esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### CCT and Work Productivity  
Results also showed that the CCT affected productivity not by increasing it, but by maintaining it. Productivity outcomes clearly demonstrated that employees in the intervention group maintained their productivity, while the productivity of participants in the control group significantly dropped. The decreased productivity among the control group participants is difficult to interpret. The most likely explanation for such an outcome is that the period at the end of 2022 was challenging for this agency due to an increased workload related not only to completing outstanding cases but also to pension and disability legislative changes that needed to be incorporated into the work process. Thus, it is very likely that toward the end of 2022, there was increased stress in the workplace due to the pressure related to finishing certain tasks and adapting to legislative changes. The key point is that participants in the intervention group maintained the same level of productivity despite dedicating two hours of their weekly working quota to CCT. It is also important to note that participants from the intervention group rated their satisfaction with the CCT process and its administration above average. This outcome is significant for future studies, conveying the message that the time devoted to CCT is unlikely to decrease the productivity of employees engaged in it.
###### Abstract  
The aim of this study was to investigate the root canal morphology of lower second molars in the Croatian subpopulation of the Zagreb region using cone-beam computed tomography (CBCT). We analyzed 3212 CBCT scans from the two radiology centers in Zagreb. The number of roots and root canals, the occurrence of C-shaped canals and additional roots were recorded. \"C\"-shaped roots were classified according to Melton classification. Canals in the mesial root were classified according to Vertucci. Lower second molars were found on 608 CBCT scans from a total number of 859. Among them, 78 (9.1%) had a \"C\"-shaped form. In the mesial roots, the frequencies of Vertucci types were: Type I in ninety-four cases (12.0%), Type II in three hundred and twenty cases (41.0%), Type III in six cases (0.8%), Type IV in three hundred and fifty-two cases (45.1%), Type V in three cases (0.4%), Type VI was found in four cases (0.5%) and Type VIII was found in one case (0.1%). Radix entomolaris and paramolaris were found in 29 (3.4%) lower second molars. The lower second molars in the Zagreb population show significant diversity in internal anatomy with a relatively high prevalence of \"C\"-shaped root canals and merged root canals in the mesial root.  
one-beam computed tomography; molar; endodontics; dental pulp cavity; tooth roots Article
# Advancing Biological Research: New Automated Analysis of Immunofluorescence Signals
## 2 Materials and Methods
### Manual Signals Analysis  
Signal quantification was obtained as the mean fluorescence intensity per cell area using ImageJ v1.54d software (National Institutes of Health, Bethesda, MD, USA) for Windows 10. The image in TIFF format is loaded, and each cell is countered using the \"freehand selections\" tool, which allows for delimiting the ROI. In detail, the user arbitrarily delimits the cell contour with the cursor and then, from the \"Analyze\" menu, selects the \"Measure\" option; the software will calculate various parameters, including the \"area\", which represents the measurement of the ROI surface, and the \"integrated density\", calculated by ImageJ as the sum of the pixel values in the selection. The last step is the calculation of the ratio between the integrated density and the area for each cell in the image. This ImageJ-based analysis is currently the standard to perform the quantification of IF signals; thus, we employed such a workflow as the ground truth to compare our automated approach. In this context, it is important to specify that the calculation of the parameters \"area\" and \"integrated density\" using this method implies the interpretative subjectivity of the user who arbitrarily performs the contouring, which therefore may differ between different users.
## 2 Research Motivation and Related Work
### Content-Based Filtering  
The content-based filtering method often uses users' profile information in the system. There are two general methods to construct users' profile information. One is the preference model, and the other involves users' data history [26; 27]. Technically, the profile information can be converted to a discrete score or number rating. The well-known representation for user profile information is the term frequency-inverse document frequency (tf-idf) or vector space representation [28; 29]. The tf-idf method converts user profile information to a vector space based on item features.  
In this paper, we use the tf-idf method to develop content-based filtering. While there are more sophisticated methods, such as support vector machines [30; 31], Bayesian classifiers [32; 33], and deep learning [8; 34; 35], we leave those for future work since these methods often require a deeper level of technical expertise and are more appropriate for advanced students who have already acquired a foundational understanding of the subject matter. Additionally, introducing these methods too early may overwhelm students and discourage them from continuing with the course. By leaving these methods as future research work, students can build on their existing knowledge and skills and gradually work toward more advanced topics as they become more confident and proficient.  
