esa-sceva/satcom-chunk-collection huggingface dataset:
# The Process of Natural and Styrene-Butadiene Rubbers Biodegradation by _Lactobacillus plantarum_
## 2 Materials and Methods
### Culture Condition  
The modified Schramm-Hestrin nutrient medium was used for the cultivation of bacteria. It was composed of 20 g of glucose, 5 g of yeast extract, 5 g of aminobak, 1.15 g of citric acid, 2.7 g of Na\({}_{2}\)HPO\({}_{4}\), and 0.5 g of MgSO\({}_{4}\) per 1000 mL of water [16]. Because it is known from the literature that changing the carbon source in the culture media may result in a different cellulose structure, glucose was removed and replaced by other additives in all experiments [17; 18]. In each case, the medium was inoculated with a pre-culture of the _Lactobacillus plantarum_ LOCK 1145. The tests used 5 mL of bacterial inoculum per 100 mL of Schramm-Hestrin medium. Bacterial cellulose was cultivated in many different square-shaped culture plates. All experiments were conducted with the use of different styrene-butadiene and natural rubber mixtures. The composition of the styrene-butadiene mixture was butadiene rubber 100 parts by weight, technical stearin 1 part by weight, zinc white 3 parts by weight, HAF carbon black (N330) 50 parts by weight, thiohexane CBS accelerator 1 part by weight, and grade II ground sulfur 2 parts by weight. The composition of the natural rubber mixture consisted of 100 parts by weight, technical stearin 2 parts by weight, zinc white 5 parts by weight, HAF carbon black (N330) 45 parts by weight, thiohexane CBS accelerator 0.5 parts by weight, and grade II ground sulfur 2.5 parts by weight. The mixtures were prepared according to the BN-72/BN 6031-03 standards [19]. In each case, different mixtures of natural rubber were added to the culture media, which was prepared without glucose. The following mixtures, which are shown in Table 1, were separately added to the glucose-free culture medium. The authors would like to emphasize that the liquid culture medium was glucose-free in all experiments. Rubber waste mixtures were the only carbon source for bacteria. In each case, the cultivation of the _Lactobacillus plantarum_ LOCK 1145 was continued in proper conditions (30 \({}^{\circ}\)C degrees, pH value 5.6-5.8 oxygen condition) for 14 days. At the end, a precise rinse process was executed. Cellulose membranes were rinsed with water, then with 1% NaOH, again with water, then with 1% CH3 COOH, and finally, with water again. Each step took at least 24 h. After the rinsing process was completed, BNCs were sliced, lyophilized, and used for preparing paper-layered compositions. The presence of cellulose on the surface of the bioreactors indicated the activity of bacteria and their metabolic processes, during which rubber waste was biodegraded. An analysis of the elemental composition of rubber waste was conducted with a statistical analysis. During this, the average carbon content in samples before and after the culture processes was the most important factor. In experiments where bacterial activity was observed, mass balances were carried out. We checked the weight of rubber waste before and after the culturing process.
## 2 Related Works
### Open Issues and Challenges
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Name of the Proposal** & **Advantages** & **Disadvantages** & **References** \\ \hline Deadline-Constrained & Accurate definition of information transfers in the transmission medium. & Works at a lower level (physical and network access layers rather than middleware or data-based ones). & [PERSON], [PERSON], and [PERSON], _A Deadline-Constrained_ 802.11 MAC Protocol With QoS \\ \hline Constrained Application Protocol & PDU definition and interchange are thoroughly described. It has been designed for constrained environments. & & Internet Engineering Task Force (IEIT), _The Constrained_ \\ \hline Advanced Message Queuing Protocol & Set of PDUs for information transmission at the data level. It publish/Subscribe communications. & & Conceived for reliable transmission mediums rather than an underwater channel. Adding security can be challenging. & \\ \hline MACA-based power control & Reliable performance in underwater environments where bits are transmitted. & Focused on bit transmission, rather than data level with higher level information. & & [PERSON], [PERSON], [PERSON] and [PERSON]. _A MACA-based power control MAC protocol for Underwater Wireless Sensor Networks_[27]. \\ \hline Power-efficient routing protocol & Optimized scheme for bit transmission. & It is not a suitable solution for transmissions at the data level. & [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON]. _A power-efficient routing protocol for underwater wireless sensor networks_[28]. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summarized advantages and disadvantages of the studied proposals.
