esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Factors Influencing PSMs Production in Plants
### Effects of Cold Stress on PSMs  
Cold stress or low-temperature stress is either chilling (<20 \({}^{\circ}\)C) or freezing (<0 \({}^{\circ}\)C) temperature, and they adversely affect plants' growth and development. Plants growing in sub-tropical and tropical areas are more sensitive to cold stress than temperate species [209]. Cold stress tolerance in plants is achieved through selective expression of stress-defensive genes, which is reviewed by [PERSON] et al. [210]. For instance, [PERSON] et al. [106] investigated transcripts and metabolites in six-day-old tartary buckwheat (_Fagopyrum tartaricum_) after cold exposure (at 4 \({}^{\circ}\)C, for various periods), observing up-regulation of phenylpropanoid biosynthetic transcripts and significant accumulation of anthocyanins and proanthocyanathins, both antioxidative (Table 1) [107]. When two varieties of grapevine _Vitis vinifera_ L. (cold tolerant - [PERSON], and cold-sensitive - [PERSON]) were exposed to 10/7 \({}^{\circ}\)C day/night cycle for 14 h photoperiod at 180-200 \(\upmu\)m/(m2s) irradiance, the cold-tolerant variety had higher total phenolic compound content when assessed using the Folin-Ciocalteu's reagent [211]. Subsequently, when they tested the antioxidant capacities of leaf extracts from two varieties by DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging assay, leaves from cold-tolerant varieties yielded better activity.  
Another exciting example of the role of PSMs in plants under cold stress is the medicinal plant, Indian ginseng (_Withania somifera_ L.), which is the primary source of biologically active withanolides. [PERSON] et al. [108] studied the accumulation of withanolides in response to cold stress in two genotypes of _W. somifera_ (AGB002--wild genotype and AGB025--cultivated genotype). After subjecting these two genotypes to chilling temperature (4 \({}^{\circ}\)C, for a maximum of seven days), bioactive compounds such as withanolide A in the roots and withaferin A in leaves were detected in both genotypes, suggesting the involvement of withanolides in cold tolerance. Moreover, the wild genotype showed a higher accumulation of marker withanolides than the cultivated one, which could mean that plants may not produce relevant bioactive compounds when out of their natural habitat, which is discussed later.  
Glucosylated terpenoids (e.g., some sesquiterpenes) are another group of PSM involved in cold stress tolerance. [PERSON] et al. [111] reported the accumulation of glucosystemed sesquiterpene and nerolidol glucoside (i.e., catalyzed by plant glycosyltransferase, UGT91Q2) in tea plants (_Camellia sinensis_) in response to cold stress (freezing temperature, \(-\)5 \({}^{\circ}\)C, for 4 h). The accumulation of nerolidol glucoside was directly proportional to the expression level of UGT91Q2, indicating that cold stress induces glycosylation in tea. Moreover, the ROS-scavenging ability of nerolidol glucoside was significantly higher than nerolidol, thus increasing cold tolerance in tea.
## 3 Survey of Techniques for Updating
### Traffic Reduction
#### 3.2.1 The Reijers code distribution scheme  
This is principally concerned with reducing the image size [8]. It does this by generating and propagating a diff script, rather than the entire image. The script is downloaded as a series of packets, each of which is self contained and states the address range which it builds (allowing for immediate processing of each packet, and easy identification of missing packets). The script is applied against the currently running program, progressively building a new image in external memory (EEPROM). A boot-loader copies this into code memory (Flash), and then control is transferred to the new image. Packets can be processed out-of-order; missing packets can be identified afterwards, during a verification phase, and the binary data requested from its neighbours. As of 2003, network flooding was not supported, and the script is loaded into EEPROM in its entirety before processing. The major limitation of this algorithm is that the scripting language developed is CPU-specific.  
Whereas size reduction may inherently increase the flexibility of response, there are no specific features in the [PERSON] code distribution scheme relevant to autonomous updates.
