esa-sceva/satcom-chunk-collection huggingface dataset:
# Estimation of the Prostate Volume from Abdominal Ultrasound Images by Image-Patch Voting
## 4 Experiments and Results
### Comparison of the Experts, Baseline, and the QDCNN Results  
We evaluated our system by 10-fold cross-validation on our data of 305 AUS images. To eliminate any scale differences between images, we re-sampled each image to a 40 pixel/cm scale using the pixel sizes that are always available from the US device.  
The second row from the bottom of Table 1 (\(AUS_{\text{QN}}\)) shows the MAVD values between our QDCNN system and the experts. Comparing our system volume estimations with expert volume estimations on AUS images, we obtained a 4.95 (\(\frac{4.86+4.52+508+5.37}{4}\)) cm\({}^{3}\) average MAVD value, which is smaller than the average inter-expert MAVD value (5.09 cm\({}^{3}\)) on AUS images. Overall, we can see that our system's volume estimations rank among inter-expert comparisons on AUS images. Table 2 shows the Standard Deviation of Absolute Value Difference (SDAVD) values, respectively. We observe from this table that generally for small absolute-value differences, we see smaller standard deviation values for both manual and automated measurements. In other words, our system's estimations can be considered as stable as the manual estimations.  
To evaluate our system's volume estimations with respect to the gold standard, we compared our system's volume estimations with expert volume estimations on MR images and obtained 6.22 (\(\frac{7.10+6.55+5.37+5.86}{4}\)) cm\({}^{3}\) average MAVD, which is less than both the intra-expert (7.63 cm\({}^{3}\)) and inter-expert (8.06 cm\({}^{3}\)) average MAVD between different modalities (AUS versus MR). We can conclude that experts could possibly produce more consistent and accurate volume estimations under the guidance of our system than the complete manual-annotation method.  
In order to compare our system's performance against the more traditional deep-learning systems, we implemented a baseline system that accepts 300 \(\times\) 600 pixels AUS images as input and produces the diameter endpoint location estimations as the output. We modified state-of-the-art DenseNet121 [45] to produce the endpoint locations. The baseline system differs from our QDCNN with its single-network non-voting structure. The training data set for the baseline system was augmented by random cropping. The comparison between our system and the baseline model shows the advantages of our image-patch voting numerically, which is demonstrated by Table 1's last row (\(AUS_{BL}\)). We obtained an average of 6.73 (\(\frac{7.92+7.27+5.97+5.77}{4}\)) cm\({}^{3}\) MAVD between the baseline system and expertson MR images. Similarly, an average of 6.25 (\(\frac{6.62+6.13+5.79+6.46}{4}\)) cm\({}^{3}\) MAVD was observed between the baseline system and experts on AUS images. Comparing these MAVD values with the values of our system, one can conclude that the image-patch voting technique improves the overall results.
## 5 Conclusions and Future Trends  
Global and European authorities are increasingly concerned with the environmental impact generated by industries, so companies are looking for a greater efficiency and sustainability of agri-food systems. Artichoke and artichoke by-products generated during processing could be an excellent ingredient for other food applications with higher added value, such as the development of additives for processed products or as a substitute for functional ingredients. Its potent antioxidant effect could play an important role in the substitution of synthetic preservatives such as BHA and BHT in perishable meat products. The replacement of traditionally used wheat by artichoke flour in bakery products and pasta could be a promising alternative to enhance the intake of dietary fiber in the diet, contributing to digestive and anti-inflammatory health. Also, its high protein content as well as its good amino acid composition, especially in branched and aromatic amino acids, could be a good choice as an added protein extract in food products. Moreover, as consumers are increasingly interested in less-processed and healthy products, artichoke and its by-products could play a dual role in their incorporation into other food products, contributing to an improvement in the circular economy and providing beneficial effects on hepatic, cardiovascular and neurological health.  
However, although the health benefits of artichoke are widely recognized through in vitro and in vivo studies, the existing literature on its application in food is limited. Additional research is needed to properly mask the bitter taste and color provided by artichoke, as a decrease in overall acceptability has been seen in crackers, meats and yogurt. In addition, there are few studies evaluating the stability of certain compounds present in artichoke as well as their most appropriate extraction through novel techniques such as solvent-mediated or ultrasound-assisted extraction. These aspects are key to achieving the optimal way to incorporate artichoke extracts in food products.  
As a conclusion, _C. scolymus_ L. represents an excellent food in terms of its key contents of bioactive compounds for the maintenance of beneficial health functions. For this reason, it is necessary to take advantage of the considerable potential of artichoke as well as the y-products generated by its processing through appropriate agro-industrial vaporization.  