## 4 Potential Applications in Nanopore Technology, Vaccine Development, and Tumor Therapy
### Nanopore Technology  
The structural properties (protein channels) of PFTs, including ClyA, are widely utilized as biological \"nanopore\" systems that enable single-molecule analysis without la beling, chemical modification, or surface immobilization [73; 74]. In 1996, [PERSON] et al. established the proof of concept of nanopores, an architectural type of biological machinery, using a membrane-embedded \(\alpha\)-hemolysis channel [75]. One of the most recognized examples of the use of nanopores is the \"MinION\" sequencer (Oxford Nanopore Technology Ltd., Oxford, UK), which is integrated with a nanopore, and is used for genome DNA sequencing to obtain long read sequences [76; 77; 78]. Although the quality of the obtained sequences at present is not high compared with that of short reads from the Illumina platform, this nanopore sequencing technology enables simpler and more rapid determination of complete genome sequences, especially for organisms with small replicon sizes, such as bacteria and viruses [79; 80; 81; 82].  
The [PERSON] group first demonstrated that ClyA can accommodate natively folded proteins within its nanopore lumen [83] and have subsequently reported the utility of ClyA as biological nanopore for the detection of single macromolecules in multiple advanced studies [84; 85; 86; 87; 88]. In a study by [PERSON] et al., ClyA was used to develop an electrode-free nanopore sensing method that enables optical monitoring of single-molecule events without any electrical connections [89]. Thus, recent studies have shown the potential for ClyA to serve as a biological nanopore, which in the future could be integrated into miniaturized, low-cost devices for use in medicine, industry, environmental monitoring, or for single-cell analysis.
## 3 Experimental Validation
### Implementation Details
#### 3.2.2 Model Training  
Since the proposed MCMS attention module is designed to be plug-and-play, a backbone network is needed for validation. In our experiments, we chose ResNet50 as the backbone CNN, where the MCMS attention module can be plugged into certain convolutional layers. For training an MCMS-assisted ResNet50, we set the batch size to 15 and the start learning rate to 3e-4, with a warmup factor of 10. Three reduction ratios 16, 32, and 64 were used in the multi-channel attention layer, and three kernel sizes, including 3, 5, and 7, were used in the multi-spatial attention layer. The choice of reduction ratios and kernel sizes was based on empirical results.
# Pore Water Pressure Prediction Based on Machine Learning Methods--Application to an Earth Dam Case
## 3 Application Case: Montbel Dam, an Existing Earth Dam  
### Description of the Case Study  
This case study is a 36 m high earth dam used for irrigation, located in the region of Occitanie in France. Its reservoir has a volume of 60 million m\({}^{3}\), and the normal water operating altitude level (400 m.a.s.l.) is 33.5 m above the altitude of the reservoir bottom (366.5 m.a.s.l.). The dam studied is a homogeneous embankment dam made of marl with very low permeability. The dam was built between 1982 and 1985. The body of the dam is equipped with a semi-vertical drain extended horizontally by a drainage mat.  
Piezometers are used to measure pore water pressure in the soil mass of the dam. They provide significant quantitative data on the magnitude and distribution of pore water pressure with time. Forty-five automatic piezometers (PWP cells) were distributed  
Figure 4: The structure of the GRU.  
at different positions of the dam. They were used to measure PWP inside the dam and the foundation.  
Although the selected monitoring section has 10 sensors, some monitoring data are in poor regularity, with interrupted monitoring or recording errors. Therefore, the most representative four monitoring points (with the completed dataset, marked with red points in Figure 5, including C2 (upstream of the dam body), C5 (downstream of the dam body), CCF1 (foundation of the dam), and C24 (near the filter) are selected for the building prediction model.
## 2 Materials and Methods
### Data
#### 2.2.3 Ancillary Data  
To assess the ability of SIF to monitor dynamic changes in NPP, we selected five environmental parameters commonly used for the estimation of NPP and analyzed the sensitivity of SIF to these environmental parameters. These environmental parameters  
Figure 1: Location of the HHH Plain and land use types in the region.  
included leaf area index (LAI), NDVI, land surface temperature (LST), fraction of absorbed photosynthetically active radiation (FAPAR), and precipitation (PRE).  
