esa-sceva/satcom-chunk-collection huggingface dataset:
# Towards Trust and Friendliness Approaches in the Social Internet of Things
## 4 Classification of Trust- and Friendliness-Based Approaches in the Social IoT
### Service Composition  
Direct service composition is a collection of honesty, community-interest, and cooperativeness values, which are assigned by node i to node j, mainly based on direct observation and interaction between the two nodes [28]. This is generally referred to as direct composition. Indirect service composition is collected through feedback from friends or someone's recommendations. If the two nodes have never interacted in the past, node i will consider indirect trust, which is based on the observations and past experiences of other connected nodes. [PERSON] et al. [43] used a similar definition in their study by developing a filter scheme for trust management. Their designed scheme is used to combine direct and indirect trust. Moreover, a weighted sum function was designed. This function is used to aggregate trust. In their model, the trustor and trustee do not have any past experiences. Moreover, trust is entirely based on a friend's opinion and can be transitive.  
In Abderrahim, Elhdhili [44], the authors proposed a system mainly based on communication interests. The novelty of their work is based on three aspects. First is a set of nodes known as a community of interest (COI). Each set of nodes shares the same type of interest, controlled by the administrator. The second aspect prevents ON/OFF attacks, and the last aspect covers predictions. These aspects are handled by a Kalman filter. The system integrates both direct and indirect trust; however, it is not capable of handling a number of attacks.
## 2 Results
### Changes in pH and TA during Fermentation  
The changes in pH and TA during fermentation are shown in Figure 1. The pH and TA of the fermented milk in the five groups of mixed starter cultures of _L. delbrueckii_ subsp. _bulgaricus_ IMAU20312 and _S. thermophilus_ IMAU80809 and the control strain showed opposite trends. At the beginning of fermentation, the pH of all samples was 6.51 (A1), 6.57 (A2), 6.66 (A3), 6.65 (A4) and 6.69 (A5), and the TA was 19.3 (A1), 18.6 (A2), 18.65 (A3), 19.4 (A4) and 18.85 (A5) \({}^{\circ}\)T, which was not significantly different from the control (\(p\) > 0.05). The TA of the samples continued to rise and stayed below 100 \({}^{\circ}\)T throughout fermentation. At the end of fermentation, the highest TA (86.15 \({}^{\circ}\)T) was achieved in the A1 sample, but it was still lower than that of the control (97.5 \({}^{\circ}\)T).