esa-sceva/satcom-chunk-collection huggingface dataset:
# Metagenomic Analysis of Bacterial Diversity on Reusable Tourniquets in Hospital Environments
## 6 Conclusions  
Metagenomic analysis of reusable tourniquets revealed a consistent presence of clinically relevant pathogens (HAI), including _Klebsiella_ spp., _Enterococcus_ spp., _Staphylococcus aureus_, _Pseudomonas aeruginosa_, and _Acinetobacter_ spp.  
Tourniquets sampled from operating theatres showed greater taxonomic diversity, suggesting variability in contamination dynamics driven by departmental usage patterns and disinfection practices. Cluster and diversity analyses further indicated that the highest genera diversity was exclusive to operating theatre tourniquets, although high contamination was not always associated with increased diversity.  
The frequent detection of potentially biofilm-forming and antibiotic-resistant bacteria underscores the limitations of current decontamination protocols. The findings strongly support the implementation of standardized sterilization procedures or the adoption of single-use tourniquets to mitigate the risk of cross-contamination and reduce the transmission of multidrug-resistant pathogens in clinical settings. However, the feasibility of widespread single-use tourniquet adoption requires careful consideration of resource constraints, particularly in low-income settings where cost and supply chain limitations may pose significant barriers. Healthcare systems should balance infection control priorities with local economic realities when implementing these recommendations.
## 2 Materials and Methods
### Data Analysis  
Volatile organic compounds (VOC) were tentatively identified by matching mass spectra with MS data libraries (NIST08, WILEY275) and by comparing their linear retention indices (LRI) with the literature. LRI are calculated using [PERSON] and [PERSON]'s equation for temperature programmed GC conditions, in which \(t_{x}\) is the retention time of compound \"\(x\)\", and \(t_{n}\) and \(t_{n+1}\) are the retention times of n-alkanes (C\({}_{6}\)-C\({}_{16}\)) with carbon number \"\(n\)\" eluting before and after compound \"\(x\)\":  
\[\left(LRI\right)_{x}=100n+100\times\frac{t_{x}-t_{n}}{t_{n+1}-t_{n}} \tag{1}\]  
Identified VOCs were classified according to their chemical nature: organic acids, alcohols, aldehydes (saturated, unsaturated, branched and cyclic), hydrocarbons, ketones, phenols, pyrazines and others. The peak areas of individual compounds as well as the total peak areas of each class of compounds are reported as area units (AU) \(\times\) 10\({}^{3}\) (mean \(\pm\) standard deviation) of HS-SPME-GC-MS analysis performed in triplicate.  
The effect of Mb addition (% Mb), grilling (G) and their interaction (% Mb \(\times\) G) on individual volatiles or groups of compounds was statistically analyzed through two-way ANOVA using IBM SPSS 27. In case of a significant interaction, the interaction term was further interpreted using one-way ANOVA followed by a post-hoc Tukey's honestly significant difference (HSD) test. A significance level of \(p\) < 0.05 was employed.  
Principal component analysis (PCA) was carried out using The Unscrambler X (v. 10.5.1) on a multivariate dataset containing peak areas of all identified compounds in each analyzed burger. Data were pre-processed by mean-centering and scaling to unit variance prior to analysis. The first two principal components (PCs) were considered to visualize the interaction between grilling and myoglobin enrichment of meat alternatives, and the resulting aromatic profile.
## 3 Technical Solutions for Collaborative Automations between Machines
### Message Events, Data Modelling and Presentation
#### 3.3.2 Data Modelling and Presentation  
For interoperable understanding between the machines, the messages are normalised according to the model described in Figure 4a. According to the type of events, messages are divided into control events and data events. The control events are for network maintenance, which give the UUID, name, and group of machines and the type of control events. Data events enclose the descriptive metadata, such as where the message is from, where it goes, the type of message, the time stamp, and the 'payload' that includes the information structured according to its type. The receiver can parse the 'payload' node with the'metamodel' and message type to obtain the useful data.  
In order to accommodate the software environments of the heterogeneous machines, JSON is chosen for data presentation in machine communications. An example of a JSON-described message is as shown in Figure 4b. The tree-hierarchy data structure can be used to describe the messages. Since JSON is cross-platform for data presentation over the internet, the events, commands, and data can be structured and wrapped for the interactions between machines.  
