esa-sceva/satcom-chunk-collection huggingface dataset:
# Novel Techniques for Microbiological Safety in Meat and Fish Industries
## 2 Factors Affecting Microbial spoilage of Meat, Fish and Derived Products
### Atmosphere Conditions  
Microbial growth depends on oxygen surface tension and the oxidation reduction potential of food, which controls the nature of microbial flora. Aerobic bacteria usually grow in the presence of air and on the surface of some meat as there is sufficient oxygen available on the surface of the food product. Similarly, in mold spoilage, mold growth starts from the surface in aerobic conditions that later spreads inside food through its mycelium. Anaerobic bacteria, such as _Bacillus_, which can even grow in the absence of oxygen, critical to control their growth and spoilage activities in all foods, including both open and canned foods [7]. To control spoilage, oxygen is limited in stored meat by controlling air gas composition. Oxygen reduction to 5% can effectively control the microbial spoilage of meat and meat-based products [16]. Modified atmosphere packaging is one of the noveltechnologies used widely to stop aerobic spoilage. In modified atmosphere packaging (MAP), the oxygen environment can be changed with carbon dioxide, which helps to reduce spoilage.
# Dynamic Tensor Modeling for Missing Data Completion in Electronic Toll Collection Gantry Systems
## 3 Materials and Methods
### High-Order Tensor Model for ETC Gantry Data
#### 3.1.4 Traffic Data Calculation Based on the High-Order Tensor Model  
Traffic data extraction was performed through calculations using a high-order tensor model. Figure 2(a) depicts this model, which utilizes 30 min traffic statistics from two ETC gantries, each with three lanes. In this model, the vehicle types within tensor blocks are color-coded, enhancing the model's visual interpretation. This tensor model is adaptable to various spatial component transformations--including expansion, reflection, shear, projection, and rotation--enabling complex, multidimensional traffic data calculations.  
For instance, Figure 2(b) illustrates the calculation of traffic data for lane 2 at the G005032001000110010 gamtry. By segmenting a slice of the tensor model for this specific gamtry, the model yields comprehensive traffic information for lane 2. This slice encompasses tensor blocks representing different time intervals and crucial traffic parameters, such as traffic volume, average time headway, vehicle type distribution, and space occupancy rate. Additionally, the process of retrieving vehicle-level information is demonstrated in Figure 2(c). By entering the license plate details of a specific vehicle, the model directly locates the corresponding tensor block. Subsequently, traffic parameters, including interval speed and time headway for that vehicle, are accurately computed.  
Figure 3: _Cont._
## 9 Conclusions and Future Work
The contribution of researchers to this approach could help develop more universally applicable estimation models, reflecting a broader spectrum of Agile implementation contexts and cultural influences on software development practices. * **Temporal Expansion of Data for Agile Practices:** Including datasets that cover extended periods is crucial for capturing the evolution of Agile practices and technologies. This temporal data inclusion helps analyze trends and shifts in development practices over time, providing a deeper understanding of how Agile methodologies adapt and evolve, which is instrumental in refining effort estimation models. * **Incorporating Team Dynamics into Estimation Models:** Expanding the dataset to include metrics related to team dynamics and individual performance is not just a suggestion but a necessary step to incorporate human factors into the estimation process. By understanding the influence of team interactions and individual contributions, estimation models could be enhanced to predict effort more accurately, acknowledging the human elements that significantly impact project outcomes. * **Real-Time Application and Feedback:** Implementing the model in real-world Agile projects and gathering continuous feedback could lead to iterative improvements, making the model more robust and aligned with industry needs. * **Advancements in NLP and ML Techniques:** As NLP and ML fields evolve, integrating newer