The LST dataset was derived from the MOD11A2 product, which has a temporal resolution of 8 days and a spatial resolution of 500 m. The NDVI dataset was calculated based on the red and near-infrared bands of MOD09A1. This dataset has a temporal resolution of 8 days and a spatial resolution of 500 m. The FAPAR dataset was derived from the GLASS FAPAR product, which has a temporal resolution of 8 days and a spatial resolution of 0.05\({}^{\circ}\). The GLASS FAPAR dataset calculates FAPAR values based on photosynthetically active radiation (PAR) transmittance throughout the canopy, thereby ensuring physical consistency between the LAI and FAPAR products [42]. GLASS FAPAR products have better quality and accuracy than similar datasets [43]. The LAI dataset was derived from the GLASS LAI product, which has a temporal resolution of 8 days and a spatial resolution of 0.05\({}^{\circ}\). The GLASS LAI dataset is a true LAI generated using general regression neural networks (GRNNs) [44] that have been validated to have high accuracy and quality, as well as good spatial and temporal continuity, temporal stability, and vegetation phenology representativeness [45]. The PRE data were obtained from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS)-2.0 dataset [46], which combines climatology, 0.05\({}^{\circ}\) resolution satellite images, and in-situation data to form a gridded rainfall time series, showing great potential in trend analysis and seasonal drought monitoring.
# Nonlinear Tank-Level Control Using Dahlin Algorithm Design and PID Control
## 2 Materials and Methods
### Controller Design
#### 2.3.1 The Dahlin Controller Design  
This algorithm of digital controller parameters setting is applied in the control systems, in which time constants are significantly higher than the transport delay and when it is desired that the controlled variable has an aperiodic response to a step signal at the input in the closed feedback loop [27; 28; 29; 30; 31].  
The standard control structure of the Dahlin algorithm is shown in Figure 4, where \(T\) is the sampling time, D/A is zero-order hold (ZOH) with the transfer function \(G_{h}(s)=\frac{1-e^{-T_{h}}}{s}\), and \(D(z)\) represents the Dahlin controller.  
According to this algorithm, the desired aperiodic step response with a time constant of \(1/\lambda\) and transport delay \(T_{d}=NT\) is adopted as shown in Figure 5.  
Figure 4: The control structure of the Dahlin algorithm.  
Figure 5: Desired step response with the Dahlin controller.  
The complex form of this response is:  
\[C(s)=\frac{\lambda}{s(s+\lambda)}e^{-N\tau_{\rm S}}. \tag{14}\]
## 3 Results and Discussion
### Search for Resistance and Virulence Genes in Reference Genomes
These proteins are found mainly in the cell walls of microorganisms and, in addition to fixation, can facilitate transport between organisms, contributing to the success of pathogenesis [114]. This mechanism is frequently observed in bacteria of the genus _Acinetobacter_, considered a critical pathogen for human health [114]. This in silico work confirmed this characteristic, identifying that species of this genus (_A. albensis_ ANC4874 and _A. pseudolwolfi_ WB5) presented 12 different types of genes related to adherence, corresponding to 35.3% of the total identified (Figure 10B). Furthermore, this genus was the only one in our analysis to have the _plcD_ gene, classified as an exotoxin in the VFDB database. This exotoxin helps the microorganism through lysis, contributing to invasion [115; 116]. For the exclusive BHMT reference genome, _Macrococcus caseolyticus_ FDAARGOS 868, the presence of five virulence genes was observed, two from the cap family (_cap8E_ and _cap8O_) related to immune modulation, two from the _clp_ family (_clpP_ and _clpC_) with function of stress survival, and one, _tufA_, related to adherence. Among the species that presented the highest number of virulence genes identified, the most notable are _R. ornitholytica_ NCTC9164, _P. weihenstephanensis_ TMW2 1728 1, _P. lundensis 2T_2\(5\)2, _P. fluorescens_ ATCC 13525, and _P. agglomerans_ FDAARGOS 1447 with 93, 89, 86, 79 and 57 genes, respectively. It is important to consider that the species _R. ornithinolytica_ NCTC9164 and _P. agglomerans_ FDAARGOS 1447 also had the highest number of genes related to antibiotic resistance. [PERSON] et al. [27] warn in their work about the need to investigate the presence of other species of bacteria in dairy products, not just those of recognized importance. Our survey shows that species of apparently minor importance can present a risk to consumers' health and, eventually, become emerging pathogens in the future. It is also important to highlight the presence of other virulence mechanisms, such as motility and biofilm formation. The presence of genes from the mot family, found in the genus _Pseudomonas_, are responsible for bacterial flagellar movement and, consequently, act in a chemotactic manner, interacting with other organisms [117]. On the other hand, we have the presence of flagella, represented by genes from the fli family, which, in addition to helping in the motility process, play a crucial role in the formation of biofilms [118]. Biofilms facilitate adhesion between bacteria, favoring the process of horizontal gene transfer, which can make the fermented food production process extremely delicate [108]. The species _A. johnsonii_ ANC3681, _A. ursingii_ NIPH706, _A. otitis_ ATCC51267, and _T. pyogenes_ TP6375 did not present virulence genes found in the analysis and, therefore, were not represented in Figure 10.
