaaG moves to a different position. Therefore, we adopt a maximum backoff time \(b_{max}\) in the algorithm to limit the backoff increase.  
The difference between \(b_{max}\) and \(c_{i,bmx}\) is that the former affects backoff time with respect to the movement of the drone, while the latter only considers the response of nearby nodes. However, when \(b_{max}\) is too high, DaaG can still pass a node in between two beacons. DaaG also sends beacons for every arbitrary distance it moves to prevent missing nodes.
## 4 System Modelling
### Path Reservation
#### 4.8.1 Path Request  
To avoid overloading the upper levels servers, each path request is treated based on its scope, more specifically it is treated at the lowest level that covers its source and destination positions, thus short paths that are within the scope of level 1 server are treated locally. Firstly, the vehicle initiates a path request, by sending a path request packet (PReq) with its current position and the final destination position. The PReq will be sent to the lowest level VVS through V2V communication, in case of isolated node where there are no neighbors in its coverage area, store-carry-forward approach is applied to deliver the path request to the VVS, the latter will decide either to treat the PReq locally or not if the destination position is situated inside its coverage zone (e.g., S1 in Figure 3). Otherwise, the PReq packet is forwarded to the upper-level VVS (e.g., S2 Figure 3). Similarly, long path requests are treated in the highest level VVS (e.g., S3 Figure 3). Upon the reception of the PReq packet, the VVS computes the shortest path from all possible paths which weighs greater than zero at the expected arriving time (fully reserved roads will be excluded from shortest path computing). Taking into consideration the previously answered path requests, and the routes' weights from the RRM.  
Figure 3: Path request process.
# Fast Path Generation Algorithm for Mobile Robot Navigation Using Hybrid Map
###### Abstract  
In this paper, we address the challenge of memory consumption in mobile robot navigation, particularly when using grid-based maps for accurate environment representation. While grid-based maps are widely used, their large memory requirements make them unsuitable for embedded systems. To overcome this limitation, we propose a novel path planning algorithm that rapidly generates secure paths using a hybrid map. This hybrid map significantly reduces memory usage compared to grid-based maps while maintaining the efficiency of a topological map. Experimental results demonstrate that the proposed method requires only 1.5% of the computation time needed for grid-based path planning, ensuring faster and more efficient navigation. Furthermore, the approach provides robust and secure paths, making it ideal for mobile robot applications. This method holds promise for advancing autonomous navigation in resource-constrained environments.  
hybrid map; mobile robot; memory consumption; path planning; navigation Article
## 5 Discussion
### Broader Implications  
River bars have always been at the forefront of biogeomorphological research [17; 59]. Our study contributes to the enhancement of quantitative insights into biogeomorphic interactions, fostering interdisciplinary engagement in the process [61] as the MYR, a non-equilibrium river undergoing strong anthropogenic disturbance, provides an ideal case for disentangling the complex bidirectional biogeomorphic interactions in fluvial and riparian systems, owing to the detailed in situ observations [62; 63; 64; 13]. Simultaneously, our enhanced ML-based LAI inversion model is employed to generate spatiotemporally continuous 30 m resolution LAI products, thereby addressing the deficiency of biophysical vegetation parameters in riverine ecosystems.  
Compared to current moderate-resolution (MODIS) LAI products [65], Landsat LAI products generated in this study can accurately capture bar LAI heterogeneity in the MYR (Figure 10). At the same time, these current moderate-resolution LAI products sometimes will misclassify bars into water owing to the mismatch between coarse resolution and small bar areas, resulting in no LAI values in these small bars and thus limiting further analyses. Generally, the proposed framework that combines maximum-value composites, RTM simulations, and ML can easily be transferred to predict long-term LAIs at other bars owing to the high generalization of RTM and ML as well as no requirement of in situ LAI measurements.  
There are several advantages of the LAI estimation method mentioned above; however, there is still room to improve LAI estimations for monitoring bar vegetation dynamics. Firstly, maximum-value composites trade temporal resolution for spatial continuity. When we want to observe bar vegetation activity at both high and temporal resolutions, some advanced sensors or algorithms can be utilized, such as Sentinel-2 and PlanetScope imagery and the spatiotemporal fusion methods [66; 67]. Moreover, the proposed framework does not require in situ LAI measurements, but these measurements are still necessary if it is possible to be collected, which can be used as a calibration for producing accurate LAI products [33].  