The proposed reference architecture is well suited for manufacturing applications to gain production line-scale machine interoperability. The decentralised structure of machine connectivity, autonomous machine discovery, ubiquitous messaging, and cross-platform presentation eventually contribute to the interoperability of manufacturing operations. The presented solutions are suitable to be used in dealing with the heterogeneity between machines, and therefore, data and information level methods can be introduced into industrial applications with these intermedium techniques.
## 3 Free Vibration and Buckling Analysis  
### Navier Solution  
For simply supported-simply supported (SS-SS) 3D-GrF cylindrical microshells, the displacement functions using the Navier method can be expressed as:  
\[u(x,\theta,t)=U_{mn}\cos\left(\frac{m\pi x}{L}\right)\cos(n\theta)\mathrm{e}^ {\mathrm{i}\omega t} \tag{55}\]  
\[v(x,\theta,t)=V_{mn}\sin\left(\frac{m\pi x}{L}\right)\sin(n\theta)\mathrm{e}^ {\mathrm{i}\omega t} \tag{56}\]  
\[w(x,\theta,t)=W_{mn}\sin\left(\frac{m\pi x}{L}\right)\cos(n\theta)\mathrm{e}^ {\mathrm{i}\omega t} \tag{57}\]  
where \(U_{mn}\), \(V_{mn}\), and \(W_{mn}\) represent the displacement amplitude components; \(m\) and \(n\) are mode numbers; and \(\omega\) is natural circular frequency of the 3D-GrF microshell. Obviously, displacement functions in Navier solution procedure satisfy the SS-SS boundary condition.  
Substituting Equations (55)-(57) into Equations (42)-(44) and then removing trigonometric functions lead to  
\[\left(\mathbf{K}+N_{xx}^{0}\cdot\mathbf{K_{g}}\right)\cdot\mathbf{d}+\mathbf{ M}\cdot\ddot{\mathbf{d}}=\left\{\begin{array}{l}0\\ 0\\ 0\end{array}\right\} \tag{58}\]  
where \(\mathbf{d}=[U_{mn},\ V_{mn},\ W_{mn}]^{T}\); \(\mathbf{K}\), \(\mathbf{K_{g}}\), and \(\mathbf{M}\) denote stiffness matrix, geometric stiffness matrix, and mass matrix, respectively. The non-zero elements in the above matrices are given in the Appendix A.  
Neglecting axial load \(N_{xx}^{0}\), Equation (58) is reduced to the following eigenvalue problem of the 3D-GrF microshell:  
\[\left(\mathbf{K}-\omega^{2}\mathbf{M}\right)\cdot\mathbf{d}=\left\{ \begin{array}{l}0\\ 0\\ 0\end{array}\right\}. \tag{59}\]  
If disregarding inertia terms and assuming \(N_{xx}^{0}=-P\), Equation (58) is reduced to the equilibrium equations of a static buckling problem of the 3D-GrF microshell:  
\[\left(\mathbf{K}-P\cdot\mathbf{K_{g}}\right)\cdot\mathbf{d}=\left\{ \begin{array}{l}0\\ 0\\ 0\end{array}\right\} \tag{60}\]  
where \(P\) represents buckling load. Therefore, the critical (minimum) buckling load \(P_{\mathrm{cr}}\) and vibration frequencies of the 3D-GrF microshell are obtained by solving the above eigenvalue problems [55; 56; 57].
# Research on Sentiment Analysis of Online Public Opinion Based on RoBERTa-BiLSTM-Attention Model
## 3 Model Construction  
### Modelling Frameworks  
This study combined sentiment dictionaries and deep learning algorithms to construct a public opinion sentiment analysis framework to achieve crawling, processing, and sentiment analysis of public opinion comments, with a view to improving the accuracy of a sentiment analysis of microblog comments related to a specific event and providing a refer ence basis for negative public opinion guidance and governance. The model framework and specific experimental steps are shown in Figure 1.  