The important thing when implementing the content-based filtering method is whether the recommendation system can learn and use the profile information in an effective manner. To solve the issue, we build summaries for 177 items related to martial arts, dance, and play in seven Silk Road countries and use them for item similarities. The details and descriptions of the tf-idf and the similarity measure are provided in Section 3.2.
## 3 The Analysis
### Mes Selection and Bandwidth Allocation  
Usually, delay guarantee and error probability are required by specific URLLC service, the modulation and coding schemes are selected based on channel quality, which are all objective. Therefore, in order to provide strict delay and reliability guarantee for URLLC traffic, the system has to try it best to allocate reasonable amount of resource.  
As it shows in Lemmas 1 and 2 that, the delay and error probability are strongly correlated with allocated spectrum \(W\), coding scheme \(n\) and modulation order \(M\). For any particular URLLC-tuple \((k,d,\epsilon)\), there are multiple solutions for \((W,n,M)\). Here, we have Theorem 1 to reveal the relationship between MCS selection and bandwidth allocation, where the lower bound of allocated bandwidth is found.  
**Theorem 1**: _Consider an information packet with length of \(k\) bits going through a wireless channel under SNR of \(P\), and the delay and error probability requirements are defined by \((d_{0},\epsilon_{0})\), then, for a particular URLLC-tuple \((k,d_{0},\epsilon_{0})\), there are multiple solutions for MCS selection \((n_{0},M_{0})\) and bandwidth allocation \(W_{0}\) as far as \(W_{0}\) is no less than_  
\[W_{0}\geq\frac{k}{d_{0}\cdot R_{2}(P,n_{0},\epsilon_{0},M_{0})}. \tag{14}\]
# Evaluating the High Frequency Behavior of the Modified Grounding Scheme in Wind Farms
## 2 Wind Turbine Model Description
### Grounding System Model  
The grounding system is one of the essential parts of the system protecting a wind turbine against abnormal conditions, specifically lightning. Diverse kinds of grounding models have been designed, such as a constant resistance model, a nonlinear resistance model with a soil ionization effect and an extended grounding system. Each of these models has disadvantages. For instance, constant resistance acts as a lossless grounding model, and simulations derived from such a system are not reliable, while nonlinear grounding that only considers the effect of soil ionization will only be applicable in the case of low frequency and current flow. To fulfill the IEC 61024 requirements, an extended grounding system was therefore designed, which soon became the prevailing model because it was more accurate at reducing GPR than previous models [30; 31]. However, this model ignores the impact of soil ionization and is instead based on frequency-dependent parameters, with the consequence that its accuracy is confined to high-frequency and low-current conditions [41].  
Due to the aforementioned problems, when modeling a comprehensive grounding scheme during transitions such as lightning strikes (when both frequency and current are at their maximum volume), it seems to be necessary to simultaneously consider both nonlinear soil ionization and frequency-dependent models to eliminate the possible opposite effects of these two factors. While soil ionization helps improve grounding system performance, the induction behavior of frequency-dependent components causes grounding disruptions [17]. Hence, we propose the following integrated grounding scheme to provide a proper solution.
# Supporting Privacy of Computations in Mobile Big Data Systems +
## Complexity
### Construction and Evaluation Time  
We used BIGNUM routines and crypto functions from the OpenSSL library to implement our secure cloud computing system. We built our system as a collection of modules, and our implementation uses TCP (which stands for Transmission Control Protocol) sockets for communication among the servers. Using a server with Intel Xeon 2.53 GHz processor (Intel, Santa Clara, CA, USA), with 6 cores and 32 GB RAM we evaluated our system. Figure 8 shows the time taken to construct one garbled table for varying number of servers. We note that in order to significantly reduce the construction time, the garbled tables for any number of gates in the circuit can be constructed in parallel.  
Figure 9 shows the time taken to evaluate one garbled gate for varying number of servers. Notice that evaluation is significantly faster than construction, and that the latter can be done offline. The evaluating server can readily carry out the requested computation, and therefore drastically reduce the response time for the mobile client, if the garbled circuits are pre-computed and made available to the evaluator, in advance.  
