esa-sceva/satcom-chunk-collection huggingface dataset:
# Decoupling the Impacts of Climate Change and Human Activities on Terrestrial Vegetation Carbon Sink
## 4 Discussion
### Limitations and Perspectives  
We have to admit that this study still has some limitations from a methodological perspective. Data processing methods including projection transformation, clipping, and resampling can introduce certain errors, thereby affecting the numerical values of NEP and the subsequent results. The accuracy of the NEP time series we obtained based on the Modis NPP-\(\mathrm{R_{h}}\) model can be affected by both the quality of NPP data and the soil respiration model. [PERSON] et al. indicated that there is a risk of underestimation and overestimation of NPP products [64]. Due to the lack of inventory sample data, the existing soil respiration models mainly rely on empirical formulas, which ignore the regional differences in the soil environment. Moreover, the carbon storage data from the Harmonized World Soil Database did not change over time [65]. Second, although the method of residual analysis based on multivariate linear regression has been widely used to estimate the influence of HA on natural habitats, it exhibits certain interpretation limitations. For instance, we only include temperature and precipitation data into the linear regression equation; other climate factors like extreme climate events were not taken into account. [PERSON] et al. also indicated that NEP and meteorological factors may exhibit complex non-linear relationships [66]. Moreover, the residual error of the regression model cannot reflect which specific HA impacts NEP. Although these uncertainties remain, this study provides a direction for further exploration. Therefore, in future research, more emphasis needs to be placed on the validation from more field observations and the optimization of the NEP model.  
Although carbon neutrality is a national-level action and goal, we believe that achieving carbon neutrality at the local level is equally important. Regional accounting of carbon sources and sinks contributes to the establishment of national carbon accounts and adjustments to carbon reduction strategies. NEP accounting, based on satellite imagery, enables long-term monitoring of regional terrestrial carbon sinks. Simultaneously, integrating existing studies on the estimation of carbon emissions allows for the efficient assessment of regional carbon neutrality gaps [67]. In subsequent studies, we hope to conduct research on regional carbon neutrality gaps in CCZ based on high-quality data and models, attempting to understand the surplus or deficit situation and delve deeper into the driving mechanisms. It is worth noting that as temperatures continue to rise, the magnitude of NEP in CCZ is likely to continue increasing, as they exhibit a broad positive correlation based on our results. However, predicting when this positive effect will cease or turn negative, and assessing its impact on carbon neutrality, requires further analysis.
# Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion
###### Abstract  
The growth of urbanization, population, and economic activity has led to a substantial increase in freight transportation demand, exceeding the capacity of existing infrastructure and creating new challenges across various regions. This has resulted in significant traffic congestion, increased travel times, and higher operational costs for commercial vehicle fleets. Leveraging topological data, such as road networks and traffic patterns, can enable more efficient routing strategies to navigate around congested areas. This study presents a comprehensive approach to truck rerouting strategy by integrating spatial analysis, truck characteristics, traffic conditions, road geometry, and cost-benefit analysis to select alternative routes suitable for commercial vehicle fleets. Incorporating real-time traffic information and predictive analytics, commercial vehicle operators can optimize their routes, reduce fuel consumption, and improve overall delivery efficiency. Three case studies were presented to demonstrate the proposed diversion decision framework. Two scenarios were designed for each case study: a base scenario with no diversion and an optimized scenario with a diversion strategy. The travel times, fuel consumption, and economic impacts between the two scenarios were compared and quantified as a total annual saving of USD 52 million. This approach goes beyond selecting alternative routes and provides decision makers with measurable benefits that justify diversion strategies.  