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Fermentation Time (h)**} & \multicolumn{4}{c}{**Viable Cell Counts (\(\times\)10\({}^{7}\) CFU/mL)**} \\ \cline{3-6}  & & **0 h** & **2 h** & **4 h** & **6 h** & **8** \\ \hline A1 & 6.5 & 0.55 \(\pm\) 0.02 \({}^{\text{a}}\) & 0.53 \(\pm\) 0.01 \({}^{\text{e}}\) & 0.68 \(\pm\) 0.09 \({}^{\text{d}}\) & 3.14 \(\pm\) 0.04 \({}^{\text{c}}\) & 5.73 \(\pm\) 0.01 \({}^{\text{a}}\) \\ A2 & 7.2 & 0.59 \(\pm\) 0.05 \({}^{\text{a}}\) & 0.65 \(\pm\) 0.03 \({}^{\text{d}}\) & 0.86 \(\pm\) 0.03 \({}^{\text{cb}}\) & 3.23 \(\pm\) 0.35 \({}^{\text{c}}\) & 5.75 \(\pm\) 0.05 \({}^{\text{a}}\) \\ A3 & 7.5 & 0.70 \(\pm\) 0.06 \({}^{\text{a}}\) & 0.96 \(\pm\) 0.02 \({}^{\text{a}}\) & 1.09 \(\pm\) 0.13 \({}^{\text{a}}\) & 3.85 \(\pm\) 0.13 \({}^{\text{b}}\) & 5.68 \(\pm\) 0.55 \({}^{\text{a}}\) \\ A4 & 8.0 & 0.65 \(\pm\) 0.35 \({}^{\text{a}}\) & 0.71 \(\pm\) 0.01 \({}^{\text{cd}}\) & 0.81 \(\pm\) 0.04 \({}^{\text{cd}}\) & 1.69 \(\pm\) 0.16 \({}^{\text{d}}\) & 5.69 \(\pm\) 0.76 \({}^{\text{a}}\) \\ A5 & 7.4 & 0.68 \(\pm\) 0.05 \({}^{\text{a}}\) & 0.82 \(\pm\) 0.03 \({}^{\text{b}}\) & 0.9 \(\pm\) 0.07 \({}^{\text{cb}}\) & 4.38 \(\pm\) 0.16 \({}^{\text{a}}\) & 5.59 \(\pm\) 0.55 \({}^{\text{a}}\) \\ JD & 7.2 & 0.64 \(\pm\) 0.32 \({}^{\text{a}}\) & 0.72 \(\pm\) 0.07 \({}^{\text{c}}\) & 0.96 \(\pm\) 0.02 \({}^{\text{ab}}\) & 3.76 \(\pm\) 0.15 \({}^{\text{b}}\) & 5.70 \(\pm\) 0.08 \({}^{\text{a}}\) \\ \hline \hline \end{tabular} Note: Figures in the same column followed by different lowercase letters indicate that they are significantly different from each other (\(p\) < 0.05). The second column represents the time at which the fermented milk samples reached the end of fermentation.  
\end{table}
Table 1: Changes in viable cell counts of yogurts produced during fermentation using different ratios of _L. delbrueckii_ subsp. _bulgaricus_ IMAU20312 and _S. thermophilus_ IMAU80809 in starter cultures compared with the commercial starter culture.
# Glass Ceramic with Improved Structure and Properties Made with Wastes from FeNi Production
## 2 Characterization of Main Industrial Wastes  
The metallurgical waste used is from the FENI INDUSTRY ferronickel smelting plant in the Republic of North Macedonia. The initial stage of the production is related to a pre-reduction of the ores in a rotary kiln, which produces a waste in the form of filter dust, D. During the second stage of reduction smelting, raw ferroalloy and electric arc furnace slag, collectively known as EFS (which is the main waste stream), are produced. At the final manufacturing stage, during the refining of the ferronickel alloy, another type of slag, one which contains huge amounts of iron oxides, is formed, namely, CS.  
The chemical compositions of these wastes were analyzed by XRF spectrometer (XRF ARL 9900), and the corresponding results are reported in Table 1. The EFS stream is rich of silica, iron oxides and MgO, which means that it might be a possible material for an additional vitrification. D waste is fairly similar, while CS is mostly composed of the iron oxides CaO and MgO.  
The major crystal phases in EFS and D are various silicates, such as olivine, plagioclase and quartz, while iron oxides are present in CS. All of these crystal phases are results of the high temperature of the production treatments, which, however, is an advantage for the eventual vitrification procedure, since the glass batch can be dense and non-foaming.  
