esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 High-Level Framework Description
### Extractor and Granulator  
Let \(P\) be an unknown, oriented and possibly complex process to be modeled, where the inputs are annotated graphs and where the output domain is a finite set of class labels. Furthermore, let \(\mathcal{S}\) be an input-output sampling of \(P\) and let \(\mathcal{S}_{\text{tr}}\), \(\mathcal{S}_{\text{val}}\) and \(\mathcal{S}_{\text{ts}}\) be a split of \(\mathcal{S}\) into training, validation and test sets, respectively. The split should be performed so that each subset should share the same statistics, in order to be considered as valid representation of the same process. Moreover, this split must satisfy the following partition properties:  
* The union of the three sets yields the original set: \(\mathcal{S}_{\text{tr}}\cup\mathcal{S}_{\text{val}}\cup\mathcal{S}_{\text{ts}}= \mathcal{S}\);
* The intersection of any two distinct sets is empty: \(\mathcal{S}_{\text{tr}}\cap\mathcal{S}_{\text{val}}=\mathcal{S}_{\text{tr}} \cap\mathcal{S}_{\text{ts}}=\mathcal{S}_{\text{ts}}\cap\mathcal{S}_{\text{val}}= \emptyset\).  
The Extractor is a block that takes as input \(\mathcal{S}_{\text{tr}}\) and returns a bucket \(\mathcal{B}\) of subgraphs drawn from graphs in \(\mathcal{S}_{\text{tr}}\).  
Conversely, the Granulator block takes as input \(\mathcal{B}\) and returns an alphabet of symbols \(\mathcal{A}\subset\mathcal{B}\), namely suitable granules of information, by running a clustering algorithm over \(\mathcal{B}\), possibly electing the representative elements of the clusters as granules of information [13; 14; 15; 28]. In particular, the latter runs a Basic Sequential Algorithmic Scheme (BSAS) [29] clustering algorithm driven by the following parameters:  
* \(\mathcal{Q}\), namely, the maximum number of allowed clusters;
* \(\theta\), namely, the maximum radius for including a pattern into one of the already-discovered clusters;
* A dissimilarity measure \(d(\cdot,\cdot)\) between any two patterns.  
The clustering algorithm addresses the dissimilarity between patterns (i.e., graphs) thanks to a parametric Graph Edit Distance (GED) [30; 31] dissimilarity measure called node Best Match First (nBMF). The interested reader is referred to ([32], Appendix A) for a full mathematical formulation of nBMF. At the end of the clustering procedure, each cluster is evaluated by means of a suitable quality index that jointly takes into account its cardinality (i.e., number of patterns) and compactness (i.e., average pattern-to-center distance) and only the centers of well-formed (i.e., compact and populated) clusters are admitted to be part of the alphabet.  
Since the Extractor and the Granulator blocks are the main focus of this paper, the four variants we aim to investigate will be thoroughly described in Section 3.
# An Effective Adaptive Combination Strategy for Distributed Learning Network
## 1 Introduction
### Motivation and Contribution  
As mentioned above, the classic AC strategy is derived based on MVUE, which is validated to be a feasible criterion [12]. In fact, one of the key techniques in the classic AC strategy [12] is orthogonal projection which is exploited to guarantee the combiners adding up to 1. However, the orthogonal projection technique actually limits the update direction of combiners at each iteration, which can be relaxed to further improve the performance of diffusion LMS algorithm further ahead in Section 3.2.  
In this paper, we still formulate the online adaptive combiners estimation of the ATC algorithm from the perspective of MVUE. Instead of directly exploiting the orthogonal projection technology in [12], we present a non-constrained mean-square deviation (MSD) cost function based on Lagrange multipliers. According to the fixed-point iteration methodology and KKT necessary conditions, we develop an effective adaptive combination strategy, which solely relies on the previous instantaneous intermediate weight estimates without resorting to the knowledge of measurement data and noises. The proposed AC strategy can be seen as the modified and extended version of the classic AC in [12]. Simulations validate the superior performance of the diffusion LMS algorithm when using the proposed AC strategy.  