As can be seen from the above figure, the model framework had four main steps:  
1. Data crawling and preprocessing. Firstly, the event-related opinion comments were crawled using Python coding and then the comment data were cleaned, de-emphasised, denoised, etc.; this was followed by word splitting and de-deactivated word operations.
2. Sentiment annotation. Based on the SO-PMI algorithm, we first constructed a supplemental sentiment dictionary of food safety events at a college, merged the supplemental dictionary with the commonly used Chinese dictionaries for sentiment pre-annotation, and then manually verified and corrected the annotated data to ensure the accuracy of the annotated data.
3. Construction of the RoBERTa-BiLSTM-Attention sentiment classification model. The RoBERTa-BiLSTM-Attention sentiment classification model was used to identify the sentiment of the review data, in which RoBERTa pre-trained the word vector features, BiLSTM extracted the sentiment features, and the attention mechanism assigned weights to the important sentiment features.
4. Model evaluation. Firstly, six indicators were selected to evaluate the model performance, ablation experiments were set up to verify the performance of each module of the model, and, finally, the sentiment results were evaluated and analysed.
## 1 Introduction  
Lentils (_Lens culinaris_ Medik.) are seeds from an annual herbaceous plant in the Leguminosae family, native to the Mediterranean. As a staple legume, lentils are crucial to global food security and sustainable agriculture, being grown across a wide range of agro-climatic regions [1, 2]. Their adaptability to diverse environments is reflected in numerous varieties, which differ in size, shape, and color [3, 4]. Nutritionally, lentils are rich in proteins, fibers, vitamins, and minerals, making them a vital component of human diets and animal feed [5]. Despite these benefits, lentil consumption has remained relatively low, likely due to factors such as long cooking times, unappealing taste, and the presence of anti-nutrients like phyt acid, tannins, and oligosaccharides that can cause digestive discomfort [6, 7].  
To address these issues, various techniques--both traditional and innovative--have been used to reduce anti-nutrient content in lentils. Methods like soaking, boiling, and fermentation, as well as emerging technologies such as dielectric heating and \(\gamma\)-irradiation, have shown varying degrees of success [8]. Malting, a process commonly used in beer production, has also been explored for lentils, as it activates enzymes that reduce key anti-nutrients [9; 10; 11].  
The aim of this study was to assess the environmental impact of lentil production, comparing conventional dry lentils with novel malted lentils that have reduced anti-nutrient levels and enhanced nutritional properties. We focused on a life cycle assessment (LCA) for two yellow lentil varieties produced in Morocco and Italy, using the Product Environmental Footprint (PEF) method, developed by the European Commission. This method evaluates 16 environmental impact categories, such as carbon footprint, water use, and resource depletion, ensuring a comprehensive environmental analysis from raw material extraction to end-of-life disposal. The PEF method includes specific guidelines, called Product Environmental Footprint Category Rules (PECRs), which provide consistency within product categories, allowing for fair comparisons. While the PEF method promotes transparency and supports environmentally informed choices, it can be data-intensive and does not cover social or economic impacts. An in-depth explanation of the PEF methodology, including data requirements and application rules, is available from the European Commission (see reference [12]).  
Through this study, we aim to identify the main environmental hotspots in lentil production, compare the profiles of novel low-anti-nutrient lentils and conventional varieties, and propose mitigation strategies to reduce their environmental impact. In this way, we hope to contribute valuable information to the ongoing efforts to make lentil production more sustainable and environmentally friendly.
## 3 Results and Discussion
### Melting and Crystalline Behaviors  
PP is a semi-crystal polymer, whose melting and crystallization properties depend on its structure, the copolymer, and the fillers. The melting and crystalline behaviors of all blends are indicated in Table 1 and Figure 3. Based on the DSC results, TPU exhibited a crystallization temperature of 62.41 \({}^{\circ}\)C, a crystallization enthalpy of 5.82 J/g, a melting point of 145.69 \({}^{\circ}\)C, and a melting enthalpy of 8.49 J/g, and all of these values, compared with other groups, are much lower. Figure 3A shows that PP100 and MPP100 possess similar melting points, which were 165.29 \({}^{\circ}\)C and 165.64 \({}^{\circ}\)C, respectively. Moreover, the melting point did not fluctuate after the addition of 10 wt% TPU, indicating that TPU did not affect the crystalline structure or stability of PP. In contrast, 10 wt% TPU decreased the melting enthalpy of PP90/TPU10 by 15 J/g. This is ascribed to the presence of TPU that was an amorphous polymer. Compared with PP100, PP90/TPU required relatively little energy to hamper the reaction between molecules, contributing to a greater mobility of the PP molecular chain. Figure 3B reveals no significant differences in the crystallization temperature or the crystallization enthalpy between MPP100 and MPP90/TPU10. MPP is a modified PP polymer with low crystallization, whereas TPU is an amorphous  
Figure 2: Fractured surface of **(A)** PP100 (1000\(\times\)), **(B)** MPP100 (500\(\times\)), **(C)** PP90/TPU10 (1500\(\times\)), and **(D)** MPP90/TPU10 (1500\(\times\)).  