The chemical durability of the wastes used was valued by TCLP (toxicity characteristic leaching procedure) for 24 h at pH = 5.0 \(\pm\) 0.2 (controlled by 0.5 M acetic acid). The resulting values, which are reported in Table 2, surpass the permissible limits for non-hazardous wastes for several metals [23]. It is evident that Zn, Ni, and As are problematic in the dust and Ni and Cr in the electric-furnace slag and the converter slag. In addition, very high concentrations of iron in the solutions from EFS and CS are also measured.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \multicolumn{6}{c}{**Wastes**} \\ \hline  & **EFS** & **D** & **CS** & **WM** & **GC** & **WG** \\ \hline wt \% & 56 & 7 & 7 & 70 & 30 & 100 \\ SiO\({}_{2}\) & 53.0 & 41.1 & 1.4 & 47.8 & 71.7 & 55.2 \\ Al\({}_{2}\)O\({}_{3}\) & 2.0 & 2.8 & 0.3 & 1.9 & 0.6 & 1.5 \\ MgO & 16.9 & 16.0 & 4.2 & 15.9 & 3.3 & 12.1 \\ CaO & 2.4 & 2.5 & 15.4 & 3.5 & 9.8 & 5.4 \\ Cr\({}_{2}\)O\({}_{3}\) & 2.5 & 1.1 & 0.2 & 2.2 & - & 1.5 \\ CoO & 0.1 & 0.1 & 0.1 & 0.1 & - & 0.1 \\ NiO & 0.1 & 3.2 & 0.5 & 0.3 & - & 0.2 \\ Fe\({}_{2}\)O\({}_{3}\) & 14.0 & 33.2 & 59.4 & 19.5 & - & 14.6 \\ FeO & 9.0 & - & 18.5 & 8.8 & - & 5.0 \\ Na\({}_{2}\)O & - & - & - & - & 13.3 & 4.0 \\ K\({}_{2}\)O & - & - & - & - & 1.3 & 0.4 \\ \hline \end{tabular}
\end{table}
Table 1: Chemical composition (wt %) of the main slag from an electro-furnace (EFS), dust (D), converter slag (CS), obtained waste mixture (WM), glass cullet (GC) and studied glass (WG).
## 4 Roles of PPK2s in Bacterial Physiology and Virulence
### Virulence Factors and Invasion  
Virulence factors are broadly defined as bacterial products or phenotypes that enable colonization, replication, or dissemination within the host organism [76]. Motility--whereby flagella or pili drive bacterial locomotion--is a necessity for the virulence of many species, and _ppk2_ deletion (\(\Delta\)_ppk2 AAppk2 BAppk2C_) has been shown to reduce swimming motility in _P. aeruginosa_[57]. Likewise, secreted toxins such as the siderophore pyoverdine are another class of virulence factor that frequently underpin _P. aeruginosa_ infections [77]. We showed that relative to the _P. aeruginosa_\(\Delta\)_ppk1_ strain, the _\(\Delta\)_polyP_ strain was further attenuated in pyoverdine production, thus implicating PPK2 enzymes in pyoverdine virulence. The _\(\Delta\)_polyP_ strain also demonstrated a further reduction of _P. aeruginosa_ virulence towards the nematode _Caenorhabditis elegans_ relative to the \(\Delta\)_ppk1_ strain, highlighting the importance of _P. aeruginosa_ PPK2s in an animal model of infection for the first time [57]. Further studies to dissect the individual contributions of each _ppk2_ isoform to these phenotypes may help elucidate the mechanistic links between polyP metabolism and virulence.  
While _P. aeruginosa_ is primarily an extracellular pathogen, PPK2 enzymes have also been extensively linked to the invasion and survival of the intracellular pathogens _C. jejuni_, _M. tuberculosis_, and _F. tularensis_. A _C. jejuni_ ppk2 mutant was defective in invasion and intracellular survival in cultured human intestinal epithelial cells. Furthermore, _C. jejuni_ _Appk2_ was also significantly impaired in the colonization of day-old chickens [48]. These defects may be due to changes in outer membrane constituents (proteins, lipids, and polysaccharides), alterations of which in _C. jejuni_ _Appk2_ have been shown to attenuate its invasion [78]. In _M. tuberculosis_, _ppk2_ mutation or downregulation impaired growth and survival in macrophages [41, 54, 55]. Moreover, macrophages infected with _\(\Delta\)_ppk2_ bacteria secreted increased levels of proinflammatory cytokines [41], which culminated towards defects in colonization following bacterial challenge in both murine and guinea pig models of infection [41, 55]. The lungs of guinea pigs infected with _\(\Delta\)_ppk2 M. tuberculosis_ had fewer and smaller tubercles relative to the WT and _ppk2_-complemented controls [55]. Similarly, deletion of _ppk2_ (FTT_1564) in _F. tularensis_ abolished polyP accumulation, and resulted in defective intracellular growth in macrophages and attenuated infection of mice [79].