Notation: \(\mathbb{R}\) and \(\mathbb{C}\) denote the fields of real and complex numbers, respectively. Scalars are denoted by lower-case letters, and vectors and matrices respectively by lower- and upper-case boldface letters. The transpose and conjugate transpose are denoted by \((\cdot)^{\mathrm{T}}\) and \((\cdot)^{\mathrm{H}}\), respectively. \(E\{\cdot\}\) represents expectation. \(\Re(\cdot)\) means the real part. \(\mathrm{col}\{\cdot\}\) stands for the vector obtained by stacking its arguments on top of one another. \(\mathrm{diag}\{\cdot\}\) generates a diagonal matrix using the given diagonal arguments. \([\cdot]_{i}\) stands for the \(i\)th element of a vector. The \(\min\{\cdot\}\) denotes the minimum element of a vector. We define the eigenvalue set of the square matrix \(\mathbf{F}\) as \(\{\lambda(\mathbf{F})\}\), with \(\lambda_{\max}(\mathbf{F})\) denoting the maximum eigenvalue. The spectral radius of the square matrix \(\mathbf{F}\) is denoted by \(\varrho(\mathbf{F})\triangleq\max\{|\lambda(\mathbf{F})|\}\).
# Photocatalytic Inactivation as a Method of Elimination of _E. coli_ from Drinking Water
## 3 Inactivation Process by Photocatalysts
### Metal Phosphides as Photocatalysts for the Inactivation of _E. coli_  
Relatively less attention has been given to the use of phosphides as a photocatalysts, but the use of zinc phosphide has been well investigated [75; 76]. The large abundance of zinc and phosphorus in the earth crust and the possibility of fabricating different morphologies with band gap that is as low as 1.5 eV makes zinc phosphide one of the photocatalysts that could be considered for the inactivation of _E. coli_[77]. The major drawback for the utilization of zinc phosphide is that it has low stability in water [75; 77]. One of the adopted strategies for the improvement of its stability is to functionalize it with organic molecules [76]. [PERSON] et al. used this strategy to improve the stability of zinc phosphide nanowire and boron nitride was used for the functionalization. The functionalized zinc phosphide was used for inactivating _E. coli_ with 5-log of the bacteria inactivated within 300 s under visible light irradiation [76]. However, the photocatalytic activities of the un-functionalized phosphide were found to be better than that of the functionalized phosphide.
## 6 Open Challenges and Related Work
### Open Challenges
#### 6.1.1 Robust to the Interference  
In households, wireless signal transmission faces two problems. First, the room structure is complex, so the signal energy is weakened by many obstructions, such as walls. Moreover, there are many wireless devices, so interference from other devices will affect transmission quality. Some work has been carried out to address this problem. To reduce the SNR of synchronization signals, thereby improving inter-connectivity, [PERSON] [27] uses matched filtering in the form of passive implementation along with cumulant-based processing, which makes this algorithm more insensitive to additive noise. However, this method is only for additive noise. The noise in the actual environment is more complex, so further research is needed.
## 4 Evaluation Results
### Reduction in Operation Time  
According to the standard operating procedure (SOP) for earthquake responses, people who are inside a building should open doors and windows, cut off gas and turn off lights and power before evacuation [28; 29]. Opening windows and doors can prevent the doors or the windows from being jammed by the large deformation caused by an earthquake and can ensure that people are not trapped inside. Another reason for leaving doors and windows open during and after an earthquake is to avoid possible fires or explosions due to a gas leakage inside the building. In addition, cutting off natural gas valves can avoid a possible fire or explosion due to a gas leakage. Furthermore, when a massive earthquake happens, fire can induce thick smoke and cause serious damage. Finally, electrical appliances or computers should be shut off or put into a safe mode in order to avoid possible flames, fire and loss of data. We designed ADRS to automatically perform these important tasks so as to help people evacuate faster and to keep their belongings from being damaged. In order to investigate the effectiveness of ADRS, we first measured the time needed to perform these tasks manually. The operation time of each task includes two parts. The first part is completion time, which is the time needed to complete the task. The second part is the response time, which is the time interval moving from the location of a control device to the location of another device. The response time represents human reaction time. In our experiment, we set the response time to one second. To measure the completion time of a task, we asked eight volunteers to manually perform the task and then found the average. Figure 13 lists the operation time of each task. For example, opening a door takes 3.87 s, opening a window 3.23 s and shutting down a computer 3.61 s. It requires a total of 18.52 s to do all of earthquake tasks manually. With the support of ADRS, all of these tasks are automatically and simultaneously finished in three seconds. As a result, ADRS can reduce the operation time by up to 15 s, which is long enough for people to get under study furniture, or to evacuate from the third floor to the first floor, or to run more than 100 m.