# Location-Aware Point-to-Point RPL in Indoor IR-UWB Networks
## 6 Conclusions  
In this paper, the Location-Aware P2P-RPL (LA P2P-RPL) algorithm is proposed, which introduces the Impulse-Response UWB (IR-UWB) based cooperative multi-hop self localization algorithm and the Location-Aware P2P-RPL algorithm for Indoor IR-UWB based networks. Smartphone based Inertial Navigation System (INS) with particle filtering is combined with B-box algorithm to improve the localization accuracy in indoor multi-hop UWB networking environments. The proposed algorithm achieves the energy-efficient P2P data delivery without reducing the networking reliability, and reduces the route discovery message overheads significantly especially in short distance P2P routing operations. Experimental results show that the proposed LA P2P-RPL works effectively to reduce the route discovery forwarding packets by limiting the route discovery region based on the accurate location information of the source and the destination nodes. As the network size increases, the proposed LA P2P-RPL saves the energy consumptions significantly by reducing the re-broadcasting P2P-DIO messages both in transmitting and receiving states compared with P2P-RPL and ER-RPL algorithms. LA P2P-RPL shows similar performance results for the route path finding success rate and the average hop count compared with P2P-RPL which forwards the route discovery packets throughout the whole network. In future research for LA P2P-RPL algorithm, the node mobility, the 3D self localization and 3D routing expansion, and the impacts of self localization errors in multi-hop UWB based networking environments are being prepared.  
**Author Contributions:** [PERSON] and [PERSON] contributed to the main idea of this research. [PERSON] and [PERSON] performed the implementations and simulations. All authors contributed to the writing of this paper. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Acknowledgments:** This paper was supported by Konkuk University in 2017.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 13: Packet delivery ratio (PDR) vs. network size.
# Rheological Characteristics Evaluation of Bitumen Composites Containing Rock Asphalt and Diatomite
## 1 Introduction
Although, diatomic can reduce the fatigue performance of modified bitumen mortar, it can significantly improve the high-temperature performance and moisture stability of the bitumen mixture. The properties of a diatomic and basalt fiber composite-modified bitumen mortar were studied [30]; the results showed that the high-temperature and low-temperature performance of the bitumen were improved. [PERSON] et al. studied the 20 \({}^{\circ}\)C four-point bending fatigue life test and 5 \({}^{\circ}\)C indirect tensile test of a composite modified bitumen with diatomic and basalt fiber [31] and concluded that the fatigue life of the diatomic and basalt fiber modified bitumen increased and that the simultaneous use of diatomic and basalt fiber could make up for the weakness of the bitumen mixture at low temperatures. Diatomite can play an active and effective role in bitumens and bitumen mixtures. The addition of diatomic to asphalt can increase the softening point and viscosity of bitumen and can decrease the needle penetration. Diatomic-modified bitumen has good thermal stability and adhesion. The high-temperature performance and moisture damage resistance of a diatomic-modified bitumen mixture were improved significantly but not the low-temperature performance [32; 33]. [PERSON] et al. evaluated the pavement performance of a rock asphalt and diatomic-modified bitumen mixture and reported that the dynamic stability of bitumen mixture was improved the most; moisture stability is superior when the mixed diatomic content is 20% [34]. The research of bitumen mixture-modified by rock asphalt or single diatomic shows that the two types of materials are effective for improving the pavement performance of bitumen concrete, but there are still many shortcomings in improving bitumen concrete by a single material. Combiningthe two types of materials can overcome their shortcomings and makes full use of the adsorption function of diatomic and the high-temperature performance of rock asphalt. Previous studies focus on the middle- and high-temperature rheological properties of bitumen, but a few of them focus on the low-temperature rheological characteristics, particularly the low-temperature fatigue properties of bitumen. Therefore, the high- and low-temperature rheological characteristics of North American rock asphalt composite diatomic-modified bitumen are investigated in this study.
## 3 Results and Discussion
### R Technique  
The procedures of the R technique are illustrated in Figure 3.  
Step 1: Determine the fluid-to-solid ratio (\(m\beta/V\)) and Freundlich exponent (\(1/n\)) from the experiments (\(m\beta/V=1.196\) and \(n=4\) were obtained in this study).  