# Study on Mechanism of Static Blasting-Induced Hard Rock Fracture Expansion
## 3 Experiments on the Fracturing and Expansion Capabilities of Static Crusher
### Expansion Pressure Test
#### 3.1.1 Expansion Pressure Test Methods and Equipment  
(1)The resistance-strain approach  
The standard measurement method, illustrated in Figure 6, involves using a model Q235 seamless steel pipe with dimensions of 500 mm in length, 40 mm in inner diameter, and 4 mm in wall thickness. The bottom plate is welded with 4 mm thick steel plate pockets, and attachments are added for longitudinal and transverse strain gauges in the corresponding positions. This setup is used to measure the expansion pressure of the static crusher, commonly known as the outer tube method [38].  
To obtain test results, strain data are recorded and inputted into the Formula (13). The crusher slurry or solid medicine rollers are then filled into the steel pipe. The magnitude of the expansion pressure can be calculated based on these inputs.  
\[P=\frac{E_{S}\big{(}K^{2}-1\big{)}}{\big{[}\varepsilon_{\theta}(2-v)\big{]}} \tag{13}\]  
where \(P\)--expansion pressure, MPa; \(E_{S}\)--modulus of elasticity of steel pipe, \(2.06\,\times\,10^{5}\) MPa; \(K\)--ratio of outer diameter to the inner diameter of steel pipe; \(\varepsilon_{\theta}\)--strain in the circumferential direction of the steel pipe; \(v\)--[PERSON]'s ratio, 0.3 [38].  
Figure 5: A schematic representation of a static crusher’s rock fracturing mechanism.  
2. Expansion pressure test equipment  
In the laboratory, the following experimental tools and materials are prepared for the investigation using the expansion pressure test method. Some of the equipment is shown in Figure 7.
## 1 Introduction
The interpretation of these data could also help gain a clearer understanding of the dependence between chemical structure and thermal properties. While little experimental data on enthalpies of fusion exists, previous studies on the correlation between molecular structure and melting temperature have been performed. Firstly, [PERSON] [15] in 1882, and more recently [PERSON] et al. [16] in 2001 both observed that symmetrical molecules with efficient crystal packing tend to have higher melting points due to stronger intermolecular bonding. This is true for molecules with higher molecular weights because of lower kinetic energy and therefore more tightly packed structures. For the same reason, branched molecules are reported to have lower melting points compared to linear homologues since they tend to form less packed structures [16]. As reported by [PERSON] et al. [17] and [PERSON] et al. [18], the melting points of alkanes increase with longer carbon chains, with two different trends for even and odd numbered carbon chains, where even-numbered ones present higher values. [PERSON] et al. [12] examined 11 commercially available linear fatty esters for use as PCM, and confirmed the trends reported above for melting points in relation to molar mass. Other studies have been performed on the subject. [PERSON] et al. [13; 14] synthesized even-numbered fatty acid esters of myristyl alcohol and esters from dicarboxylic acids with promising enthalpies of fusion over 200 J/g. [PERSON] et al. [19] synthesized esters derived from stearic acid with glycerol, isopropyl alcohol and n-butyl alcohol through Fischer esterification. In this study, synthesis of linear fatty esters from fatty acids of different even-numbered chain lengths (Myristic Acid MY (C\({}_{14}\)), Palmitic Acid PA (C\({}_{16}\)), Stearic Acid SA (C\({}_{18}\)), Behenic Acid BE (C\({}_{22}\))), coupled with alcohols (methanol (C\({}_{1}\)) and 1-decanol (C\({}_{10}\))) was performed. All IUPAC names, trivial names, chemical structures and shortenings from the esters produced are reported in Figure 11. The thermal properties of the esters produced were analyzed to individuate possible trends with the molecular structure, and to obtain a broader overview on the possible range of melting points. In order to optimize and validate the synthesis, at first a commercially available ester (Methyl Palmitate) was reproduced in the laboratory and the resulting properties compared with the one purchased by manufacturers. Following optimization of the synthesis procedure, new esters of fatty acids with methanol (MeOH) and 1-decanol was produced. Methyl Palmitate (MEPA), Methyl Myristate (MEMY) and Methyl Stearate (MESA) have been previously produced and are available at affordable prices, while Methyl Behenate (MEBE) is also available at higher prices. Little to no thermal data has been found on fatty esters derived from 1-Decanol, and their commercial availability is limited.