# Design and Implementation of a Multi-Function Hydrophone for Underwater Acoustic Application
## 2 System Overview
#### 2.1.1 The Pre-Amplifier  
In order to amplify the weak signals, a second-order pre-amplifier is utilized. The integrated chip AD620 is used as the first pre-amplifier. AD620 chip is an instruction amplifier [20], and the gain range is from 1 V/V to 10,000 V/V with extremely low noise, where V/V represents the ratio unit of output voltage to input voltage. The gain of AD620 can be adjusted by a resistor \(R_{3}\) as shown in Figure 3a. The input for AD620 can be single end or differential. The input impedance of AD620 (Analog Devices, Inc., Norwood, MA, USA) is 10 M\(\Omega\), which is good for improving the signal to noise ratio (SNR). Moreover, the AD620 chip has some characteristics, e.g., low input offset voltage and input offset drift, high common-mode rejection ratio, etc. A pre-amplifier with an adjustable gain is a good method to counteract the attenuation. Since the MCU contains rich general purpose input output (GPIO), digitally controlled programmable gain amplifier is chosen in our proposed system. As a result, the integrated chip LTC6910-2 ((Analog Devices, Inc., Norwood, MA, USA)) is adopted as a second pre-amplifier as shown in Figure 3b. The gain can be configured as 0 V/V, 1 V/V, 2 V/V, 4 V/V, 8 V/V, 16 V/V, 32 V/V, and 64 V/V, respectively, [21]. Especially, 0 V/V means the input circuit is open while the output is active.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Value** & **Parameter** & **Value** \\ \hline Height & 450 mm & Diameter & 60 mm \\ Weight & \(\approx\)2.5 kg in the air & Power consumption & 1.8 Watt \\ Working time & 7 days & Capacity of SD card & maximum 2 TB \\ Bandwidth & 20 Hz–200 kHz & Sensitivity & \(-\)205 dB @ V/μPa \\ Maximum sampling frequency & 256 kSPS & Maximum gain & 56.1 dB \\ Average self-noise & no more than 0.1 mV & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of the multi-function hydrophone.  
Figure 3: Pre-amplifier. (**a**) The circuit of AD620. (**b**) The circuit of LTC6910-2.  
Figure 2: Signal process component.
# Security Attack Behavioural Pattern Analysis for Critical Service Providers
## 4 Cyber Attacks  
### Classification of Security Events  
The data treatment process was carried out in four stages. During the first stage, all IT-incidents reported between 1 April 2019 and 1 April 2023 were gathered, and the incidents describing malicious events were singled out. The remainder were excluded from the dataset. During the second stage, the IT-incident reports were categorised according to **vulnerability**, **attack-mechanism** and **security events**, and **attack target**, and the results transformed into a similar, quantifiable format. The incidents that did not provide enough information for the incident to be classified in accordance with each classifier were categorised as **unknown**. The third stage of the data treatment process included summarising the quantities found within each category to be able to compare the frequencies.  
During the period from April 2019 to 2023, (MSB) received a total of 1332 IT-incident reports from major service providers. Out of the total reports, 256 were submitted by organisations in the (NIS) sector, while the remaining 1076 were submitted by government agencies. Among the entire dataset, 254 reports contained detailed accounts of incidents that were ascribed to intentional and malicious acts. The remaining incidents were ascribed to a range of causes, including technician and user errors, system malfunctions, natural occurrences, and unidentified variables. Moreover, the frequency of the reported cyberattacks from April 2019 to 2023 has consistently maintained a stable level. During the period spanning from 1 April 2019 to 2020, there was a substantial increase in reported cyberattacks, reaching a total of 73 incidents. Afterwards, in the time period of 2022-2023, a total of 67 cyberattacks were reported. During the period from 2020 to 2021, there was a significant rise in cyberattacks, with a total of 61 reported cases. From April 2021 to 2022, there was a limited occurrence of cyber attacks that specifically focused on important service providers. The number of reported incidents totaled only 53 occurrences.
# Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles
## 4 Integrating Electric Vehicles into Smart Cities: Challenges and Opportunities
### Cybersecurity Challenges  
The integration of electric vehicles (EVs) into smart cities requires the development of intelligent transportation systems (ITS) that enable seamless communication between EVs, the charging infrastructure, and the city's transportation network. However, the implementation of ITS solutions for EVs in smart cities is also subject to cybersecurity challenges. One of the most significant challenges is the risk of cyber attacks on the communication systems that connect EVs to the city's transportation network. Hackers could potentially exploit vulnerabilities in the communication systems to gain unauthorized access to sensitive data, such as location information, the personal information of drivers, and even control over EVs. To prevent such attacks, stakeholders must ensure that the communication systems are secure and use encryption to protect data at rest and in transit.  
Another challenge is the risk of cyber attacks on the charging infrastructure. EV charging stations are connected to the internet and are vulnerable to attacks that could compromise the security and reliability of the charging network. Hackers could potentially exploit vulnerabilities in the charging infrastructure to gain unauthorized access to the charging network, overload the grid, or even cause physical damage to the charging stations. To address this challenge, stakeholders must ensure that the charging infrastructure is secure and uses encryption to protect data at rest and in transit.  
The integration of EVs into smart cities also requires the development of secure software applications that can enable seamless communication between EVs and the city's transportation network. Software engineers must ensure that the software applications are secure and follow best practices for secure software development, such as input validation, error handling, and secure coding. Additionally, software engineers must ensure that software applications are regularly updated and patched to address any security vulnerabilities that may arise.  
Finally, the integration of EVs into smart cities requires the development of secure data analytics tools and techniques that can process and analyze a large number of data in real time while protecting the privacy and security of users' data. To address this challenge, stakeholders must ensure that data analytics tools and techniques follow best practices for secure data processing, such as data anonymization, data minimization, and data encryption. Additionally, stakeholders must ensure that data are only accessible to authorized personnel and are protected from unauthorized access and disclosure.
## 3 Materials and Methods
### Landslide Susceptibility Assessment
#### 3.3.2 Modeling Techniques
Key parameters that were tuned included max_depth, min_samples_split, min_samples_leaf, and max_features. The optimal parameters found were max_depth = 7, min_samples_split = 5, min_samples_leaf = 3, and max_features ='sqrt'. For our small dataset, we favored smaller max_depth values and larger min_samples_split/min_samples_leaf to build more generalized trees. After tuning, models were evaluated on a validation set. If one model significantly outperformed the other (difference in accuracy > 1%), the better model was chosen. If performance was similar, a weighted ensemble was used, where the final prediction was a weighted average of SVM and RF outputs, with weights inversely proportional to validation error. * Extreme Gradient Boosting (XGBoost)  
XGBoost is a tree-based ensemble learning method that builds models sequentially, where each new tree corrects the residuals of the previous ones. It minimizes a regularized objective function [41]:  
\[\mathcal{L}=\sum_{i=1}^{n}l\left(y_{i},\hat{y}_{i}^{(t)}\right)+\sum_{k=1}^{t }\Omega(f_{k}) \tag{3}\]  
where \(l\) is a differentiable loss function (e.g., log loss), and \(\Omega\) is a regularization term that penalizes model complexity. After establishing the model framework, we performed hyperparameter tuning to optimize performance. We employed both L1 (reg_alpha) and L2 (reg_lambda) regularization to penalize the weights of the leaf nodes, along with Early Stopping to prevent excessive boosting iterations. The optimal reg_lambda (L2) was 1.0, and the optimal reg_alpha (L1) was 0.01. We used Early Stopping by monitoring performance on a validation set; training halted if validation performance did not improve for 20 early_stopping_rounds. Other crucial regularization parameters for XGBoost were also tuned, with optimal values including max_depth = 4, min_child_weight = 1, subsample = 0.8, and colsample_bytree = 0.7.