### Applications  
Several applications motivated us to develop the hash-chain fog/edge, which is stated as below:  
* Secure university: All universities within the country can be interconnected for authentication. Henceforth, university students can effectively use facilities within other universities when visiting. These facilities can help them utilize resources for scientific job processing including high-performance servers, CUDA graphics cards, fog/edge testbeds, etc. They can also take advantage of stored resources, research journals, patents, thesis reports, etc;
* Secure Industry 4.0: In Industry 4.0, all the devices can interconnect with each other and share statistics about sensors, manufacturing devices, demand supply operations, overload management, etc. Furthermore, securing them will help avoid malware attacks, protect their IPR/copyrights, and avoid personal/corporate data breaches, phishing, and ransomware;
* Secure government: In this newly coined term, all the government offices can interconnect securely and can improve security for national-level offices, e.g., National Health Insurance (NHI), which was shut down in a major attack, ransomware protection, protection from real estate, fake documents, employment, lottery, or government impersonation fraud, etc.;
* Secure country: In a secure country, WiFi access points can be secured further for IoT devices including traffic lights, temperature sensors, flood sensors, surveillance cameras, power stations, e.g., the U.K. power grid was brought down by attackers. Several infrastructure automation tasks including roads, railways, transport, watercraft ships, airways, communication systems, etc., can be performed.
# Metabolic Engineering _Escherichia coli_ for the Production of Lycopene
## 2 Metabolic Engineering of Two Major Pathways in _E. coli_ for Lycopene Production
### Metabolic Engineering of the Endogenous MEP Pathway in E. coli

Table 1: Summary of the metabolic engineering optimization strategies used for the production of lycopene in _E. coli_. Several key enzymes involved in the biosynthetic pathway were usually co-overexpressed in metabolic engineering. As described, with the co-overexpression of DXS and exogenous carotenoid biosynthetic enzymes, the engineered _E. coli_ strain exhibited lycopene production of 1.3 mg/g dry cell weight (DCW) [32]. Similarly, the combinational overexpression of endogenous DXS and IspA and optimal expression of the four exogenous enzymes of IDI, CrtE, CrtB, and CrtI resulted in lycopene production of 5.2 mg/g DCW [13]. Moreover, the co-overexpression of IDI, DXS, IspD, and IspF in the MEP pathway (Figure 2), showed a 6-fold increase in lycopene production (5.39 mg/g DCW) [28]. Besides the overexpression of the rate-limiting enzymes in the pathway, direct evolution and the optimization of ribosome binding sites (RBS) are conducive for the improvement in lycopene production. RBS libraries were utilized to adjust the expression of _dxs_, _idi_, and the _crt_ gene operon, leading to an increase in lycopene yield by 32% [27]. Similarly, directed evolution was applied to modulate both the enzymatic expression and specific activity of CrtE. A combination of this and DXS overexpression reached above 45 mg/g DCW of lycopene production [33]. [PERSON] et al. constructed a lycopene-indicated high-throughput screening method for isoprene production by performing directed co-evolution of the key enzymes (DXS, DXR, and IDI) of the MEP pathway. The result indicated a potential for pathway optimization in lycopene production [34]. In addition, when the expression of _dxs_, _idi_, and _crt_ operon genes was modulated using the RBS library, a significant improvement in lycopene yield was observed [27]. Figure 2: Metabolic engineering strategies of the entire lycopene pathway in _E. coli_. (The yellow arrow represents gene overexpression; the red “x” represents gene knockout or elimination of the pathway). Pps, phosphoenolpyruvate synthase; Pck, PEP carboxykinase; Ppc, PEP carboxylase; Ldh, lactate dehydrogenase; PoxB, pyruvate dehydrogenase; Ack, acetate kinase; Pta, phosphate acetyltransferase; Zwf, glucose-6-phosphate dehydrogenase; Pgi, glucosephosphate isomerase; GdhA, glutamate dehydrogenase; PykFA, pyruvate kinases; AceE, pyruvate dehydrogenase; FdhF, formate dehydrogenase H.  