# Enhancing QoS in Opportunistic Networks Through Direct Communication for Dynamic Routing Challenges
## 4 Simulation Environment and Results
### Simulation Environment Assumptions  
This section outlines the assumptions of the simulation environment to enhance the clarity and understanding of the underlying system, the existing schemes, and the consistent advantages offered by the proposed approaches.  
1. LoS: LoS communication is initiated when the time to select a next hop exceeds the threshold \(T\) seconds.
2. \(\theta\): Angle between predicted direction and SDL (source-destination line).
3. \(\delta\): Perpendicular distance of neighbor node from SDL.
4. \(\psi\): Stability measured using speed variance.
5. State Assumption: We assume an open area without signal obstruction to allow uninterrupted LoS transmission.
## Appendix A  
```
Input: Cost matrix \(costMatrix\) Output: Assignment matrix \(M\) Function HungarianMethod(\(costMatrix\)):  Initialize a matrix \(M\) of the same size as \(costMatrix\) with all zeros;  Initialize arrays \(rowCovered\) and \(colCovered\) of size equal to the number of rows and columns of \(costMatrix\) respectively, filled with False; whilethere exists an uncovered zero in \(costMatrix\)do  Select an uncovered zero \(Z\) in \(costMatrix\); Star\(Z\) and cover its row and column; whilethere exists a starred zero in the same rowdo  Find a starred zero \(Z^{\prime}\) in the same row as \(Z\);  Cover the column of \(Z^{\prime}\) and uncover the column of the starred zero in the same row as \(Z^{\prime}\); Star the uncovered zero in the same row as \(Z^{\prime}\); \(Z\leftarrow\) the uncovered zero just starred;  end if ifno starred zero is found in the same rowthen  AugmentPath(\(Z\));  end if  end if return\(M\); FunctionAugmentPath(\(Z\)):  Initialize a stack \(path\) and push \(Z\) onto it; whiletruedo  Find a primed zero in the same column as the top element of \(path\), say \(Z^{\prime}\); ifno primed zero is foundthen  Break;  end while Push \(Z^{\prime}\) onto \(path\);  Find a starred zero in the same row as \(Z^{\prime}\), say \(Z^{\prime\prime}\);  Push \(Z^{\prime\prime}\) onto \(path\);  end for for each element \(E\) in pathdo if\(E\) is starredthen  Unstar \(E\);  end if else  Star \(E\);  end if  end while
```  
**Algorithm A1**Hungarian method (Munkres algorithm).
# Determination of Cyanotoxins and Prymnesins in Water, Fish Tissue, and Other Matrices: A Review
## 4 Sample Preparation and Analytical Methods for Cyanotoxins and Prymnesins Detection
### Analytical Methods
#### 4.2.3 LC-UV and LC-FLD  
Monitoring UV absorbance was historically one of the first techniques to detect cyanotoxins after LC separation. MCs and CYNs have specific UV spectra with maximum absorbances at 240 and 262 nm, respectively [94; 95]. Analytical workflows using LC-UV and/or LC-PDA allow for measuring the concentration of MCs by using these characteristic absorbances. In conjunction with good chromatographic separation, samples can not only have toxin concentrations measured but also give some information on the congeners of the MCs present. The key limitation of UV-absorbance-based techniques, however, is that the absorbance is not limited to only MCs and that background interferences may also impact the baseline signal. This can result in both lower DLs and potentially false positive signals, depending on the matrices being studied. Literature results for MC monitoring using LC-UV and LC-PDA have allowed for measurement of up to seven MC variants through comparison with analytical standards [96; 97].  