Figure 9: Adjustments of hydraulic geometry at different sub-reaches along the Middle Yangtze River from 2004 to 2015. The blue (red) bars represent river depth (river width) and cross-section area (river regime coefficient) in the left and right figures, respectively. The color gradient from lighter to darker signifies the progression of time, ranging from 2004 to 2015.
# An Aerobic Degradation Model for Landfilled Municipal Solid Waste
## 4 Verification
### Experiment 1  
#### 4.1.1 Experimental Introduction  
An indoor aerobic degradation study in an old landfill in southeastern Vienna was conducted [35]. The age of the sampled waste was between 8 and 17 years. The physical composition of the sampled waste was 31% residue, 12% bulky waste, 25% commercial waste, 19% construction waste, and 13% compost waste. Waste was passed through a 20 mm sieve, and waste smaller than 20 mm was used for the experiment. The experimental chambers had diameters of 20 cm and heights of 65 cm. The experimental temperature was controlled at 35 degrees Celsius. The initial masses of S3 and S6 columns were 14.6 kg and 15.7 kg, and the densities were 1.25 t/m\({}^{3}\) and 1.37 t/m\({}^{3}\), respectively. The mass water content of the freshly collected waste was 41.4%. The experiment was carried out for 513 days. The S3 treatment was oxygenated and recharged for all 513 days, while the S6 treatment was oxygenated and recharged for 275 days, with an oxygen concentration twice that of S3, and 243 days were allowed for anaerobic recharge operation. Total organic carbon (TOC), total nitrogen (TN), humic acid, and cellulose were measured at the beginning and end of solid waste samples; the leachate quality was sampled once a week; and the test indexes include chemical oxygen demand, ammonium, and nitrate. Oxygen, carbon dioxide, and methane concentration were measured continuously.
## 2 Material and Methods
### Plasma Source, Characterization, and Treatment  
A sinusoidal power supply was used to generate the cold plasma. Helium with five standard liters per minute was used as feed gas supplemented with ten standard cubic centimeters per minute of molecular oxygen as carrier gases. The plasma jet was operated at 8 kV peak-to-peak voltage and 6 kHz frequency, resulting in a total dissipated power of 1 W. The distance between the plasma jet and the treated target was fixed to 10 mm. Optical emission spectroscopy (AvaSpec-ULS3648-USB2 with diffraction grating of 300 lines per mm, ten \(\upmu\)m gap, and a wavelength range of 200 to 1100 nm) was employed to analyze the plasma gas. In plasma-treated liquids, hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)) and nitrite (NO\({}_{2}\)\({}^{-}\)) were measured using spectrophotometry as described before [38]. The pH of plasma-treated cell culture media was measured using a pH meter. The temperature of plasma-treated cell culture media was measured using a thermal infrared camera (FLIR E4 camera 80 by 60 pixels). For the treatment of collagen tissues, either direct or indirect plasma exposure was performed. In the direct treatment, the tumors embedded in collagen were directly exposed to physical plasma for 4 min while, in the indirect treatment, 1 mL of fully supplemented culture medium was exposed to plasma for 4 min and then transferred to collagen-tumor tissues. The control group remained untreated without any intervention and therapy. The plasma treatment was repeated 24 h later, and the collagen tissues were incubated for at least another 24 h after that. The plasma treatment time was identified to be suitable based on results obtained in pilot experiments.
# Fixed Wireless Access in Flexible Environment: Problem Definition and Feasibility Check
## 3 Assumptions and Inputs
### Potential Connection Targets  
The set of potential connection targets (CT) is indicated by  
\[pCT=\{pCT_{1},pCT_{2},\ldots,pCT_{k}\}. \tag{1}\]  
This set can include any nearby datacenter (if the host placement for the service is flexible), internet exchange point(s) for general internet connectivity, and the home server of the CSP for telephony services [34; 42].