algorithms could further enhance the accuracy and efficiency of the SEE process. * **Human Factors in Estimation:** Investigating the interplay between automated estimations and human judgment could provide insights into how to balance these approaches for optimal project management. * **Scalability and Efficiency:** Assessing the model's scalability for large-scale projects and its efficiency in different project environments is essential for broader adoption. These future research directions could refine and advance the methodologies for SEE, ultimately contributing to the enhanced success and management of Agile software projects. **Author Contributions:** Conceptualization, B.Y. ; Methodology, B.Y., A.G.K; Software, B.Y. ; Validation, B.Y., A.G.K. and M.O.E. ; Formal analysis, B.Y., A.G.K; Investigation, B.Y. ; Data curation, B.Y. ; Supervision, K.D., M.O.E; Resources, K.D., M.O.E; Writing--original draft, B.Y. ; Writing--review & editing, B.Y, K.D., A.G.K. and M.O.E. ; Visualization, B.Y. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. **Conflicts of Interest:** Author [PERSON] was employed by the company HORITAI PTY LTD. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Antioxidant Properties of Selenium Nanoparticles Synthesized Using Tea and Herb Water Extracts
## 2 Materials and Methods
### The Synthesis and Characterization of Obtained SeNPs  
The green synthesis of selenium nanoparticles was based on the reduction of sodium selenite with tea or herbal extract. Briefly, 2.5 mL of selenium solution (0.1 mol L\({}^{-1}\)) was placed on the magnetic stirrer and 15 mL of deionized water was added. After that, 2.5 mL of tea infusion (Se/infusion ratio 1:1) or 5 mL (Se/infusion ratio 1:2) or 7.5 mL (Se/infusion ratio 1:3) or 10 mL (Se/infusion ratio 1:4) was added dropwise. The concentration of plant extract in the reaction mixture was: 1.25 \(\times\) 10\({}^{-3}\) (1:1), 2.50 \(\times\) 10\({}^{-3}\) (1:2), 3.75 \(\times\) 10\({}^{-3}\) (1:3), and 5.00 \(\times\) 10\({}^{-3}\) (1:4). The reaction mixture was intensively stirred for 60 min. The analogical reaction was also performed with the excess of selenium; in that case, the volumes were reversed.  
The obtained nanoparticles were so strongly stabilized that it was impossible to isolate them from the post-reaction mixture using e.g., centrifugation. This problem concerned tea extracts. In the case of herbal extracts, centrifugation with the intensity of 12,000 rpm enabled their isolation; however, due to the difficulties with repeating the procedure for teas, the separation of SeNPs in post-reaction mixtures was abandoned.  
The UV-Vis absorption spectra in the range of 250-900 nm were recorded after the synthesis to predict the sizes of obtained SeNPs. This was conducted using Perkin Elmer spectrophotometer (model Lambda 20) with cuvettes of 1 cm in length. In order to avoid interference related to the color of the brew used for synthesis, the spectra were recorded using the appropriate brew as a blank. The infusion used had the same concentration as that used for the given synthesis. For measurements, the sample was diluted 50 times.  
The size of the obtained nanoparticles was also investigated by dynamic light scattering (DLS). For this purpose, Mastersizer 2000 (Malvern Panalytical, UK) was equipped with the wet samples dispersion unit (Hydro 2000 MU). The device was controlled by standard operating procedure, which is a part of Malvern SOP software. The apparatus allows the measurement of particle sizes larger than 0.01 um, which can be valuable support for the measurement of synthesized nanoparticles if they are larger than 10 nm.
# Linewidth Measurement of a Narrow-Linewidth Laser: Principles, Methods, and Systems
## 2 Basic Principles
### Delayed Self-Heterodyne Method
#### 2.3.1 MZI-Type Delayed Self-Heterodyne Method  
The structure of the MZI-type delayed self-heterodyne method is shown in Figure 1c. Its basic principle is the same as that of the aforementioned delayed self-homodyne method. In 1980, [PERSON] et al. demonstrated a method for characterizing the linewidth of DFB semiconductor lasers [30], which used a delay fiber instead of an intrinsic oscillator. After  
Figure 2: Schematic diagram of the beat frequency signal when the reference linewidth (**a**) is equal to and (**b**) is much smaller than the measured linewidth.  