Figure 8: Time taken to construct one garbled table.  
While our prototype is implemented entirely in software, we note that it is possible to achieve significant speedup through special dedicated hardware blocks. For example, our method relies on the computation of pseudorandom functions such as AES, which can be expressed as a Boolean circuit with only _AND_ gates and _XOR_ gates [18]. Therefore, using hardware blocks for realizing the computation of pseudorandom functions that are used very frequently in our system can dramatically improve the overall time taken for performing privacy-preserving computations on the cloud on behalf of the client.
###### Abstract
In addition, phages are the most abundant biological entities and are found in places where their host organism exists. They are relatively stable under various conditions, such as pH, temperatures, and organic/inorganic solvents, and they resist proteases. They are also cheaper to produce than antibodies and have a relatively long shelf life. It is easier to distinguish dead from live bacterial cells using this platform, as phages replicate only inside living bacteria [12]. The short shelf life of food products and the low infectious dose of most foodborne pathogens [13] are the most critical driving forces that push researchers to design sensitive, specific, and reliable detection techniques. The development of phage-based biosensors as a tool for the direct detection of live pathogens in food is an important and attractive approach [14]. Presently, several phage-based biosensors have been developed that incorporate various transducers, including electrochemical [15], quartz crystal microbalance (QCM) [16], surface plasmon resonance (SPR) [17], magnetoelastic (ME) [18], and others. Most of these biosensors have been designed using the whole/intact phage or the phage proteins as well as the cytoplasmic markers that are released following the phage infection. The performance of these biosensors varies, as they employ different immobilization methodologies (physical, chemical, covalent, or oriented) and/or transducers. Efforts have been made in the last decade to optimize biosensor systems, including phage-based sensors, to enhance the reliability of the technique. As far as we know, phage-based biosensors for monitoring water and food samples have not yet been commercialized; however, the current trends show promise. This review provides an overview of the different types of phage-based biosensors and their application in the detection of foodborne bacterial pathogens, with a special emphasis on recently developed biosensor platforms.
###### Abstract  
Experiments were performed with Fabry-Perot optical resonators in vacuum at low temperatures. Mirrors were applied on substrates of various optical materials. An infrared laser with a wavelength of 1.064 microns was used. The pump power at the maximum could reach 450 mW. The evolution of the optical properties of the FP cavity was traced in the temperature range 300-10 K. The main parameters measured were the integral characteristics of the FP resonances-sharpness (finesse) and contrast of interference. Three types of substrates were tested: a stall, an optical glass with ultra low thermal expansion (ULE); sapphire; and calcium fluoride. During cooling, the degradation of the integral characteristics of the FP cavity was observed for the stall mirrors due to the loss of the properties of ULE, and for sapphire mirrors due to the birefringence effect. The satisfactory constancy of the integral characteristics of the FP resonator on calcium fluoride was demonstrated in the entire temperature range studied.  
Keywords: cryogenic Fabry-Perot cavity; cooled mirrors; optical frequency standards; gravitational wave laser interferometers +
Footnote †: journal: Physics Letters B
## 5 Examples
### The Effect from Parameters of Altitude Feature Extraction Method  
To verify the robustness of the method, the impact of parameter settings on FCDF was discussed, and the results are shown in Figure 7. For sliding window width \(k\), a different point only occurs in \(k=40\) when the limitation of \(k\) is in interval [0, 200] or about 1/21 of the length of flight profile data; the others of the FCDF are the same, showing that parameter \(k\) affects the resulting litter. For intervals, when \(\Delta n\geq 60\), the FCDF is constant, so it will affect the resulting litter if large enough. Altitude threshold \(c\) affects the result greatly because it is a parameter related to the maneuvering motion; however, the altitude change is limited to the performance of the aircraft, so it is constant when larger than 14%.  
Figure 6: Altitude feature extraction results for flight profiles of some other shapes: (**a**) Profile 1; (**b**) Profile 2; (**c**) Profile 3; (**d**) Profile 4.