# _Sci_
## 2 Materials and Methods
### History of Laser Employment as Link Source
#### 2.1.4 Demonstrations on Fast-Moving Platforms  
Not to belittle the work done in orbit, but very little of the above experimentation examined the impacts of terminals moving at greater speeds (low-earth orbit at seven kilometers per second versus geosynchronous orbit at three kilometers per second) or being affected by intramosphere turbulence; this is changing. The German aerospace center (Deutsches Zentrum fur Luft- und Raumfahrt, i.e., DLR) are conducting experiments using their optical space infrared downlink system, a small laser communications terminal orbiting in low-earth orbit, demonstrating the requirements for high-precision alignment between stations [49; 50]. Additionally, in 2013, DLR went on to successfully demonstrate laser communications from a jet aircraft. Flying at roughly sixty-five percent the speed of sound (eight-hundred kilometers per hour), the test demonstrated a transmission rate of 1.25 giga-bits per second at sixty kilometers. The test not only demonstrated the ability to overcome atmospheric turbulence-driven distortions, but also the impact of fast flight maneuvers and strong vibrations [49].
# Two-Step Multiuser Equalization for Hybrid mmWave Massive MIMO GFDM Systems
## 1 Introduction
### Previous Works on Hybrid Architectures
The main purpose of the proposed low complexity hybrid precoder is to minimize the total transmit power of the BS, under data rate requirements of users and coverage constraint of signaling broadcasting. For this solution, iterative optimizations between analog and digital precoders are not required. In [25], a full iterative solution was proposed, where the analog and digital parts are iteratively. This approach introduced optimal performance in terms of removing the residual MU and inter-symbol interferences (ISIs). The previous schemes require a high number of phase shifter and connections. To solve the issues of complexity and power consumption of hybrid full connected architectures, some approaches were addressed for hybrid sub-connected architectures in [26; 27], but with losses in terms of performance. In the sub-connected architectures, each RF chain is only connected to a sub-set of antennas. The authors of [26] designed an efficient MU linear equalizer combined with full analog precoder for uplink single carrier-frequency division multiple access (SC-FDMA) systems. They considered single RF low complexity UTs using an efficient full analog precoder based on the knowledge of partial CSI. Then, at BS, the hybrid equalizer is optimized by minimizing the average BER. Finally, a hybrid MU equalizer based on a dynamic subarray antennas structure was proposed in [27]. In the first step, the analog part of equalizer is designed, where a dynamic antenna mapping algorithm is applied to connect each RF chain to antennas, and the phase of each phase shifter is computed. The analog equalizer is constant over the iterations and subcarriers owing to the hardware constraints. Then, the digital equalizer is computed iteratively over the subcarriers based on the iterative block decision feedback equalization (IB-DFE) principle.
## 3 Results and Discussion
### Evaportranspiration and Vegetation Greening
It is difficult to precisely separate the different components of the water budget on such large scales and this analysis is an attempt to highlight the dynamic interaction between vegetation and climate in the regulation of the water balance and the partitioning of precipitation into evapotranspiration and runoff. The statistical relationship establishes observational evidence supporting the hypothesis that vegetation greening is responding to the increased precipitation and suggests that part of the \"excess water\" is contributing to increases in evapotranspiration.
## 2 Fundamental Principles of Quasi-Zero Stiffness
### Basic Types of QZS Vibration Isolators
#### 2.2.1 Linear Spring as Negative Stiffness Mechanism
This classification was based on the system's reliance on the linear spring for the primary negative stiffness effect, with the cam-roller mechanism acting to support this structure rather than serving as the primary source of negative stiffness. Figure 5: Different structures of a linear spring as a negative stiffness mechanism: (**a**) QZS isolator in three directions proposed by [PERSON] [36]; and (**b**) schematic diagram of a novel linkage antivibration structure via the linear positive and negative stiffness compensation mechanism proposed by [PERSON] [37]. The design of the QZS vibration isolation system, employing a three-spring structure, exhibits notable shortcomings. This susceptibility arises when the system is subjected to substantial loads due to the unconstrained trajectories of the linear springs. Moreover, friction occurring at the joints diminishes the isolation zone, thereby impacting the system's isolation performance.
## 5 Discussion
### Statistical Significance and Effect Size Interpretation  
The results of the one-way ANOVA on the FP-Growth execution time across support thresholds revealed not only a statistically significant difference (\(p<0.001\)) but also a large effect size, with an estimated \(\eta^{2}\) (eta squared) = 0.78. This indicates that 78% of the variance in the FP-Growth execution time is explained by changes in the minimum support threshold, which are substantial. The high \(\eta^{2}\) value confirms that FP-Growth's performance is highly sensitive to threshold variations, reinforcing the importance of parameter tuning in practical deployments.  