Most research has been focused on improving activities of the desired enzymes via conventional strategies, such as overexpression, direct evolution, and RBS optimization for lycopene production using the MEP pathway. However, fewer studies have been performed to investigate the regulatory mechanisms of the metabolic pathway. Therefore, further understanding of the regulatory mechanism of the MEP pathway and the combination of different strategies for lycopene production in _E. coli_ need to be explored in the future.
## 3 Results and Discussion  
### Feature Extraction and Scaling  
A few basic features were first extracted from the SAWP. Then, a few more advanced features were created by combining the basic features. A total of ten features were extracted and these features are listed in Table 3. The features are min-max scaled so that the features have a range between 0 to 1. Normalising each feature to the range 0 to 1 range is equivalent to min-max scaling.
# Research on Optimization of Target Positioning Error Based on Unmanned Aerial Vehicle Platform
## 2 Definition of a Coordinate System
### Geodetic Coordinate System \((O-BLH)\)  
The origin of the WGS84 coordinate system is located at the geometric center of Earth's ellipsoid, coinciding with Earth's center of mass. The geodetic latitude \(B\) is defined as the angle between the ellipsoid normal and the plane of the equator at a given point in space. This angle is measured using the equator as the baseline, following the principle of positive north and negative south, and its range of variation covers the global latitude domain from \(-90^{\circ}\) to \(+90^{\circ}\), which comprehensively maps the latitudinal variation in Earth's surface. The determination of the geodesic longitude \(L\) is based on the angle between the meridian plane where the space point is located and the primary meridian plane. This angle is also based on the primary meridian, following the rule of positive associated with the east and negative associated with the west, with a range of values spanning from \(-180^{\circ}\) to \(+180^{\circ}\). Geodetic elevation \(H\) quantifies the vertical distance from a space point to the surface of the ellipsoid, with a positive value given for being above the ellipsoid and a negative value given for being below the ellipsoid. The coordinates of a point can be expressed as \((B,L,H)\).
## 1 Introduction
Therefore, beyond the pleural-line, ultrasound images cannot be considered to be an anatomical representation of the lung structure. However, when considering the typical frequency range employed for ultrasound medical imaging, say 1-10 MHz, the wavelength of the corresponding pressure waves is small enough, i.e., from 0.15 to 1.5 mm, to be able to feel even small alterations in the lung structure. Consequently, different artifacts can be produced by the application of standard image reconstruction algorithms to these signals [20]. In this case, the target of ultrasonography is represented by several pathologies involving peripheral lung that do not determine parenchymal consolidation with focal or diffuse extension. It is the case of fibrosing interstitial lung diseases, early septal cardiogenic pulmonary edema, cardiogenic pulmonary edema with alveolar flooding, acute respiratory distress syndrome, pulmonary hemorrhage,and focal or diffuse inflammatory abnormalities [4; 5]. Generally, the main diagnostic tool for these pathologies is chest CT scan. Obviously, Chest CT scan is able to provide morphological and panoramic views of these pathologies. In these contexts, different artifacts provide different information for clinicians, which is useful to get both the correct diagnosis and to indicate the correct diagnostic process. The final goal of chest ultrasonography and artifacts analysis in these pathologies is not to substitute chest CT scan, but to become the fifth pillar of medical examination, providing signs to clinicians not obtainable by classic semiotic [8]. Finally, when lung is normally inflated, the anatomic representation, even more so, is not possible. The normal pleural-line acts essentially as a specular reflector to ultrasound waves, resulting in the visualization of reverberation artifacts of the pleural-line, and both mirror and replica effects of the chest wall are visible. This so-called \"normal pattern\", when characterized by the detection of lung points and by the absence of sliding sign, is indicative of pneumothorax [20; 21]. In conclusion, chest ultrasonography has the potential to help physicians facing different pathologic conditions afflicting the respiratory system, especially in case of acute onset dyspnea. The BLUE-protocol (Bedside Lung Ultrasound in Emergency) is an example, and it has been proposed as an easy and feasible approach to acute dyspnea, reaching 90.5% of accuracy and quickly providing appropriate diagnosis [22]. In this review, the acoustic properties of the normal and pathological pleural-line will be discussed together with the acoustic behavior of the sub-pleural lung when the pleural-line is not a strong near-perfect reflector.