the tested laser is split into beams, it undergoes a delay fiber delay and an AOM frequency shift. The mixed-beat signal of the delayed light and the frequency-shifted light is:  
\[I(t)=E_{L}(t){E_{L}}^{*}(t)=E_{L}cos[-f_{0}t+(f+f_{0})\tau_{0}+\varphi(t)-\varphi (t-\tau_{0})] \tag{9}\]  
where \(E_{L}\) is the electric field of the interference beat frequency signal. The current power spectral density obtained by Fourier transform of its differential electrical signal is:  
\[\mathrm{S}_{L}(f,\,\tau_{0})=\frac{2(f\pm f_{0})\tau_{c}}{1+\tau_{c}^{2}(f\pm f _{0})^{2}}\bigg{\{}1-\exp\biggl{(}-\frac{\tau_{0}}{\tau_{c}}\biggr{)}\biggl{[} cos(f\pm f_{0})\tau_{0}+\frac{sin(f\pm f_{0})\tau_{0}}{(f\pm f_{0})\tau_{c}} \biggr{]}\bigg{\}}+\exp\biggl{(}-\frac{\tau_{0}}{\tau_{c}}\biggr{)}\delta(f\pm f _{0}) \tag{10}\]  
When the length of the delay fiber is much longer than the coherence length of the laser, \(\tau_{0}\) is much greater than \(\tau_{c}\). The exp term on the right side of the equation approaches 0, and the beat spectrum exhibits a Lorentz shape. The linewidths of the frequency-shifted light and delay light are the same, and the 3 dB bandwidth of the power spectrum curve is twice the linewidth of the tested laser [31; 32; 33].  
Additional optical transmission losses and 1/_f_ noise are inevitable for excessively long delay optical fibers, resulting in spectrum broadening and phase noise jitter. Therefore, researchers have proposed MI-type structures [34; 35; 36; 37] and gain-compensated cyclic structures [38; 39] based on MZI-type structures.
# Relevance of Surface Electromyography Assessment and Sleep Impairment in Scoliosis: A Pilot Study
## 1 Introduction
The method emphasizes the holistic approach of addressing the entire body's posture rather than focusing on isolated areas or symptoms [12]. Since a limited number of studies refer to global postural reeducation as a therapy in idiopathic scoliosis, research in this direction has recently started to be carried out. Based on 16 patients diagnosed with idiopathic scoliosis and with an average Cobb angle of 33\({}^{\circ}\), [PERSON] et al. conducted a study analyzing the effectiveness of postural therapy. Exercises based on morphology and symptomatology and organized towards the correction of deformities can lead, according to the previously mentioned study, to a reduction of 11 percent of the Cobb angle [13]. Another method used in therapeutic intervention is the Schroth method. It is a physiotherapeutic approach that employs various exercises, including isometrics, to strengthen or lengthen asymmetrical muscles associated with scoliosis. The treatment program of the Schroth method focuses on correcting scoliotic posture and incorporates specific breathing patterns. The method utilizes proprioceptive and exteroceptive stimulations, as well as mirror control, to enhance body awareness and promote postural corrections. By combining these elements, the Schroth method aims to improve posture, reduce spinal curvature, and enhance overall functional abilities in individuals with scoliosis [14]. The purpose of the present study is to monitor the evolution of children diagnosed with idiopathic scoliosis, to whom a mixed program of GPR and Schroth therapy was applied, considering the following aspect: sleepiness and paravertebral muscular status the latter being assessed through surface electromyography. The objectives of this study are as follows: to evaluate the paravertebral muscle balance, by EMG, before and after combined therapy; to evaluate the sleepiness according to the evolution of scoliosis and therapy; and to evaluate the perception of scoliosis using specific scales.
## 5 Results and Discussion
### Evaluation of Quantitative Method
For the AR app for 6 th grade: Earth as a living space for humans (see Table 4), the teacher-in contrast to the pupils and computers science students-supported that they would need help from a technician to use the system as well as they might need to learn a lot of things before teachers will be able to use it. This might be explained by the fact that one of the teachers did not have a satisfactory level of expertise and familiarity with such technology. In addition to this, another explanation might be the limited sample, which consists of only two teachers. As far as the AR app for 6 th grade: Earth as a celestial body is concerned (see Table 5), the majority of the participants agreed that the AR app is easy to use and, in general, they felt confident using it, since the AR app did not present any inconsistency. Table 6 presents the results regarding the extra question that was added to the questionnaire and referred to whether the proposed AR apps look like games (see Table 6). The participants highly rated all three AR Geography apps as game-like. More specifically, the results in the AR app for 6 th grade: Earth as a living space for humans, are in line with \begin{table}