Conceptualization, P.A. and G.N.; methodology, P.A.; validation, P.A., J.Q., M.d.I.A.R., R.P. and G.N.; investigation, P.A.; writing--original draft preparation, P.A.; writing--review and editing, P.A., J.Q., M.d.I.A.R., R.P. and G.N.; visualization, G.N.; supervision, G.N.; project administration, G.N.; funding acquisition, G.N. All authors have read and agreed to the published version of the manuscript.  
This study forms part of the Agroalnext program and was supported by MCIU with funding from European Union Next GenerationEU (PPRTR-C17.I1) and by Comunidad Autonoma de la Region de Murcia--Fundacion Seneca.  
The authors declare no conflicts of interest.
# A Two-Stage Registration Strategy for Thermal-Visible Images in Substations
## 3 Experimental Results and Discussion
### Experimental Setup and Dataset  
In this paper, 30 pairs of substation images from Yujiatou Substation in Wuhan, China, were selected as experimental registration images. To validate the efficacy of the proposed method across diverse scenarios, the selected experimental data contain the vast majority of the problems with thermally visible image registration: scale differences, perspective differences, image distortion, a large number of detailed features, noise, and rotation.  
The two-stage registration strategy proposed in this paper contains five parameters that affect the registration results, namely, the threshold value for the number of feature points in the Harris corner detector, the number of layers and octaves in the scale space, the additional weight of the matching accuracy and the additional weight of the average running time.  
In general, it is necessary to obtain a large number of highly repetitive feature points to form sufficient matching candidate points. However, an abundance of feature points will adversely impact computational efficiency and result in an excessive number of outliers. Therefore, it is necessary to limit the number of detected feature points. Following the experiment using 30 sets of images, we set the initial value of the threshold to 500 and increased this incrementally by 100 each time until reaching 1200, and we found that, at a threshold of 800, all images were well registered. Below this value, some images showed obvious registration errors, and above this value, the overall calculation time was significantly improved. Therefore, the threshold value for the number of feature points in the Harris corner detector was set to 800 in this experiment.  
Similarly, constructing a suitable scale space is also key to ensuring the registration effect and computational efficiency. In our experiments, we set the number of layers in the scale space to 4-8 and the octave of the scale space for initial registration was 2-4. After testing the above 15 combinations, we found that the optimal combination of layers and octave under this experiment was 6 and 3, and the octave of the two stages of registration was determined by the comprehensive registration index. The parameter settings described above are specifically tailored to this experiment. For other scenarios, adjustments to the parameters should be made according to the actual circumstances.  
The additional weights of the matching accuracy and average running time were set to 0.5 in this experiment, which can be adjusted according to field requirements in practical applications.
# 3R Composites: Knockdown Effect Assessment and Repair Efficiency via Mechanical and NDE Testing
## 2 Materials and Methods
### Equipment for the Mechanical Characterization
#### 2.3.3 Compression after Impact (CAI) Testing  
CAI experiments were performed on a Universal Testing Machine WDW-100 by Jinan S.A. equipped with a 100 kN loadcell according to ASTM D7137. The displacement rate was set at 1.25 mm/min. The dimensions of each specimen were recorded. Each specimen was clamped in an in-house CAI fixture that did not allow the sample to slide or move. Half of the impacted 3R specimens (at each energy level) were subsequently tested for compression after impact (CAI), and the rest of them were repaired and tested again (impact damage and CAI). The mechanical knockdown effect and the repair efficiency (of the 3R specimens) were evaluated in terms of maximum CAI load (kN) and CAI strength (MPa). The maximum CAI strength (MPa) was estimated from Equation (2):  
\[\text{Strength}_{\text{CAI}}=\text{P}_{\text{-max}}/(\text{w }\times\text{h}) \tag{2}\]  
where P is the maximum load (N), w is the width of the specimen (mm), and h is the thickness of the specimen (mm).
## 3 Case Study: Purse Seiner in the Adriatic Sea
### LCA Models for Different Power Systems
#### 3.2.8 The LCA of a Hydrogen-Powered Ship  
In this paper, grey hydrogen (produced by natural gas) and green hydrogen (produced from Renewable Energy Sources (RESs)) are investigated to gain an insight into their feasibility, environmental friendliness, and economic performance as marine fuels.  