## 3 Results and Discussions
### Groundwater Vulnerability Using DRASTIC Index  
Figure 10 shows the calculation of the DRASTIC index in the Tebessa-Morsott alluvial aquifer, classified in three classes of vulnerability: low, medium and high. The classes of average and high vulnerability cover more than 90% of the area. The aquifer is characterized by an average-high vulnerability, which is also negatively influenced by agricultural activities and urban discharges (Morsott, Hammamet and Bekkaria cities). However, in these localities were implanted the majority of boreholes for drinking-water supply and agricultural needs. These areas must now be subject to rigorous control to define the appropriate protective measures. The increase in the degree of vulnerability is mostly related to the pedological characteristics, vadose zone media and aquifer material (permeable).
## 2 Formulation of Optimal Scheduling of Wind-Hydro-Thermal System
### Set of Constraints and Wind Model  
#### 2.2.1 Constraints from Hydropower Plants  
Hydropower plants are constrained by limits of reservoirs, turbines, and generators. The detail is expressed as follows:  
_Water Balance Constraint:_ The reservoir volume at the \(i^{th}\) considered subinterval is always related to the volume of previous subinterval, water inflow, and water discharge. All the parameters must be supervised so that the following equality is exactly met.  
\[RV_{hp,i-1}-RV_{hp,i}+WI_{hp,i}-Q_{hp,i}=0,\ i=1,\ 2,\ldots,N_{s} \tag{2}\]  
Note that \(RV_{hp,i-1}\) is equal to \(V_{hp,0}\), if \(i=1\), and \(RV_{hp,i}\) is equal to \(RV_{hp,Ns}\), if \(i=N_{s}\).  
_Initial and Final Volumes Constraints:_\(V_{hp,0}\) and \(V_{hp,Ns}\) in constraint (2) should be equal to two given parameters, as shown in the model below.  
\[RV_{hp,0}=RV_{hp,start} \tag{3}\]  
\[RV_{hp,N_{s}}=V_{hp,end} \tag{4}\]  
For each operating day, initial volume, \(RV_{hp,start}\), and final volume, \(RV_{hp,end}\), of each reservoir are required to be always exactly met.  
_Reservoir Operation Limits:_ Water volume of reservoirs must be within the upper and lower limits in order to assure that the water head is always in operation limits. Therefore, the following inequality is an important constraint.  
\[RV_{hp,min}\leq RV_{hp,i}\leq RV_{hp,max},\ \left\{\begin{array}{l}\mathit{ hp}=1,\ 2,\ldots,\ N_{h}\\ i=1,\ 2,\ldots,N_{s}\end{array}\right. \tag{5}\]  
_Limits of Discharge Through Turbines:_ Turbines of each hydropower plant is safe, if the water discharge through them does not exceed the limits. Both upper and lower limits have a huge meaning for the safety and stable operation of turbines. Thus, the following constraints are considered.  
\[q_{hp,min}\leq q_{hp,i}\leq q_{hp,max},\ \left\{\begin{array}{l}\mathit{ hp}=1,\ 2,\ldots,\ N_{h}\\ i=1,\ 2,\ldots,N_{s}\end{array}\right. \tag{6}\]  
where \(q_{hp,i}\) is determined as follows:  
\[q_{hp,i}=x_{hp}+y_{hp}PH_{hp,i}+z_{hp}\big{(}PH_{hp,i}\big{)}^{2} \tag{7}\]  
In addition, the total discharge of each subinterval is determined as follows:  
\[Q_{hp,i}=t_{i}q_{hp,i} \tag{8}\]  
_Limits of Hydropower Plant Generators:_ The power generation of each hydropower plant must follow the inequality below, to assure the safe operation of generators all the time.  
\[PH_{hp,min}\leq PH_{hp,i}\leq PH_{hp,max},\ \left\{\begin{array}{l}\mathit{ hp}=1,\ 2,\ldots,\ N_{h}\\ i=1,\ 2,\ldots,N_{s}\end{array}\right. \tag{9}\]