alternative route selection; congestion mitigation; truck diversion strategies; traffic management; GIS applications in transportation +
Footnote †: journal: _Sciencedence_
# Review of Recent Phased Arrays for Millimeter-Wave Wireless Communication
###### Abstract  
Owing to the rapid growth in wireless data traffic, millimeter-wave (mm-wave) communications have shown tremendous promise and are considered an attractive technique in fifth-generation (5G) wireless communication systems. However, to design robust communication systems, it is important to understand the channel dynamics with respect to space and time at these frequencies. Millimeter-wave signals are highly susceptible to blocking, and they have communication limitations owing to their poor signal attenuation compared with microwave signals. Therefore, by employing highly directional antennas, co-channel interference to or from other systems can be alleviated using line-of-sight (LOS) propagation. Because of the ability to shape, switch, or scan the propagating beam, phased arrays play an important role in advanced wireless communication systems. Beam-switching, beam-scanning, and multibeam arrays can be realized at mm-wave frequencies using analog or digital system architectures. This review article presents state-of-the-art phased arrays for mm-wave mobile terminals (MSs) and base stations (BSs), with an emphasis on beamforming arrays. We also discuss challenges and strategies used to address unfavorable path loss and blockage issues related to mm-wave applications, which sets future directions.  
beamforming; beam-scanning; millimeter-wave (mm-wave); 5G; line-of-sight (LOS); phased arrays +
Footnote †: journal: Sensors
## 3 Results and Discussion
### Fundamental Frequency and Related Perturbation Parameters
Figure 7 narrows the range of muscle activation for normal phonation by frequency and perturbation parameters. Similar to the results in the previous section, in addition to the difficulty with high-frequency vibration, patients with a vocal fold polyp should pay attention to increasing their TA and LC muscle activity while decreasing CT muscle activity to produce a voice in a medium-high frequency range. One of the reasons for limited pitch range may be a decreased ability to vary vocal fold length. As shown in the figure, vocal fold vibration is irregular when \(a_{\text{CT}}>0.4\), so CT activity will be restricted to a small range. The results also provide insights into the increase in fundamental frequency in response to effort. For patient with a vocal fold polyp, obtaining a better balance between CT and TA muscle activity is critical. As the results in Figures 6 and 7 show, when the value of \(a_{\text{CT}}\) is not small, TA muscle activity has little influence on voice quality. Hence, TA muscle activity can be increased appropriately to control \(F_{0}\) while avoiding the generation  
of high-frequency sound. LC activity should be kept greater than 0.3 even when the pitch is in the low-frequency range.
# Influence of Sea Level Anomaly on Underwater Gravity Gradient Measurements
###### Abstract  
Considering the theoretical research needs of gravity gradient detection and navigation, this study uses the right rectangular prism method to calculate the disturbing gravity gradient from sea level anomalies in the range of \(5^{\circ}\times 5^{\circ}\) in the Kuroshio extension area of the western Pacific with large sea level anomalies. The disturbing gravity gradient is obtained in different directions within a depth of 50 m below the mean sea level based on the principle of the disturbing gravity gradient. The calculation results show that the sea level anomalies at local positions significantly impact the underwater gravity gradient measurements, with the maximum contribution exceeding 10 E and the maximum difference between different locations exceeding 20 E. The change of the sea level anomaly over time also significantly impacts the measurement of the underwater gravity gradient, with the maximum change value exceeding 20 E. The impact will have a corresponding change with the seasonal change of the sea level anomaly. Therefore, the underwater carrier needs to consider the disturbing gravity gradient caused by sea level anomalies when using the gravity gradient for underwater detection and navigation.  
disturbing gravity gradient; sea level anomaly; right rectangular prism; forward modeling 20222220222022202220222202  
[PERSON], [PERSON] et al. conducted a quantitative analysis and calculation of the high-frequency wave of the sea surface, and they determined that for the sea state above level 4 (the average wave height is greater than 1.25 m), the fluctuation of the sea waves will cause significant disturbance in the measurement value of the gravity gradient on the underwater carrier [8]. In addition to the high-frequency waves, there are also low-frequency changes in sea level. Sea level denotes the average height of the sea surface over a period of time. It is the level that the ocean can maintain at a certain moment, assuming that no sea surface fluctuation is caused by tides, waves, or other factors. Based on the observation time, the sea level can be divided into daily mean sea level, monthly mean sea level, annual mean sea level, long-term mean sea level, etc., which are affected by weather, climate, or celestial movement and change. Moreover, long-term global trend changes, periodic changes, and large spatial differences can be observed at different locations [9; 10; 11]. This study aims to determine how the mass anomaly caused by the difference of the sea level height affects the gravity gradient, which could provide a theoretical reference for the practical application of gravity gradient detection and navigation in the future.
