esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Cell cytotoxicity  
The growth and spread of tumors are marked by an increase in cell proliferation and a decrease in the process of apoptosis. The signals that encourage cell proliferation result in uncontrolled growth, which is a significant characteristic of cancer. Apoptosis, or programmed cell death, on the other hand, is a process that typically disposes of damaged, unnecessary, or potentially harmful cells [50].  
Specific mechanisms inside the cells can prevent cell apoptosis during tumor formation, which can lead to tumor cell proliferation. It is essential to develop chemical molecules that can trigger apoptotic processes in tumor cells, as it can help eliminate cancerous cells [51].  
Our study aimed to investigate the effect of specific compounds on the LoVo and SKOV-3 human tumor cells compared to normal cell line HUVECs. We analyzed the impact of these compounds on cell proliferation and apoptosis. The study's positive control was the cytostatic CisPt, which is commonly used to treat colon and ovarian cancer. We exposed the cell lines to different concentrations of the compounds for 24 and 48 h. To determine the apoptotic process, we used double labeling with annexin V-FITC/PI and flow cytometry. This method helped us identify the population of cells in early or late apoptosis and those in necrosis. Furthermore, we compared the effects of the analyzed compounds on tumor cells to those on normal cells.  
The obtained data revealed differences in the effectiveness and specificity between the compounds we studied compared and the clinically used cytostatic. In analyzing the impact of these compounds on the apoptotic processes and proliferation, we were able to gain a more comprehensive understanding of their mechanism of action.
# Information-Centric Network-Based Vehicular Communications: Overview and Research Opportunities
## 5 ICN-Based VANET Research Opportunities
### ICN-Based VANET Mobility  
Mobility is a critical challenge to the ICN deployment corresponding to all emerging technologies [40]. In ICN, when subscribers change their location, their connectivity is changed from one node to the other. However, as no IP address is used to route contents, it is transparent, in contrast to IP, in which addresses are changed [41]. In the VANET environment, content objects must pass a centralized facilitator (vehicle having sensors) before reaching the actual subscriber. This is the most crucial module because contents in VANETs travel along a longer path rather than the best one. Mobility in ICN is achieved through a paradigm, known as publish-subscribe Internet model. In this approach, interested subscribers request particular contents by sending request messages without knowing the location of the content, and the publisher responds with the actual content [41].  
This phenomenon guarantees secure content distribution because of the publisher and subscriber decoupling, and thereby catch the attention of the ICN and VANET communities for integrating these emerging models. However, providing mobility support in ICN-based VANETs requires  
Figure 4: An example of research challenges faced by Vehicular ICN.  
smart and suitable techniques so that content should route to a particular destination without extra retrieving delay.
# Progress in THz Rectifier Technology: Research and Perspectives
###### Abstract
This flow is conveyed to the feed point of the antenna where the electric field (\(E\)) intensity obtained is one hundred times greater than the incident radiation. The second block is constituted of an ultra-high-speed diode. The diode must be optimized to rectify higher frequency. By assuming appropriate impedance matching between the equivalent antenna resistance and the equivalent diode resistance, needed to reach good conversion efficiency, when SPPs flow reaches the end of the antenna, it is captured by the diode positioned in the antenna feed point, obtaining a current flow in a single direction. At THz regimes, the diode must have a very short response time, i.e., it should have a  
Figure 1: Architecture of a typical THz rectenna. lower RC time constant (\(10^{-15}\) s) than the AC cycle period. In principle, devices based on the electron tunnel respond to THz radiation with no losses. Furthermore, the open circuit voltage of the single antenna is about a few tens of picovolt and this might be insufficient for the rectification process to be efficient. The only way to overcome this problem is to design a diode that turns on at a voltage equal to the open circuit voltage of the antenna. The output voltage of the rectifier is not stable and is affected by ripples. To overcome this issue, a low pass filter (LPF) not visible in Figure 1 is introduced at the output of the circuit to produce a more stable and regular DC voltage. A DC-DC converter is also required to adapt the LPF output voltage levels to the level required by a storage device, usually a rechargeable battery not visible in Figure 1 that stores the excess energy for later use. Finally, the third block represents a load powered by a constant signal (DC). The load could be a resistor, a capacitor, an inductor, or a combination of all these elements [1; 2; 19; 20]. The diode at the THz frequency plays a crucial role in improving the conversion efficiency of EM waves to DC. For energy harvesting (EH) applications, only the zero bias rectification process is considered of interest. Despite recent advancements, there are still a number of unresolved technological challenges at these frequencies. This review aims to provide a wide overview of recent research progress, specific issues, performance, and future directions on THz rectifier technology based on quantum tunneling (single insulator and multi-insulator diodes) and ballistic or quasi-ballistic transport. This paper is organized as follows: Section 2 discusses the status of planar diode technology (single and multi-insulator), including operation, performance criteria, and applications from IR to optical response. Section 3 describes the status of geometric diode technology (up to 28.3 THz), including operation, performance criteria, and applications. Finally, Section 4 provides perspectives and conclusions.