\begin{tabular}{c l l l l} \hline \hline  & & \multicolumn{1}{c}{**Pupil**} & \multicolumn{1}{c}{**Teacher**} & \multicolumn{1}{c}{**Comp.**} \\
**Item** & **English Version of SUS** & **Responses** & **Responses** & **Science** \\  & & **Mean (Std)** & **Mean (Std)** & **Mean (Std)** \\ \hline Q1 & I think that I would like to use this system frequently. & 3.43 (1.09) & 4.50 (0.71) & 4.00 (0.90) \\ Q2 & I found the system unnecessarily complex. & 2.57 (1.28) & 1.00 (0.00) & 1.39 (0.73) \\ Q3 & I thought that the system was easy to use. & 4.14 (0.86) & 4.50 (0.71) & 4.39 (0.62) \\ Q4 & I think that I would need the support of a technical person to be able to use this system. & 2.79 (1.19) & 3.50 (0.71) & 1.28 (0.50) \\ Q5 & I found that the various functions in this system were well & 3.93 (0.92) & 4.50 (0.71) & 4.26 (0.85) \\ Q6 & I thought that there was too much inconsistency in this system. & 2.14 (1.03) & 1.00 (0.00) & 1.56 (0.80) \\ Q7 & I would imagine that most people would learn to use this system very quickly. & 4.29 (0.62) & 4.50 (0.71) & 4.39 (0.62) \\ Q8 & I found the system very cumbersome to use. & 1.64 (0.84) & 1.00 (0.00) & 1.46 (0.70) \\ Q9 & I felt very confident using the system. & 3.64 (0.84) & 4.50 (0.71) & 4.42 (0.59) \\ Q10 & I needed to learn a lot of things before I could get going with this system. & 2.29 (0.99) & 3.00 (1.41) & 1.42 (0.66) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Mean values and standard deviations of participants’ responses for the AR app for 6 th grade: Earth as a living space for humans.
## 2 Hardware Design and Implementation
### Fiber Optic Temperature Sensor
Based on the interference spectrum we obtained from the optical power meter (Agilent 8163A) in the fabrication process, the two neighboring valleys are 1489.1 nm and 1525.1 nm, we calculated that the FP cavity length was 30.797 \(\upmu\)m, which was very close to the length estimated by SEM imaging. The fabricated device was tested for its ability to survive high temperatures. The sensor was placed horizontally in a quartz tube with one-inch inner diameter, hosted inside a programmable electric tubular furnace. The temperature of the furnace was increased from room 50 \(\,\mathrm{\SIUnitSymbolCelsius}\) to 1100 \(\,\mathrm{\SIUnitSymbolCelsius}\) (limited by the highest temperature of the furnace used) at a step of 50 \(\,\mathrm{\SIUnitSymbolCelsius}\) and the interference spectra at these temperatures were recorded. However, to improve the accuracy, we replaced the tunable laser with a broadband source made by multiplexing a C-band and an L-band Erbium doped fiber ASE (amplified spontaneous emission) sources. The interference fringe reflected from the device was recorded by an optical spectrum analyzer (OSA, HP 70952B). The cavity length as a function of the temperature is plotted in Figure 1d, where it increased nearly linearly following the increase of temperature. The fiber FP device successfully survived high temperatures up to 1100 \(\,\mathrm{\SIUnitSymbolCelsius}\). Even if not lasting long at the very high temperature, it is good enough to meet the needs of early warning of the LPG storage tank fire hazards. The temperature sensitivity of this particular FP device was estimated to be 0.074 pm/\(\,\mathrm{\SIUnitSymbolCelsius}\) based on the linear fit of the measurement data. The equivalent CTE of the device was calculated to be 2.4 \(\times 10^{-6}/\,\mathrm{\SIUnitSymbolCelsius}\), which was about four times larger than the known CTE of the fiber cladding (fused silica, 5.5 \(\times 10^{-7}/\,\mathrm{\SIUnitSymbolCelsius}\)). The thermal test was repeated several times and the results were quite reproducible. For the protection of the miniaturized fiber inline FP interferometer temperature sensor, a brass bushing packaging technique was introduced. Figure 8a shows the schematic design of the packaged sensor and Figure 8b shows the actual packaged temperature sensor.