Hydrogen represents an ideal fuel for fuel cells. In this paper, a high-temperature Solid Oxide Fuel Cell (SOFC) is selected for further assessment. The annual fuel consumption of hydrogen in a SOFC, i.e., \(FC_{SOFC-H}\) (kg), is calculated with the following equation [86]:  
\[FC_{SOFC-H}=\frac{EC_{SOFC}}{\eta_{SOFC}\cdot L{HV}_{H}}, \tag{14}\]  
where \(\eta_{SOFC}\) refers to SOFC efficiency (60%), \(L{HV}_{H}\) represents lower heating value of hydrogen (kWh/kg), Table 1, while \(EC_{SOFC}\) (kWh) refers to the annual energy consumption of an SOFC-powered ship.  
Selected SOFCs provide fuel flexibility and higher energy efficiency than low-temperature fuel cells, such as a Proton Exchange Membrane Fuel Cell (PEMFC), but they require higher temperatures for operation. The time required for the fuel cell system to reach its operating  
Figure 13: Processes included in the LCA of an LBG-powered ship.  
temperature is referred to as the start-up time, which for the SOFC equals 30 min [98]. The energy required for heating the fuel cell system, \(EH_{FC}\) (kWh), is calculated with the following equation [86]:  
\[EH_{FC}=0.015\cdot 6.7\cdot P_{SOFC}. \tag{15}\]  
The processes included in the LCA of a hydrogen-powered ship are presented in Figure 14. During the ship's operation, there are no tailpipe emissions, i.e., TTW emissions are equal to zero.  
The M phase refers to the process of SOFC manufacturing. Its environmental impact is analysed through the weights of the materials used for SOFC manufacturing [26] as inputs for GREET 2022. Its replacement is considered after 20,000 working hours [86]. The WTT phase of hydrogen includes the processes of feedstock processing, hydrogen production and liquefaction, and finally, distribution to the port. Feedstock processing depends on hydrogen origin. Grey hydrogen feedstock processing refers to natural gas extraction, while the feedstock processing of green hydrogen refers to the production of electricity by RESs. It is assumed that each type of hydrogen is produced in Western Europe, liquefied, and transported to Croatia via tank trucks for 1000 km. Besides the WTT phase of hydrogen, the LCA also contains the WTT phase of electricity, since onshore electricity is used for the start-up of the fuel cells, and it includes electricity generation, transmission, and distribution. The sources included in the European electricity mix in the GREET 2022 software are used for electricity generation in Croatia.
## 2 Materials and LCA Methodology
### Life Cycle Impact Assessment (LCIA)  
The aim of the life cycle impact assessment (LCIA) was to translate the LCI results into meaningful environmental impacts, particularly concerning the environment, natural resources, and human health. The concept of LCA encompasses various terms and concepts, with no universally accepted set of environmental impact categories. Commonly recognized categories include climate change, eutrophication, acidification, stratospheric ozone depletion, human toxicity, aquatic toxicity, fossil fuel depletion, water depletion, and land use.
## 4 Systematic Review of the Research Pillars  
Digital Twins (DTs) driven by AI are essential for improving energy use in commercial buildings and greatly lowering carbon emissions. By integrating complex algorithms and real-time data, these systems improve energy management strategies, resulting in increased sustainability and efficiency. The main methods by which AI-powered DTs achieve these optimizations are outlined in the sections that follow:  
* Real-time monitoring and control: IoT integration, where DTs provide accurate monitoring and control of energy systems by using Internet of Things (IoT) sensors to collect real-time data on occupancy, energy usage, and environmental factors [39]. Also, the Adaptive HVAC Systems: Human-centered energy management systems optimize energy use while preserving comfort by modifying HVAC operations according to occupancy and preferences [40].
* Predictive Analytics and Optimization, including Machine Learning Algorithms: AI methods, including Random Forest Regression, predict energy requirements and maximize power production in microgrids for smart buildings while balancing ecological and economic considerations [41]. In multi-objective Optimization, DTs provide intricate optimization scenarios, optimizing the use of renewable energy while lowering emissions and operating expenses [41].  
Considering the significant advantages of AI-powered DTs, there are still obstacles to overcome in their implementation, such as the requirement for user involvement and the blending of various technologies. To fully utilize digital twins in energy management, several issues must be addressed. Figure 13 summarises the main pillars of the integration between digital twins and AI.  
Figure 13: Digital Twin—AI integration.
# A Tiered Control Plane Model for Service Function Chaining Isolation
## 7 Evaluation and Discussion
### Proof of Concept Demonstration of Data Plane Forwarding
#### 7.1.3 An MTU Increase  
Encrypting IP packets often results in exceeding the Maximum Transfer Unit (MTU) and consequently ends up with packet segmentation. This is considered normal in many encryption set-ups. However, an introduction of another SFC layer can potentially make additional computational overhead and packet segmentation, which results in lower performance in packet forwarding. To prevent packet segmentation, it is possible to increase the MTU. However, adding the original NSH header can alone potentially trigger packet segmentation. If the NSH header length is constant, additional NSH attributes do not influence further packet segmentation.  