Step 2: Plot the experimental concentration decay (ECD) curve (\(c_{t}\) vs. \(t\)) and dimensionless curves (\((C_{t}-C_{e})/(C_{0}-C_{e})\) vs. \(T\)). Determine the experimental time ratio \(t_{0.2}/t_{0.8}\) from the plot. Please note that \(t_{0.2}\) and \(t_{0.8}\) are experimental times corresponding to concentrations (\(c_{t}\)) at 0.2 and 0.8, respectively. \(t_{0.2}\) and \(t_{0.8}\) are equal to 3700 and 13.7 min, respectively. The experimental time ratio of \(t_{0.2}/t_{0.8}\) is equal to 26.91 in this case.  
Step 3: Simulate the theoretical concentration decay (RTCD) curves for various values of the Bi number (such as 1.0, 25, 10, and 40) using Equations (7)-(12). Determine the dimensionless time ratios (\(T_{0.2}/T_{0.8}\)) for various Bi numbers from the RTCD curves. \(T_{0.2}\) and \(T_{0.8}\) correspond to the dimensionless concentration (\(C_{t}-C_{e})/(C_{0}-C_{e})\) at 0.2 and 0.8.  
Step 4: Plot the Bi number and the time ratio of \(T_{0.2}/T_{0.8}\) obtained in step 3. The optimum Bi number can be obtained from the plot by using \(T_{0.2}/T_{0.8}=t_{0.2}/t_{0.8}=26.91\), which was obtained in Step 1, as shown in Figure 3. The optimum Bi number is equal to 40, as indicated in the figure. A complicated computation is required in both Steps 3 and 4. Please note that \(T_{0.2}/T_{0.8}\) is equal to \(t_{0.2}/t_{0.8}\), which can be derived from the dimensionless variable. For example, \(T_{0.2}/T_{0.8}=[(D_{s}/r_{p}^{2})\times t_{0.2}]/[(D_{s}/r_{p}^{2})\times t_{0. 8}]=t_{0.2}/t_{0.8}\).  
Step 5. Plot both the ECD and RECD curves with an optimal Bi number (Bi = 40). \(T/t\) = 1.8 \(\times\) 10\({}^{-4}\) (min\({}^{-1}\)) was obtained in this step by matching both curves, as shown in the figure. For example, \(t\) = 1 min and \(T\) = 1.8 \(\times\) 10\({}^{-4}\), as seen in the plot.  
Step 6. Determine the D\({}_{8}\) value. For example, since \(T\) = (\(D_{s}/r_{p}\)) \(t\), \(D_{s}\) = (\(T/t\)) \(\times\) \({r_{p}}^{2}\) = 1.8 \(\times\) 10\({}^{-4}\) (min\({}^{-1}\))/(0.1 cm)\({}^{2}\) = 3.0 \(\times\) 10\({}^{-8}\) cm\({}^{2}\)/s. Therefore, the \(D_{s}\) value determined by the \(R\) method equals 3.0 \(\times\) 10\({}^{-8}\) cm\({}^{2}\)/s.
## 2 Related Work  
### Malware Detection  
Android malware detection has been extensively studied and broadly divided into signature-based and artificial intelligence-based methods [12].  
[PERSON] et al. [13] obtained features through a static analysis of the AndroidManifest.xml and Android Dalvik executable (DEX) file. They generated four different feature sets: permission, intent filter, API call, and string, and proposed a convolutional neural network (CNN)-based model for malicious app detection by creating a vector of features through a feature embedding model.  
[PERSON] et al. [14] created a hybrid model using a deep autoencoder and convolutional neural network to detect malicious applications. They used seven categories of static features: requested permissions, intent, restricted API calls, hardware functions, code-related patterns, and suspicious API calls. The total number of extracted all individual features was 34,570. Among them, 413 features were used after filtering. Two variant CNN-based models, CNN-S and CNN-P, were used to detect malicious apps.  