polymer. Their (MPP90/TPU10) combination caused a slight decrease in the crystallization temperature and crystallization enthalpy of MPP90/TPU10. In addition, the combination of PP and amorphous polymer TPU in PP90/TPU10 resulted in an increasing crystallization temperature. Compared to PP100, the crystallization of PP90/TPU10 took longer. PP has a polymorphism that can be divided into three crystalline structures: an \(\alpha\) crystal form of the monoclinic system, a \(\beta\) crystal form of the hexagonal system, and a \(\gamma\) crystal form of the orthorhombic system [11]. Under common processing conditions, isotactic PP often shows an \(\alpha\) crystalline form. Figure 3C shows that, in the XRD test, when 2\(\theta\) was 14.1\({}^{\circ}\), 16.8\({}^{\circ}\), 18.5\({}^{\circ}\), 21.3\({}^{\circ}\), and 21.8\({}^{\circ}\), the corresponding Bragg diffraction characteristic peaks of PP were accompanied by crystal plane diffraction of (110), (040), (130), (111), and (131) [1; 12; 13; 14]. The results illustrated that, for PP90/TPU10 and MPP/TPU, the diffraction peak remained the same, indicating that adding TPU did not create a new crystalline structure [15; 16]. Moreover, both PP/TPU at (110) and MPP90/TPU10 at (040) had higher strengths. There were no significant differences in other peak values, suggesting that TPU did not function as a nucleating agent in the PP or MPP matrix and thus did not cause any significant difference in the crystalline phases of PP or MPP [11].
## 1 Introduction
Moreover, in the areas of interest of researchers, there are issues similar to those presented in this article, i.e., locating the AE source based on the wavelet analysis of the signal using the minimum number of sensors [14] or searching for the wavelet coefficients of AE signals that can predict material damage [15]. In addition, the analysis of AE signals may concern the monitoring of technological processes: aluminum welding [16] or quality assessment of the chemical mechanical polishing (CMP) process [17]. In addition, it is worth mentioning scientific research with the improvement of ultrasound methods [18] or references such as wireless technologies [19] or IoT [20]. This paper is devoted to the problem of detecting and locating one or more defects in a steel plate while using the acoustic emission method in conjunction with a discrete wavelet transform. Apart from the introduction, the paper is organized as follows: The second part of the article describes the AE method and wavelet transform. Then, in the third part, the construction of the test setup and test method are presented. The next part includes the results of the measurements. The article ends with conclusions from the research, and this part also includes plans for future research.
# Positioning Systems for Unmanned Underwater Vehicles: A Comprehensive Review
## 4 Methodology in Reviewing Positioning Systems Applications Based on Positioning Systems
### Filtering  
During our research, we came across a substantial number of identical papers, papers with irrelevant content, and even outdated review papers. Some papers provided insufficient information about the positioning systems that we used and conflicted with other papers. Using personal criteria and specific keywords like \"INS\", \"LBL\", \"LIDAR\", and more, which are the abbreviations of technologies we mentioned in Sections 2 and 3, we narrowed our selection of papers even more. In the end, we opted for 109 papers for our research. The initial screening process yielded a total of 280 research papers that required thorough examination and assessment. Our primary task was to determine which of these papers would be suitable for inclusion in our review.  