# A THz Passive Image Generation Method Based on Generative Adversarial Networks
###### Abstract
proposed an improved WGAN model by using gradient penalty to replace the weight clipping operation in WGAN, named WGAN-GP, which avoided the problem of extreme weight parameter distribution due to weight clipping [13]. In the abovementioned GAN models, simple stacked deep convolutional network structures are used. Generally speaking, to enhance the feature extraction ability of the model, the most direct way is to increase the network depth, but some studies found that blindly increasing the network depth will cause the problem of network degradation. To enhance the feature-learning ability of deep convolutional network, avoid network degradation and vanishing gradient problems in the deep network structure, a generative adversarial network model using residual structure [14] is proposed in this paper, named Res-WGAN-GP. Moreover, the loss function of WGAN-GP is used to the proposed model to maintain the training stability. According to the special requirements of the loss function, different residual block structures are designed for the generator and discriminator. In addition, a quality evaluation method suitable for a THz passive image generation task is proposed. Finally, the proposed model can generate high-quality THz passive images to augment the dataset. The main contribution of this paper is the first attempt to apply deep-learning technology to achieve low-cost terahertz passive image data augmentation, which aims to help the further application of terahertz passive imaging systems in the field of security inspection. This rest of paper is organized as follows. A detailed description of the Res-WGAN-GP model is given in Section 2. Then the experimental results based on 0.2 THz band passive imaging dataset are given in Section 3. Then, the resulting analyses of the generated images are discussed in Section 4. Finally, a conclusion is drawn in Section 5.
# Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction
## 6 Discussion
### Modality of communication  
Though our findings suggest that pedestrians rely on legacy behaviors (driving style) rather than the information on an external display, many participants, however, preferred additional displays on AVs.  
Display text messages such as'stop' or 'go' or other symbolic form messages need to be clear, simple, and easily readable. In pedestrian and AV interaction, the unavailability of such informal communication leads road users to feel unsafe [46]. Pedestrians have to understand and interpret display signals in a limited time. Among display options, significant diversity was observed; around one-third of the pedestrians preferred to use'red' and 'green' lights options, while few favored lighting patterns for visual communication.  
Similarly, around one-fourth found symbolic indication of 'crossing' or 'not crossing' as suitable communication. Very few believed that conventional techniques such as a horn would be suitable for communication. In summary, there was no consensus about any specific external human-machine effective AV-to-pedestrian communication.
# An Innovative Low-Cost Equipment for Electro-Concentration of Microalgal Biomass
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Strain** & **Electrode Material** & \begin{tabular}{c} **Working** \\ **Volume (I\({}_{3}\))** \\ \end{tabular} & \begin{tabular}{c} **Biomass** \\ **Concentration (g/I)** \\ \end{tabular} & \begin{tabular}{c} **\# of Electrodes** \\ **Mixing (typm)** \\ \end{tabular} & \begin{tabular}{c} **Time(min)** \\ \end{tabular} & \begin{tabular}{c} **Efficiency (\%)** \\ \end{tabular} & **Author** \\ \hline \hline Chlulla sp. M 11/11 & Stainless steel & 0.4 & 1.5 & 2 & — & 30 & 98 & [1] \\ Chlulla sp. 0217 & Graphite coupled with chitosan & 1 & 0.5 & 2 & 30 & 3 & 90 & [16] \\ Chlulla sp. (PTCC 6010) & Al & 1.28 & — & 4 & \