# Malware Collusion Attack against SVM: Issues and Countermeasures
###### Abstract  
Android has become the most popular mobile platform, and a hot target for malware developers. At the same time, researchers have come up with numerous ways to deal with malware. Among them, machine learning based methods are quite effective in Android malware detection, the accuracy of which can be as high as 98%. Thus, malware developers have the incentives to develop more advanced malware to evade detection. This paper presents an adversary attack scenario (Collusion Attack) that will compromise current machine learning based malware detection methods, especially Support Vector Machines (SVM). The malware developers can perform this attack easily by splitting malicious payload into two or more apps. Meanwhile, attackers may hide their malicious behavior by using advanced techniques (Evasion Attack), such as obfuscation, etc. According to our simulation, 87.4% of apps can evade Linear SVM by Collusion Attack. When performing Collusion and Evasion Attack simultaneously, the evasion rate can reach 100% at a low cost. Thus, we proposed a method to deal with this issue. This approach, realized in a tool, called ColluDroid, can identify the collusion apps by analyzing the communication between apps. In addition, it can integrate secure learning methods (e.g., Sec-SVM) to fight against Evasion Attack. The evaluation results show that ColluDroid is effective in finding out the collusion apps and ColluDroid-Sec-SVM has the best performance in the presence of both Collusion and Evasion Attack.  
Android security; machine learning; SVM; collusion attack; evasion attack +
Footnote †: journal: Applied Sciences
# Development of Automatic Crack Growth Simulation Program Based on Finite Element Analysis
## 2 Development of AI-FEM
### Crack Tip Meshing Criteria
#### 2.2.1 Geometry and Materials  
Figure 2 is a schematic of a flat plate with a semi-elliptical surface crack. Figure 2a shows the overall shape of the cracked plate, and Figure 2b shows the shape variables of semi-elliptical surface crack. In Figure 2a, \(L\), \(w\), and \(t\) mean the vertical length, half of the horizontal length, and thickness of the plate, respectively. In Figure 2b, \(a\), \(c\) and \(\theta\) represent the crack depth, half of the crack length, and crack angle, respectively. As shown in Table 1, \(w/t=3.15\), \(a/t=0.3\), and \(a/c=0.5\) were considered as the shape variables of the plate in the SIF sensitivity analyses. The elastic modulus (\(E\)) was considered to be 200 GPa, and the Poisson's ratio (\(v\)) was considered to be 0.3.
## 6 Stability Analysis
### Stability Analysis for FDTSMC  
First of all, a Lyapunov candidate function, \(V_{f_{1}}\), and its derivative, \(V_{f_{1}}\), are defined along the system trajectory as follows:  
\[\left.\begin{array}{l}V_{f_{1}}=\frac{1}{2}s_{3}^{2}\\ \dot{V}_{f_{1}}=s_{3}s_{3}\end{array}\right\} \tag{25}\]  
Now, \(\dot{s}_{3}\) from Equation (21) is substituted into Equation (25) as follows:  
\[\dot{V}_{f_{1}}=s_{3}\Big{[}\widehat{L}_{j}^{3}h(\mathbf{x})+\widehat{L}_{g}L _{j}^{2}h(\mathbf{x})\dot{u}_{FDTSMC}-\dddot{\widetilde{z}}_{ref}+c_{3}\bar{e}+ c_{2}\sigma+\beta_{3}\frac{q_{3}}{p_{3}}\sigma\Big{(}\tfrac{q_{3}}{p_{3}}-1 \Big{)}\sigma\Big{]} \tag{26}\]  
Now, \(u_{FDTSMC}\) from Equation (24) is substituted into Equation (26), giving:  
\[\dot{V}_{f_{1}}=-\mathcal{K}_{1}s_{3}^{2}-\mathcal{K}_{2}s_{3}\,\text{sign}( s_{3})\leq-\mathcal{K}_{1}s_{3}^{2}-\mathcal{K}_{2}|s_{3}|\qquad\therefore\forall \,\mathcal{K}_{1},\mathcal{K}_{2}>0,\dot{V}_{f_{1}}<0 \tag{27}\]
# Software-Defined Visible Light Communication for Internet of Things: A Low-Complexity Approach
## 1 Introduction
To address the challenges of implementing flexible and adaptive VLC systems, this work proposes an SD-VLC solution based on the PYNQ platform, an open-source framework that enables rapid prototyping of adaptive computing systems using Python in combination with programmable logic and microprocessors [12; 13; 14]. The proposed system achieves low complexity and real-time reconfigurability, making it suitable for diverse IoT deployment scenarios. By employing carrierless amplitude and phase (CAP) modulation, the system effectively reduces hardware complexity and eliminates IQ imbalance, while preserving high spectral efficiency under the constraints of intensity modulation and direct detection (IM/DD). In addition, an adaptive equalizer based on the sign-data least mean squares (SDLMS) algorithm [15] is integrated to dynamically mitigate inter-symbol