# Salient Object Detection via Fusion of Multi-Visual Perception
## 6 Discussion
### Performance with Low Resolution  
To further validate our method's effectiveness for low-resolution images, we conducted relevant experiments. Testing across different image resolutions yielded typical results as shown in Figure 11. Our method performs well across various low-resolution images. However, as resolution decreases further, detection becomes increasingly affected by background interference, making background areas easier to detect. When resolution reaches its limit, such as 200 \(\times\) 150, subtle feature detection, including shape structures and fine edges, is impaired, lowering detection accuracy. Nevertheless, salient areas remain recognizable. Therefore, our multi-visual perception-feature-based method maintains effectiveness even at low image resolution. However, detection precision decreases at very low resolutions.  
Figure 10: Typical example of representation feature distribution of salient objects. (**a**) Original image. (**b**) Original image MSCN histogram. (**c**) Salient region contrast histogram. (**d**) Hue statistics histogram. (**e**) Hue edge statistics histogram. (**f**) Hue growth result.  
In general, our method optimizes salient object detection by integrating image features aligned with human visual perception, as elaborated in Section 3.2. It is particularly effective in natural environments and adept at capturing complex scene nuances via nuanced use of perceptually relevant features. This approach markedly outperforms conventional methods, showcasing adaptability to dynamic visual characteristics in natural images. The method's precision and robustness make it valuable for diverse applications in natural image processing and computer vision.
## 2 System Model and Channel Model
### Outage Probability  
Outage probability is an important performance measurement, typically used to characterize the events that the instantaneous data rate is less than the target rate under imperfect CSI [22]. Defining the transmission target rate of the \(k\)-th UD as \(v_{k}\), and the outage probability can be written as  
\[\Pr[R_{k}<v_{k}] =\Pr[\frac{|h_{k}|^{2}p_{k}}{\sigma^{2}}<2^{v_{k}/b}-1]\] \[=\Pr[\frac{|h_{k}|^{2}}{\sigma_{h,k}^{2}}<\frac{\gamma_{k}\sigma^ {2}}{p_{k}\sigma_{h,k}^{2}}]\] \[=F_{X_{k}}(\frac{\gamma_{k}\sigma^{2}}{p_{k}\sigma_{h,k}^{2}}). \tag{11}\]where \(\gamma_{k}=2^{v_{k}/b}-1\) and \(X_{k}=\frac{|h_{k}|^{2}}{\sigma_{hk}^{2}}\). It is obvious that \(X_{k}\) is a random variable that obeys non-central chi-squared distribution with degrees of freedom 2, and its non-central parameter is \(\lambda_{k}=\frac{|h_{k}|^{2}}{\sigma_{hk}^{2}/2}\), i.e., \(X_{k}\sim\chi^{2}(\lambda_{k})\). Due to that the generalized Marcum \(Q\)-function \(Q_{n}(a,b)\) is the complementary cumulative distribution function (CCDF) or reliability function of the normalized non-central chi-squared distribution with \(2n\) degrees of freedom, the outage probability can be rewritten as [23]  
\[\Pr[\chi^{2}(\lambda_{k})<\frac{\gamma_{k}\sigma^{2}}{p_{k}\sigma_ {hk}^{2}}] =F(\frac{\gamma_{k}\sigma^{2}}{p_{k}\sigma_{hk}^{2}})\] \[=1-Q(\sqrt{\lambda_{k}},\sqrt{\frac{\gamma_{k}\sigma^{2}}{p_{k} \sigma_{hk}^{2}}}), \tag{12}\]  
where \(Q_{n}(\sqrt{a},\sqrt{b})=\int_{b}^{\infty}\frac{1}{2}(\frac{x}{a})^{\frac{n}{ 2}-\frac{1}{2}}e^{-\frac{x+a}{2}}I_{n-1}(\sqrt{ax})dx\), \(I_{n}\) denotes modified Bessel function of order \(n\). In order to obtain the closed expression of the outage probability, we approximate the non-central chi-square distribution with the central chi-square distribution, which can written as [22]  