\begin{tabular}{c} 100 (high), 30 \\ (low) \\ \end{tabular} & 1 (high), 15 & 96.8 & [5] \\ Chlulla pyramidal & Al, Zn, Cu, Fe, and & & 3 & & & & \\ non-sacrificial carbon electrode & 0.6 & \(22\pm 0.15\) & \(2\) cathodes, 1 & — & 5 & 95.83 & [25] \\ Chlulla vulgaris & Al & 0.4 & — & 2 & — & 8 & 100 & [8] \\ Chlulla vulgaris & UTEX 1803 & Al and Cu & 0.5 & 0.9 & 2 & 200 & 25 & 97-88 & [13] \\ Chlulla vulgaris & Al or Fe (Anode), and 1 GO/TiO\({}_{2}\) & 1 & 0.5 & 2 & — & 30 & 88 & [26] \\ Chlulla vulgaris & (Anthode) & 1 & 0.5 & 2 & — & 20 & 95.4 & [27] \\ Demodomonas subjects & Al or Fe Spinal electrode & — & — & — & 20 & 95.4 & [27] \\ Demodomonas subjects & Al or Fe Spinal electrode & — & 0.88 & 2 & 150 & 3 & 97.16 & [3] \\ Demodomonas subjects & Al & 0.3 & — & 2 & 100 & 7 & 98.99 & [15] \\ Demodomonas subjects & Al & 1 & — & 2 & 200 & 45 & 100 & [19] \\ Chlorovirus aeruginosa & Al and Fe & 1 & — & 2 & 200 & 50 & 100 & [29] \\ Photardardynchrotron & Al or Fe (Anode), and 1 GO/TiO\({}_{2}\) & 1 & 0.5 & 2 & — & 20 & 85 & [26] \\ Semodomonas sp. & Al and graphite & 0.34 & 0.25 & 2 & — & 20 & 98.5-92 & [17] \\ Semodomonas activities & Mg, Al, Zn, Cu, Fe, and brass & 0.09 & — & 2 & 100 & 7.3-30.9 & 90 & [18] \\ Semodomonas ubiquitous & Graphite mixed with Al\({}_{2}\)SO\({}_{4}\)) & 0.9 & 2.4 &
\begin{tabular}{c} (2 cathodes, 1 \\ \end{tabular} & — & 60 & 83 & [4] \\ Tetraselins sp. & Al & 4.8 & — & 2 & — & 15 & — & [6] \\ Semodomonas sp. UFPS\({}_{0}\)02 & Al & 2 & 1.2 & 11 & 150 & 15 & 100 & This paper \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Electrode materials evaluated for the harvesting of microalgae and cyanobacteria.
## 5 Fatigue and Rutting Damage Analysis
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Mixture Type** & **Strain Types** & **Value [Microns]** & **Number of Passes to Damage** \\ \hline \multirow{2}{*}{SBS-7\%} & \(\varepsilon_{t}\) & 29.4 & \(1.18\times 10^{10}\) \\  & \(\varepsilon_{c}\) & 562.4 & \(1.52\times 10^{6}\) \\ \hline \multirow{2}{*}{LF} & \(\varepsilon_{t}\) & 24.6 & \(1.98\times 10^{10}\) \\  & \(\varepsilon_{c}\) & 471.5 & \(4.36\times 10^{6}\) \\ \hline \multirow{2}{*}{PF} & \(\varepsilon_{t}\) & 22.7 & \(2.71\times 10^{10}\) \\  & \(\varepsilon_{c}\) & 469.5 & \(5.63\times 10^{6}\) \\ \hline \multirow{2}{*}{BF} & \(\varepsilon_{t}\) & 20.1 & \(4.63\times 10^{10}\) \\  & \(\varepsilon_{c}\) & 410.6 & \(6.57\times 10^{6}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Microstrains and number of passes to fatigue and rutting damage. Figure 10: Comparison of number of passes to rutting damage. Figure 9: Comparison of number of passes to fatigue damage. Rut depth at 1.6 million passes for each mixture type was calculated and shown in Figure 11. As observed, the maximum magnitude of rut depth is shown by for SBS-7% only mixture at 5.9 mm. The lowest magnitude of rut depth is shown by BF mixture at 3.5 mm. PF closely follows the rut depth of BF at 4.1 mm. LF also exhibits a closer rut depth magnitude to that of PF at 4.6 mm.
## 2 Materials and Methods  
Since the classical U-Net network model based on the coding and decoding structure is prone to spatial accuracy loss, the study presented in this paper takes the improved network model F EPA-Net as the core, obtains deep multi-scale feature perceptual field information through the feature extraction module, increases the number of network convolutions,and adds the position attention module, which can effectively enhance the segmentation precision of building-related information in remote sensing images. The technical roadmap of this paper is shown in Figure 1. First, we use two datasets, namely the Massachusetts dataset and the WHU aerial imagery dataset. The training set and the validation set are input into the FEPA-Net model. Through training and optimization, the parameters are adjusted to improve performance. Finally, the obtained optimal model is used to evaluate the accuracy of the test set and obtain the prediction results of the remote sensing images.