interference (ISI) and nonlinear distortions, with significantly lower computational overhead compared to conventional LMS approaches. Extensive simulation results under both additive white Gaussian noise (AWGN) and multipath channel conditions demonstrate that the proposed approach can reduce the bit error rate (BER) by nearly two orders of magnitude, validating its effectiveness and robustness for resource-constrained VLC-based IoT applications. While existing SD-VLC studies have explored various modulation and equalization techniques, this work distinguishes itself by combining CAP modulation and SDLMS equalization in a fully reconfigurable system optimized for IoT scenarios. Instead of proposing entirely new algorithms, we focus on tailoring and integrating computationally efficient techniques into a hardware-software co-design framework using the PYNQ platform. This approach offers a practical balance between performance and complexity, demonstrating significant BER improvements while maintaining low power consumption--making it especially suitable for resource-constrained VLC-based IoT deployments. The main contributions of this work are summarized as follows:* An SD-VLC system is proposed on the PYNQ platform, enabling reconfigurability and low complexity suitable for IoT scenarios. * CAP modulation is employed to simplify hardware design while maintaining high spectral efficiency under IM/DD constraints. * A lightweight adaptive equalizer based on the SDLMS algorithm is integrated to enhance signal quality with minimal computational overhead. The rest of this paper is structured as follows. Section 2 outlines the overall system architecture and discusses its applicability to IoT scenarios. Section 3 focuses on the baseband signal processing techniques, with particular attention to the design and modeling of CAP modulation and SDLMS-based equalization. In Section 4, we detail the simulation setup and evaluate system performance under different channel conditions. Finally, Section 5 summarizes the main findings and discusses potential directions for future work.
# Fluorescent Imprinted Nanoparticles for Sensing of Chlorogenic Acid in Coffee Extracts
## 1 Introduction
A procedure using molecularly imprinted solid-phase extraction, coupled with high-performance liquid chromatography, was established for their determination. The recoveries of the chlorogenic acids were found from 93.1% to 101.4% [13]. Although there are a few examples of MIPs for chlorogenic acid recognition present in the literature, not one is based on optical fluorescence, which is very interesting for its great sensitivity in comparison to other spectroscopic techniques, allowing the detection of particular compounds and analytes in low concentrations. Fluorescence sensors based on MIPs can be developed, taking advantage of the fluorescent properties of some of its components, either monomers present inside the polymer or template. Since not all analytes are fluorescent, it is convenient to use fluorescent monomers to have a fluorescent MIP matrix (fMIP) as a recognition element. When the analyte binding occurs, the fluorescent properties changes of the polymer can be measured, and usually a fluorescence quenching, a shift, or even a fluorescence enhancement are observed. Applications of fMIPs as detecting elements are well documented in the literature, such as the detection of cocaine using an optical fiber with a thin MIP film made of acrylamide fluorescein, acrylamide, and ethylene glycol dimethacrylate (EGDMA) [14], or the detection of \(\lambda\)-cyhalothrin in honey samples using allyfluorescein, acrylamide, and EGDMA to build a fMIP layer directly synthetized onto the core shell of Fe\({}_{3}\)O\({}_{4}\)/SiO\({}_{2}\) particles [15]. More recently, we also developed fluorescent MIPs for the analysis of tyrosol and hydroxytyrosol in aqueous olive leaves extracts using the non-covalent approach [16], as well as for the detection of irinotecan in human plasma using a napthalimide polymerisable derivative (2-allyl-6-[2-(aminoethyl)-amino]napthalimide) as a functional monomer [17]. In the present work, fluorescent polymeric imprinted nanoparticles were synthetized following the non-covalent approach using H-5-CQA **2** as the template. 4 VP **3** and a napthalimide derivative containing a polymerizable vinyl group **7** were used as functional monomers, capable of interacting with the template by relatively weak non-covalent interactions, such as \(\pi\)-staking, hydrogen bonding, hydrophobic interactions, or van der Waals forces (Figure 1).