\[\Pr[\chi^{2}(\lambda_{k})<\frac{\gamma_{k}\sigma^{2}}{p_{k}\sigma _{hk}^{2}}] \approx\Pr[\chi^{2}(0)<\frac{\gamma_{k}\sigma^{2}/p_{k}\sigma_{ h,k}^{2}}{1+\lambda_{k}/2}]\] \[=1-Q(0,\sqrt{\frac{\gamma_{k}\sigma^{2}/p_{k}\sigma_{hk}^{2}}{1+ \lambda_{k}/2}}), \tag{13}\]  
where \(Q_{n}(0,\sqrt{b})=e^{-\frac{b}{2}}\sum\limits_{m=0}^{n-1}\frac{(b/2)^{m}}{m!}\) when \(n\) is a positive integer. Thus, the closed expression of the outage probability can be approximately written as  
\[\Pr[\chi^{2}(\lambda_{k})<\frac{\gamma_{k}\sigma^{2}}{p_{k}\sigma_{ h,k}^{2}}]\approx 1-\exp(-\frac{\gamma_{k}\sigma^{2}/p_{k}\sigma_{hk}^{2}}{2(1+ \lambda_{k}^{2}/2)}), \tag{14}\]
## 2 Endophytes-Current State of the Art
### Endophytes as Inhabitants of Agricultural Plants
#### 2.2.5 Endophytes of the Most Common Crops
It was also found that inoculation of endophytic microbes (_Acinetobacter_, _Bacillus subtilis_, _Azospirillum brasilense_, _Klebsiella_ sp., _Streptomyces coelicolor_, _Herbspirillum hiltneri_, _Pantoea albagi_ and _Paenibacillus_ sp.) decreased chlorophyll degradation and enhanced the accumulation of soluble sugars, resulting in higher grain yield [27]. The occurrence of endophytic fungi has also been detected in the tissues of wheat plants. It has been evidenced that endophytic fungi can reduce the susceptibility of wheat to pest attacks and pathogens, enhance resistance to drought or high temperatures, and induce plant growth and development [104]. However, the study conducted so far related to the distribution and ecological role of fungal endophytes in wheat plants, and has focused mainly on the Clavicipitaceae family, or rather was limited to the model system of fungi of the genera _Neotyphodiumi Epichloz_[105]. The ITS region as a DNA barcode was used by [PERSON] et al. [106] in the identification of many fungi important for agriculture, such as genera _Colletotrichum_, _Fusarium_, _Alternaria_, _Puccinia_ and _Rhizoctonia_. Rice (_Oryza sativa_ L) is the most important cereal crop for more than 50% of the world's population [107]. Endophytes are crucial for growth and stress tolerance of rice and can be used to increase its yield [107]. The beneficial effects of endophytes on rice growth are mediated by several functional traits such as phytohormones and siderophores production, N fixation and metal detoxification [108]. [PERSON] et al. [108] successfully isolated more than 60 bacterial endophytes from the roots, leaves, stems and grains of rice. The highest number of bacterial endophytes were isolated from the root, followed by the stem, leaf and grains [108]. Two phyla (Proteobacteria and Firmicutes) and five genera _Bacillus_, _Enterobacter_, _Klebsiella_, _Leclercia_ and _Xanthomonas_ were identified in the majority of rice tissues [107; 108]. Other most documented rice endophytes are representatives of the genera _Microocccus_, _Pantoea_, _Lysinibacillus_[109], _Burkholderia_ and _Pseudomonas_[110]. [PERSON] et al. [111] reported that the cultivable seed endophytes were dominated by Proteobacteria and mostly class Gammaproteobacteria. They also confirmed the presence of _Flavobacterium_ sp., _Microbacterium_ sp. and _Xanthomonas_ sp. in the rice seeds [111]. Seed bacterial endophytes were also mentioned as promising PGP activities, including hormone modulation, nitrogen fixation, siderophore production and phosphate solubilization [112]. A summary of the benefits of plant endophytes is illustrated in Figure 2.