Detection by fluorescence is also commonly used after LC separation. However, cyanotoxins do not naturally fluoresce and, therefore, require the addition of a derivatization process during the sample preparation. For example, in the high-performance liquid chromatography with fluorescence detection (HPLC-FLD) system used by [98], post-column derivatization was performed using a solution containing 10 mmol/L of periodic acid and 550 mmol/L of ammonia in water (flow rate 0.3 mL/min). Nitric acid (0.75 mol/L in water; flow rate 0.4 mL/min) was used for reducing the pH value to 2-3. Fluorescence detection was applied for the determination of STX oxidation products at an excitation and emission wavelength of 330/395 nm.  
While most studies that have used LC-UV and LC-FLD techniques have done so in water matrices, several prior studies have used fluorescence and/or UV-based methods to measure cyanotoxins (and in particular MCs) in fish, sediments, and plants [96; 99]. The results of these studies show sensitivities comparable to those of LC-MS/MS methods, but with reduced specificity, due to which they can be more susceptible to matrix interferences,resulting in higher practical DLs. While LC-UV, LC-FLD, and LC-PDA methods can be simple and cost effective, misidentification can occur due to the non-specific nature of these methods. LC-MS/MS methods are becoming more prevalent in environmental laboratories now and are the preferred method for toxin identification as they can precisely and accurately identify toxins based on a specific mass/charge precursor ion that is unique to each toxin. In addition, despite typically offering only a unit mass resolution, LC-MS/MS methods can improve confidence in the identification of target compounds through screening for confirmation ions and the ratio of target and confirmation ions being produced.
## 2 Background and Review of Related Works
### Securing the ICV with XAI: Background Information  
#### 2.4.1 Existing Approaches to Combating Security Breaches on ICVs  
Security has remained a big concern among ICV stakeholders due to their reliance on the internet connection, thus exposing them to cyber criminals/hackers. Hackers can take control of a connected car, forcing unintended braking, acceleration, or steering. Privacy invasion can also be a security concern as hackers can gain access to the personal information of users. To solve this, the report from the connected vehicle 2022 summit by [PERSON] [62] opened that \"Escrypt\", a cyber threat protection company, was of the view that vehicle data safety could be ensured through blockchain-based communication systems, smart gateways, cyber digital twin, AI-based detectors and other encryption systems [62]. Similarly, the authors of [63] proposed what they considered an advanced AI and ML technique to protect connected vehicles from vulnerabilities related to automated driving, smart charging of electric vehicles, and communication among vehicles or between vehicles and roadside infrastructure. The advanced AI/ML known as \"CARAMEI\" was demonstrated to secure ICVs from spoofing attacks [63]. This work shows the promising role of AI in securing ICVs. However, XAI promises even more benefits to the ICVs dues to the trustworthiness introduced in addition to the known gains of AI. This paper focuses on the adoption of AI with an attention on the XAI for securing ICVs.
# An Image-Encryption Algorithm Based on Stage-Merging Bit Scrambling
## 1 Introduction
The diffusion process of the algorithm described in [7; 8] adopts forward and reverse diffusion, which is realized by the XOR of the pixel value with the previous pixel value and the chaotic value in turn. This diffusion method has been proven to create security problems, and attackers can obtain equivalent keys by constructing special images [9; 10]. It can be seen from the above analysis that single-pixel bit scrambling is less sensitive to the chaotic sequence used, and adjacent-pixel bit scrambling suffers from difficulties ensuring a good scrambling effect and speed at the same time. Additionally, these two scrambling processes are divided into two stages of position scrambling and bit scrambling. The two stages are executed serially. It would be considered an improvement to this process to increase the scrambling speed. In this regard, this paper proposes a stage-merging scrambling method. Compared with the two-stage scrambling process, this method merges the two stages and can simultaneously complete the double scrambling of pixel position and pixel value. While the scrambling effect is excellent, the scrambling time is shortened.