# Symbol-Level Selective Channel Estimation in Packet-Based OFDM Systems
## 1 Introduction
Thus, to improve the performance of the channel estimation, it is necessary to track the channel variations within a packet caused by high Doppler shifts in vehicular communications. Through a comprehensive analysis of existing techniques, our main motivation is to design a novel channel estimation scheme that can accurately track channel variations from the beginning to the end of a packet in a vehicular environment, where high mobility produces rapid channel variations within a packet. Therefore, in this paper, we propose a symbol-level selective (SLS) channel estimation scheme that selectively uses two channel estimation schemes--TRFI and DD-TT, which demonstrate good performance in different disjointed SNR regions--on a symbol-by-symbol basis in a packet. As TRFI and DD-TT demonstrate superior performance in high- and low-SNR regions, respectively, if these techniques can be adaptively selected for each symbol in a packet, then the error performance can be better than that of the conventional technique. The channel estimation proposed in this paper is not a simple combination of DD-TT and TRFI, but the creation of a new channel estimation scheme selecting the better one between DD-TT and TRFI on the symbol-by-symbol basis without significantly increasing the computational complexity. A simple combining method may select the better one by comparing the error performance of the two techniques after applying both techniques at the same time on the received packet, which leads to significant computational complexity. As a result, the simply combining method introduces a delay in choosing a better technique, which degrades the system performance. Overall, our contributions in this paper are as follows:  
* We present a new criterion that selects a better channel estimation scheme between two channel estimation schemes (DD-TT and TRFI) on a symbol-by-symbol basis without significantly increasing the computational complexity. * We perform a complexity analysis of the proposed scheme to demonstrate its implementation feasibility and prove that additional computational complexity is not substantial while selecting a better technique. * We analyze the trade-off between performance and complexity according to the algorithm's selection period within a packet. * By providing simulation results in terms of the bit error rate (BER) and packet error rate (PER), we demonstrate that the better channel estimation scheme can be selected on a symbol-by-symbol basis, thereby obtaining a performance gain in vehicular environments. The rest of the paper is organized as follows. In Section 2, IEEE 802.11p and the channel models adopted in the simulations are briefly introduced. Section 3 is a concise overview of three practical channel estimation techniques: DD-TT, TRFI, and PLS. In Section 4, we describe the algorithm for the proposed SLS scheme. Section 5 performs a computational complexity analysis of the proposed algorithm. Section 6 analyzes the simulation results for a performance comparison. Finally, in Section 7, we provide our conclusions.
## 4 Discussion  
Individually, each algorithm from previous studies provides performance parameters with some limitations that reduce the ability to diagnose breast cancer.  
The diagnosis of breast cancer requires high performance, including in terms of accuracy, precision, and F1 score, among other metrics.  
This study presents an integrated method that combines three advanced algorithms, which work together to achieve very high performance and provide precise diagnoses.  
Figure 2a illustrates the receiver operating characteristic (ROC) curve with an area under the curve (AUC) of about 0.996, which is exceptionally high, indicating that the model performs extremely well in distinguishing between malignant (dangerous) and benign (typical) cases. The ROC curve hugs the top-left corner, which is ideal, as this shows a very low false-positive rate and a very high true-positive rate. This means the classifier is highly capable of detecting breast cancer with minimal errors. This demonstrates that the classification model used in the breast cancer diagnosis task is highly effective, with near-perfect discriminatory power.  
Figure 2b is a Confusion Matrix that consists of 350 true positives (TPs) (correctly identified cancer cases), 7 false negatives (FNs) (cancer cases misclassified as benign instances), 208 true negatives (TNs) (correctly identified benign cases), and 4 false positives (FPs) (normal cases misclassified as cancer).  
As shown by this Confusion Matrix, very few misclassifications occurred for false positives and false negatives. The model is powerful in identifying cancer cases (showing high sensitivity) and minimizing false alarms (showing high specificity).  
The model's high sensitivity (recall) of approximately 99.6% ensures that most cancer patients are correctly identified, thereby minimizing missed diagnoses.  
A low false-positive rate helps avoid unnecessary stress and treatment for patients without cancer.  
The results show that the breast cancer classification model is highly accurate and reliable, making it well-suited for real-world diagnostic use. The combination of an AUC = 0.996 and strong confusion matrix metrics indicates that the model achieves an excellent balance between sensitivity and specificity, a critical aspect in medical diagnosis.  
Furthermore, comparisons between the proposed integrated algorithm and other algorithms from previous studies, such as SVM, KNN, RF, ANN, LR, NN, ENN, DT, and Naive Bayes, showed the superiority of the proposed integrated algorithm for all performance parameters investigated.  
Figure 10: Accuracy of different matrices in comparison with the proposed approach.