## 4 Highly Dynamic Simulations and Results
### Simulation of Inertial Calculation
#### 4.2.2 Stability Simulation under Highly Dynamic Circumstances
In all, the simulation results above have proved that Equation (27) could make a correct judgment about the stability of the tracking loop in consideration of the IMUs' precision, the system parameters, and the vehicle maneuvering.
## 2 Materials and Methods
### Universal GNSS Channel Validation
#### 2.2.3 Spreading Code Schemes Compatibility  
Spreading codes are probably the greatest source of variation among all signals. Indeed, different types are currently broadcast: Gold, Weil, Maximal Length, short cycled linear patterns, _etc._ Rather than deploying dedicated logic to support all signals, a universal memory code approach is used. The remaining signal-specific configuration parameters are the code length and its chipping rate; the only exception being the GPS L2 CL code generated with LFSR logic.
## 3 Results
### Stability of the LiSA Catalyst  
To evaluate the stability of the LiSA catalyst, SEM, XRD, TGA, and lithium content analyses were conducted after 508 min of use. Figure 4a,b compare the diffractograms and TGA curves of fresh and used LiSA catalysts, showing that the crystallinity of the catalyst remained largely unaffected by the reaction. However, TGA revealed a 12% weight loss between 100 \({}^{\circ}\)C and 180 \({}^{\circ}\)C, indicating the presence of residual organic matter. These findings are consistent with the SEM images (Figure 7b), which further illustrate the presence of surface deposits of reaction products on the catalyst after 508 min of operation. Despite these observations, no significant decline in catalytic activity was noted throughout the reaction period, as evidenced by the %FAME values remaining above commercial standards (Figure 5).  
The sustained catalytic performance of the LiSA catalyst may be attributed to the absence of lithium leaching during the reaction. ICP analysis revealed not a decrease but  
Figure 7: SEM images of the LiSA catalyst: (**a**) fresh catalyst, and (**b**) used catalyst after 508 min of reaction.  
an apparent increase in lithium content after the reaction (Table 1). While lithium levels are not expected to rise, as the oil feedstock does not contain lithium, this anomaly might be explained by the previously discussed non-homogeneous lithium distribution within the support matrix. It is plausible that lithium remains intact and does not diminish during the reaction, but its uneven distribution may lead to localized variations in concentration, giving the impression of an increase.  
This combination of structural stability and resistance to lithium leaching underscores the robustness of the LiSA catalyst, making it a promising candidate for prolonged biodiesel production processes.  
This study highlights the advantages of utilizing a structured lithium-impregnated aluminosilicate (LiSA) catalyst synthesized with innovative 3D-printed molds, demonstrating enhanced catalytic activity, stability, and thermal robustness for biodiesel production under room temperature conditions. The findings underscore the energy efficiency of the process, attributed to the cosolvent-assisted transesterification and the potential for cosolvent recovery and reuse. Moreover, the adaptability of the 3D-printed catalyst shape to continuous fixed-bed reactor systems presents a scalable and sustainable solution for industrial biodiesel production. Future work should explore the long-term operational stability of the LiSA catalyst under industrial conditions and evaluate alternative, more sustainable cosolvents to further minimize environmental impacts. For example, solvents such as ethanol, a renewable and biodegradable cosolvent, could offer environmental benefits over conventional synthetic options. Additionally, glycerol, a byproduct of biodiesel production, may be an effective cosolvent, reducing waste and enhancing process sustainability. Propylene glycol and certain vegetable-derived fatty acids could also be explored for their biodegradability and lower toxicity.
# Multiscale Content-Independent Feature Fusion Network for Source Camera Identification
## 2 Methodology
### MCIFFN Structure
#### 2.1.2 SE-SCINet in MCIFFN Structure  
Generally, the deeper the CNN network, the stronger its feature expression ability and the higher its classification accuracy. Deep networks, such as ResNet and DensNet are usually better than shallow networks, such as LeNet and AlexNet. However, for the task of image source forensics, although the detection accuracy of the deep network is higher, the shallow network can also achieve good accuracy, and the network complexity is smaller, and the network reasoning time is faster [16; 17; 36; 37]. Therefore, a shallow network is usually selected for image source forensics.  