To begin with, we employed a keyword-based filtering approach. This initial filter was crucial for narrowing down the extensive list of papers, enabling us to exclude those that did not align with our research objectives or were irrelevant to our study. Given the sheer volume of papers, this first filtering step was particularly challenging, as it required careful consideration to eliminate only those papers that were clearly outside the scope of our review. After the first filtering, we had to re-filter 208 papers.  
Following the first round of filtering, we conducted a second, more detailed review. This stage proved to be significantly beneficial as it allowed us to further refine our selection. During this phase, we eliminated papers that were outdated or contained information that was no longer pertinent to our research. This step was essential for ensuring that the literature we included in our review was both current and relevant, thus improving the overall quality and reliability of our analysis. Before moving on to the final step of our literature research, we had 169 papers.  
The third and final filtering stage was implemented to address papers that did not provide sufficient data for our review. Despite the comprehensive nature of the papers we considered, some were excluded because they focused predominantly on mathematical modeling rather than on practical positioning systems, which was the core focus of our study. This final filter was instrumental in ensuring that the papers we selected contributed meaningful and applicable insights to our research, thereby enhancing the robustness and relevance of our review findings. A total number of 110 papers can be seen in the References section.  
In summary, our filtering process involved multiple stages of refinement: initially using keywords to weed out irrelevant papers, then applying a more detailed review to exclude outdated information, and finally excluding those papers that did not meet our data requirements. Each stage was critical in streamlining our selection process and ensuring that only the most pertinent and high-quality papers were included in our review.
# Analysis of the Relationship between Scintillation Parameters, Multipath and ROTI
## 2 Materials and Methods  
### Data and Instrumentation  
Data used in this study were collected from three stations, PRU2 (51.41\({}^{\circ}\) W, 22.12\({}^{\circ}\) S), SAO0P (46.65\({}^{\circ}\) W, 23.55\({}^{\circ}\) S) located in Sao Paulo, Brazil and SNA0P (2.84\({}^{\circ}\) W, 71.67\({}^{\circ}\) S) located in Antarctica. The receivers in PRU2, SAO0P and SNA0P stations are Septentrio PolaRxS 2.1.1, Septentrio PolaRxS 2.9.6 located in Sao Paulo, Brazil and Septentrio PolaRxS 2.9.0 located in Antarctica, respectively. The Septentrio PolaRxS is a multi-frequency multi-constellation receiver specialized for monitoring ionospheric activity. As scintillation activity is mainly strong in two global areas, namely the equatorial and polar regions, where the causes leading to the generation of scintillation are completely different [12], data from three stations located in these two regions is used. All the parameters are acquired with a sampling interval of 1 min for the purpose of comparison.
## 3 Results
### Tunable NIR Pump
The appearance of all even harmonics, in the case of NIR pulses, using thicker (0.5 mm) BBO crystal, revealed a sufficient spatiotemporal overlap of tunable 1300-1370 nm radiation and its second harmonic emission in LIPs due to a lesser difference in the group velocity dispersion of these pulses in the NIR range. At these conditions of Sn NP ablation, the analysis of debris from the ablated area showed the presence of notably smaller NPs compared with the original 70 nm species glued on the glass substrates. Figure 5B shows two TEM images with different magnification factors of the debris deposited on the nearby substrates, which allow for the determination of the presence of a broad range of the dimensions of nanoparticles (between a few units of nm up to 15 nm). Some smaller clusters yet resolved in these images, being in a plasma state, could be responsible for the resonance enhancement of a single harmonic. The studies of harmonics using idler pulses (1600-2400 nm) were carried out as well. The harmonics were generated using the wavelengths of a pump close to the regenerative regime of the OPA (1600 nm), due to higher pulse energy. The experiments were carried out in the 1600-1900 nm range. The application of these longer wavelength pumps led to a notable decrease in harmonic generation efficiency due to the \(\mathrm{I_{harm}}\)\(\infty\)\(\lambda^{-5}\) rule. Only the two-color pump configuration was suitable, in this case, to generate odd and even harmonics, while the application of the single-color pump led to a notably weaker harmonic emission. This observation, as well as the above-presented data, points out the attractiveness of the two-color pump over the single-color pump for harmonic generation in laser-induced plasmas, independently on the spectral range of emissions of the fundamental radiation.