## 3 Materials and Methods
### Datasets of Speech Audios and Background Noises
#### 3.1.3 Visual Representation of Audios  
Audio signals can be processed as a time-domain or a frequency-domain representation. The former uses the signal as raw audio. The latter uses images of visual representations of the audio. Due to the high complexity of the problem, where the original speech audios and its version with background noise do not match any of the values (increasing the difficulty of a reconstruction problem), we have decided to use the second option as images perform well in auto-encoders. We used autoencoders with convolutional filters of 2 dimensions which have demonstrated better performances in these models than those of 1 dimension [25].  
Many audio representations in the frequency domain are log power spectrograms (LPS), Mel spectrograms, or Mel-frequency cepstral coefficients spectrograms (MFCCS). In this case, we used LPS because it includes an audio feature called power representing wave decibels at a particular moment. LPS consists of an image representing the audio information. In this case, it captures more information than other standard spectrums [26].  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Use Case** & **Number of Audios** & **Length per Audio** \\ \hline \hline Aircrafts & 80 & Around 5 s \\ Storm lights and rain & 18 & Around 5 min \\ Wind & 522 & From 3 s to 5 min \\ Traffic jams & 512 & Around 3 s \\ \hline \hline \end{tabular}
\end{table}
Table 1: Background noise use cases dataset.  
Spectrograms are created using a Python script and a library called librosa, [27], which specializes in music and audio management. The script implements a Short-Term Fourier Transformation (STFT) that converts the audio from the time domain to the frequency domain. Each spectrogram was created using a sliding window of 23 widths and 11.6 steps in milliseconds. The output spectrograms had a size of 256 \(\times\) 256 \(\times\) 1 for each instance. Finally, the dataset contained 60,000 spectrograms, with 15,000 belonging to each use case.
## 3 System Description
### Proposed Solution: BAQALC Algorithm  
BAQALC, the proposed solution for DNA data compression, is explained in this section. The BAQALC solution comprises a compression module and decompression module. The specific flow of each module is shown in Figure 3.  
Figure 3: BAQALC Compression and Decompression Modules.  
In the BAQALC compression module, DNA data is initially input. If it is a multi-thread input, the algorithm is subsequently processed in parallel. As discussed in Section 2.1, DNA FASTQ files are in ASCII characters, which are converted to the according integers. That is, alphabets or characters are converted. Integers are then delta computed, before finally being put into the DNA-optimized LZW algorithm. Here, the delta computation is the difference between the previous and the next integer. As a result, only the differences between the integer samples remain, which contributes to the reduced integer size (except for some exceptions, if the differences are too distant).  
This final step is based on DNA FASTQ-optimized code and a dictionary that has been developed by the authors. In this step we have also developed a bit allocation scheme according to dictionary size. Although many of the specifics cannot be revealed, as an example, one of the randomly selected samples that we have used in the evaluation section could be processed with a dictionary size of 46. This can be bit-allocated within 8 bits into substitute integers from \(-32\) to 31, in which this coverage helped predict the level of redundancy. After this final step, the compressed DNA data output file is constructed.  
The BAQALC decompression module follows the inverse steps of the compression process. After the compressed DNA data is input, it is decoded by the DNA-optimized LZW decompressor (parallel processing if multi-thread). Then, delta is decoded and all converted integers are converted back to their original ASCII characters. If this occurs in a multi-thread, then channels are separated, otherwise not. Lastly, the decompressed DNA data is output losslessly.