The CNN in Figure 3 is a shallow network with an SE structure, and that structure is shown in Figure 4. The network proposed in this paper has five convolution layers, five pooling layers, an SE block, and a fully connected layer. The network input data are an \(64\times 64\times 3\) image patch (\(64\times 64\) pixels, \(3\) RGB color channels). As suggested in [38], in order to keep the computational complexity at bay, we use more convolutional layers with smaller kernel sizes instead of using large kernels and fewer convolutional layers. Therefore, all convolution layers in the network use convolution cores with a receptive field of \(3\times 3\). Because we still want our CNN to be able to model non-linear functions, we use a single ReLU layer towards the first fully connected layer of the network. This will make the CNN have a wide range of camera models due to the fact that the non-linearity can be helpful to capture non-trivial classes.  
Finally, the output features of the fully connected layer are classified by the softmax classifier. In this paper, the standard nonlinear equation is \(f(x)=max(0,x)\). Each convolution layer is followed by a max-pooling operation that helps to retain more texture  
Figure 4: Structure of SE-SCINet network.  
information and improve convergence performance. The network extracts 128-dimensional features, inputs them to the fully connected layer, and outputs the classification results through a softmax classifier. The convolution of the CNN can only fuse the spatial information of images, and then there is also correlation between channels of the CNN. To make full use of the information between channels, we embed an SE module in this CNN to explicitly model the information between channels. The network parameters are shown in Table 1.
## 3 Results and Discussion  
### Microbiological Analysis  
Among the seven analyzed samples, one (sample 7) contained the number of total coliforms (2.4 \(\times\) 10\({}^{4}\) Most Probable Number--MPN/g) and thermotolerant coliforms at 45 \({}^{\circ}\)C (2.5 \(\times\) 10\({}^{4}\) MPN/g) above the limit allowed by the Brazilian (10\({}^{2}\) MPN/g) [26] and European [15] legislations. Escherichia coli and _Salmonella_ sp., molds, and yeasts (4.6 \(\times\) 10\({}^{3}\) Colony Forming Unit--CFU/g) were also identified in this sample. Therefore, it was excluded from the study.  
Coliforms, including _E. coli_ and _Salmonella_ spp., are among the etiological agents frequently identified in outbreaks of foodborne diseases [31]. The count of total coliforms and _E. coli_ reflects the current health condition of the food [32] and indicates fecal contamination [33]. The counting of yeasts and molds in foods can also be used to assess the quality and progression of deterioration and predict the product's shelf life [34]. However, in some cases, like intentional fermentation during postharvest processing of coffee cherries, yeasts can be used for flavor development. Consequently, fermentation must be carried out in a controlled manner to avoid the growth of undesirable microorganisms.  
Because hot water is used for tea preparation, all the infusions, including the one from Sample 7, were microbiologically safe, with zero counts of thermo-tolerant coliforms at 45 \({}^{\circ}\)C, _E. coli_, _Salmonella_ sp. and molds and yeasts. According to the Food and Agriculture Organization [35], the limit of viability and multiplication of pathogenic strains of _E. coli_ in foods is between 6.5-49.4 \({}^{\circ}\)C. Despite the death of yeasts and molds, a concern is the susceptibility of coffee cascara to contamination by mycotoxin-producing microorganisms [36]. Ochratoxin A (OTA) is the most studied mycotoxin in coffee and the only one regulated by European legislation [37]. A recent study has detected OTA (4.3 \(\mathrm{\SIUnitSymbolMicro g}\)/kg) in a coffee cascara tea from Nicaragua at a lower level than that established by the EC (maximum 5 \(\mathrm{\SIUnitSymbolMicro g}\)/kg) [13]. Hot water cannot destroy mycotoxins, which are reasonably soluble [38]. Therefore, coffee cascara may present food security risks common to those observed in dried fruits. Considering the microbiological results, Sample 7 was excluded from the remaining parts of the study. It is worth noting that in the case of iced tea preparation, coffee cascara should always be extracted with hot water and then refrigerated, never cold brewed.