[PERSON] et al. [15] presented two methods for processing classes.dex files into fixed-size sequences and using them as input to a deep learning model. This method does not limit the input file size, does not require feature engineering, and consumes few resources.  
[PERSON] and [PERSON] [16] mapped the bytecode of classes.dex to RGB color to create fixed-size color images that revealed visual patterns in malware from the same family. The inception-V3 model detected malware with high accuracy, and the grayscale image was as effective as the color.  
[PERSON] et al. [17] used grayscale images from DEX file bytecodes to detect malware with a CNN model, achieving high accuracy. Image size did not significantly impact performance, and obfuscated apps were also effectively detected.  
[PERSON] et al. [4] constructed MALNET-IMAGE, a dataset consisting of over one million malicious application images, providing a valuable resource for research into malicious apps. Using this MalNet dataset, detection performance was evaluated using CNN-based models such as ResNet, DenseNet, and MobileNet.  
[PERSON] et al. [18] presented an EfficientNet-B4 CNN-based method for Android malicious app detection, wherein the DEX file was transformed into an image and used as model input. This approach demonstrated superior malicious app detection performance compared to pre-trained models such as ResNet, InceptionV3, and DenseNet.  
These influential studies in the field of Android malicious app detection each employ unique approaches, ranging from static analysis and feature extraction to complex deep learning models. Studies focusing on image-based malware detection have demonstrated impressive performance, leveraging the latest CNN-based models.
###### Abstract  
The aim of the present study is to perform a comparative analysis of two actuator disc methods (ACD) and two analytical wake models for wind farm power production assessment. To do so, wind turbine power production data from the Lillgrund offshore wind farm in Sweden is used. The measured power production for individual wind turbines is compared with results from simulations, done in the WindSim software, using two ACD methods (ACD (2008) and ACD (2016)) and two analytical wake models widely used within the wind industry ([PERSON] and Larsen wake models). It was found that the ACD (2016) method and the Larsen model outperform the other method and model in most cases. Furthermore, results from the ACD (2016) method show a clear improvement in the estimated power production in comparison to the ACD (2008) method. The Jensen method seems to overestimate the power deficit for all cases. The ACD (2016) method, despite its simplicity, can capture the power production within the given error margin although it tends to underestimate the power deficit.  
wind resource assessment; wakes; wind farm layout; actuator disc; computational fluid dynamics +
Footnote †: journal: Applied Sciences
###### Abstract  
The research problem described in this article is related to the security of an IP network that is set up between two cities using hosting. The network is used for transmitting telephone traffic between servers located in Germany and the Netherlands. The concern is that with the increasing adoption of IP telephony worldwide, the network might be vulnerable to hacking and unauthorized access, posing a threat to the privacy and security of the transmitted information. This article proposes a solution to address the security concerns of the IP network. After conducting an experiment and establishing a connection between the two servers using the WireShark sniffer, a dump of real traffic between the servers was obtained. Upon analysis, a vulnerability in the network was identified, which could potentially be exploited by malicious actors. To enhance the security of the network, this article suggests the implementation of the Transport Layer Security (TLS) protocol. TLS is a cryptographic protocol that provides secure communication over a computer network, ensuring data confidentiality and integrity during transmission. Integrating TLS into the network infrastructure, will protect the telephone traffic and prevent unauthorized access and eavesdropping.  
Asterisk; Private Branch Exchange based on Internet Protocol (IP PBX); IP telephony; security; Session Initiation Protocol (SIP); Transport Layer Security (TLS); Wireshark
###### Abstract
This work shows the details of the discussed problems and suggested ways to solve them, while maintaining all the requirements of the EN 13796-3 standard and other standards taken into account in material, fatigue and certification tests. An important aspect of the conducted research is the knowledge of the phenomenon of material fatigue. The construction of the gondola, as mentioned earlier, combines aluminum (Al 2024-T4) and steel (welded) elements made of 42 CrMo4 alloy. Depending on the mechanical properties, these materials are characterized by different fatigue strengths caused by a different internal structures and mechanical properties of the materials. Examples of Wohler plots (S-N curve) are presented in Figure 1.  