FP-Growth's superior performance, particularly under lower support thresholds, can be attributed to its avoidance of candidate generation and repeated database scans. At low thresholds (e.g., 0.10), the number of frequent itemsets increases significantly, leading Apriori to generate and test an exponential number of candidate itemsets across multiple passes through the data. This results in higher computational overhead and memory usage. In contrast, FP-Growth builds a compact FP-tree structure in only two scans of the dataset and then mines frequent itemsets via a divide-and-conquer recursive strategy. This tree-based compression becomes increasingly efficient as the number of frequent itemsets grows, making it especially suitable for large, sparse datasets, which are common in e-commerce settings.  
The Pearson correlation coefficient of r \(\approx\) 0.97 between the rule counts of Apriori and FP-Growth suggests a strong linear relationship: when Apriori generates more rules, FP-Growth does as well, often at a higher magnitude. However, this should not be interpreted as redundancy. Rather, the strong correlation implies that both algorithms capture similar underlying co-occurrence structures in the dataset, but FP-Growth is able to scale further and uncover more associations, particularly at relaxed thresholds.  
This correlation highlights a complementary relationship: while Apriori may be sufficient for exploratory analysis or small-scale systems--where simplicity, interpretability, and lower memory usage are priorities--FP-Growth is more suitable for scalable, production-grade environments that demand efficiency and completeness. Moreover, practitioners can use Apriori output as a predictive heuristic or sanity check for estimating the rule volume and computational requirements of FP-Growth, as demonstrated by the regression models derived in this study.  
In summary, the high correlation reinforces shared sensitivity to parameter settings, but also points to strategic differentiation: FP-Growth is better suited for exhaustive mining, while Apriori offers a lightweight, pedagogical, or constrained-resource alternative.
## 3 Discussion
Further clinical research is needed to optimize its delivery and evaluate its full therapeutic efficacy. On the other hand, apigenin, a flavonoid with antioxidant properties, plays a crucial role in altering the interaction between Keap1 and Nrf2. When apigenin binds to Keap1, it induces structural changes that reduce Keap1's ability to retain Nrf2. This disruption primarily affects the DGR domains in Keap1, which typically facilitate the binding and degradation of Nrf2. As a result, Nrf2 is released from Keap1 and translocates into the nucleus where it activates antioxidant genes by targeting specific DNA sequences known as antioxidant response elements (AREs) [56]. Research indicates that apigenin not only stabilizes Nrf2, extending its presence in cells, but also enhances its antioxidant effects. Furthermore, apigenin upregulates the expression of genes involved in detoxification and cellular defense, thereby improving the cells' ability to manage oxidative stress. In this way, apigenin enhances Nrf2 activation and strengthens the cellular response to oxidative damage, offering additional protection against cellular harm [57]. Moreover, apigenin has several pharmacophores that play a key role in its effects on the Keap1-Nrf2 pathway, particularly relevant for managing Long COVID-19 symptoms (Figure 7). The hydroxyl groups in apigenin are crucial for its antioxidant activity, allowing for the activation of the Keap1-Nrf2 pathway by regulating Keap1 activity, thereby releasing Nrf2 to initiate the expression of antioxidant genes in the cell nucleus [58]. The  
Figure 6: Diagram of the primary structures of Nrf2 and Keap1. The key functions of the Nrf2 and Keap1 domains are illustrated [49; 55]. flavonoid structure of apigenin enables efficient interaction with target proteins such as Keep1, affecting the binding and release of Nrf2. Additionally, the lipophilic nature of apigenin, enhanced by its benzene rings and substituents, allows for better penetration into cell membranes, thus enhancing its bioavailability to interact with the Keep1-Nrf2 pathway [59]. This understanding provides important insights into the potential of apigenin as a supportive therapy in reducing oxidative stress and inflammation associated with Long COVID-19, encouraging further studies for the development of effective therapeutic strategies. To verify these findings, further molecular experiments such as in vitro binding affinity assays, Nrf2 activation studies using cell-based models, and site-directed mutagenesis on Keep1 to analyze specific apigenin interactions are essential. These experiments would provide a deeper understanding of the mechanism by which apigenin regulates the Keep1-Nrf2 pathway, validating its therapeutic potential.