In general, 2024-T4 aluminum alloy has a lower fatigue strength [25] than 42 CrMo4 alloy steel. In turn, this steel is also characterized by stability in the range above \(1\times 10^{6}\) cycles (no decrease in durability)--endurance limit. In turn, welding the above alloy reduces its fatigue strength, resulting in lower levels of stress to failure, with the same number of cycles. Due to the above, as well as the complex state of stresses and complex geometry combined with the complex state of fastening the elements together, it is not possible to select a single curve that would represent fatigue for the above-mentioned materials that could be used for the production of the gondola. Therefore, it is necessary to carry out overall fatigue tests and to verify the structure as a whole, and not its individual parts in fragmentary tests. The above-mentioned statement is the foundation of the proposed and discussed fatigue tests of gondolas for cableways. The discussed solutions, taking into account additional suggestions and good practices, will be presented on the example of fatigue tests carried out on a gondola for cableways, by TRANSFSTEM S.A. (Wola Dalsza 367, 37-100 Lancut, Poland). Following the presented solutions and suggestions allows you to significantly shorten the research time. In the discussed case, it took only 8 weeks, during which 5 million load cycles were generated and 11 DIC tests and visual inspections were carried out.
# Challenges and Future Trends in the Treatment of Psoriasis [PERSON] and [PERSON]
## 4 Future Aspects in the Treatment of Psoriasis
### Biologic Agents and Small Molecule Inhibitors under Development
#### 4.1.5 ROCK2 Inhibitors  
Rho-associated protein kinase 2 (ROCK2) inhibitors have emerged as potential candidates for psoriasis treatment. By inhibiting ROCK2, these agents modulate inflammatory responses and reduce the production of pro-inflammatory cytokines, offering a new avenue for targeted therapy. One study demonstrated that oral administration of a specific ROCK2 inhibitor, KD025, lead to a 50% reduction in PASI scores from the baseline in 46% of patients with psoriasis vulgaris and significant reductions in IL-17 and IL-23 levels, while IL-6 and TNF-\(\alpha\) levels remained unchanged. These results indicate that an orally available selective ROCK2 inhibitor effectively downregulates the autoimmune response driven by Th17 cells, leading to improved clinical symptoms in psoriatic patients [64].
## 4 Conclusions  
In summary, we investigated the use of PCA-LDA and PLS-DA techniques to obtain reliable classification of Raman spectra measured inside healthy and cancerous colon cells. Specifically, for each cell type, we initially formed two spectral datasets, one comprising spectra measured in regions including the nucleus and another consisting of spectra measured in regions excluding the nucleus. Each of the two whole datasets was randomly split into two subsets: the calibration set, comprising data used to build and optimize classification models, and the test set, comprising data to be used to estimate classification accuracy. We found excellent classification accuracy for both classification techniques in both cell regions, with the PCA-LDA method performing slightly better compared to the PLS-DA method (100% accuracy for the former and 96% accuracy for the latter).  
Although these findings are interesting in promoting translation of Raman spectroscopy and machine learning algorithms in cytology diagnostics, there are still some steps to be taken before assuming such translation possibility is valid. In fact, the main limitation of our findings concerns the use of cell lines instead of cytological specimens from patients. Indeed, cell lines may not fully represent the heterogeneity of the clinical cytological samples. Nonetheless, we believe that the quite large values of standard deviation spectra in Figure 1 could partially account for the heterogeneity of clinical samples and make the results reliable. Moreover, the achieved results should be confirmed for cell samples characterized by different degrees of pathology. However, we maintain that it is possible to apply the suggested approach to any other type of cancer cells. Therefore, this investigation can be considered as a preliminary step towards the adoption of Raman spectroscopy in clinical practice related to cytological diagnostics.  
Conceptualization, G.P and V.C.; methodology, G.P.; software, G.P.; validation, M.L.; formal analysis, G.P.; investigation, M.L. writing--original draft preparation, G.P.; writing--review and editing, G.P. and V.C.; supervision, V.C. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
The data are available upon request from the corresponding author.