This architecture suggests putting the SFC header between the OSI layer 2 and the layer 3. This means that it is the layer 2 or the SFC transport layer that need an MTU increase. Hence, it is the underlying Tier 1 transport that potentially can segment packets. General solutions to this problem are to introduce an MTU limitation in the setup of VNF encryption services or using Ethernet jumbo frames on the transport links.
# Enhancing Chatter Stability for Milling Thin-Walled Blades by Designing Non-Uniform Allowance
## 2 Description of the Methodology
### Design of Thin-Walled Blade Allowance Distribution Based on First-Order Sensitivity
Subsequently, the cross-section curves can be deduced using interpolation, leading to the acquisition of a bias mesh surface with non-uniform thickness for the entire blade via interpolation of each cross-section curve. Example Analysis: Designing Non-Uniform Allowance for Milling Thin-Walled Blades of Titanium Alloy TC4  
The blade has an inlet spread length of 64.7 mm and an exhaust side spread length of 55.0 mm. The tip chord measures 41.3 mm, with the thinnest and thickest points at 0.34 mm and 1.1 mm, respectively. At the root, the blade has the thinnest point of 1.6 mm and the thickest point of 4.11 mm with a root fillet radius of 2.5 mm. The figure in Figure 2 displays the experimental blade made of TC4 titanium alloy with solid structural features. The variable cross-section twisted free-form surface of the blade requires corresponding design allowances for finishing. Design basic processes and steps is as follows. 1. The process system is first meshed, and the mass and stiffness matrices are calculated according to reference [1]. 2. Sensitivity calculation of eigenvalue to mass (Equation (27)) and stiffness (Equation (29)) in the first order. 3. Calculation of the correction (Equation (33)) with reference to the sensitivity of blade mid-axis position. 4. Generation of mesh node interpolation heights (Equations (33) and (34)). 5. Creating the blade cross-section curve using the nodes to form a non-uniform allowances mesh bias surface. 6. Using the bias surface as the driving surface for CNC finishing programming.
## 5 Conclusions  
TEA showed better performance in terms of both encryption and decryption execution times than XTEA and XXTEA. The XTEA was proposed to set the key schedule and XXTEA was proposed in order to present the key material slowly. The proposed algorithm NTSA does the same, and experiments performed proved that the performance of NTSA is better than TEA. In addition to this, NTSA created more confusion on the key than the tiny encryption algorithm. The avalanche effect showed a positive result to NTSA when compared to TEA. Thus, NTSA can be used by all the latest applications in IoT devices with different computational and storage facilities to transfer text files efficiently and securely through the network. The NTSA algorithm security can be further increased by encrypting the compressed file. In future we also aim to integrate and implement this algorithm for data transfer in ad hoc, sensor and fog networks [8; 52; 53; 54; 55; 56; 57].  
**Author Contributions:** Conceptualization, S.R.; formal analysis, S.R. and V.M.; funding acquisition, V.M.; investigation, S.R.; methodology, S.R.; project administration, V.P., V.M. and M.K.; resources, V.P. and V.M.; software, M.K.; supervision, V.P.; validation, S.R. and M.K.; visualization, S.R.; writing--original draft, S.R., V.P. and V.M.; writing--review and editing, V.M. and M.K.  
**Acknowledgments:** Authors would like to thank the Management and Principal of SCMS School of Engineering and Technology for providing the infrastructure and facilities to carry out the research. Authors would also like to thank [PERSON], Assistant Editor for all the support handling the manuscript and the reviewers for providing valuable suggestions and comments in improving the manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Potential of Plant Stem Cells as Helpful Agents for Skin Disorders--A Narrative Review
## 4 Mechanistic Insights into the Skin Aging of Plant-Derived Stem Cells
### Anti-Inflammatory Activity  
Various plant-derived metabolites, such as flavonoid glycosides, phenolic acids, sterols, triterpenes, and lignans, have been proven to exhibit anti-inflammatory activity. It has been demonstrated that the hydrosoluble _Rubus ideaus_ cell culture extract demonstrates significant anti-inflammatory properties, primarily attributed to high concentrations of flavonoids and anthocyanins. This is confirmed by a marked reduction in the expression of inducible Nitric Oxide Synthase 2 (iNOS2) and Cyclo-oxygenase 2 (COX2) [68]. [PERSON] et al. observed that the anti-inflammation activity of the Edelweiss cell extract suppressed iNOS2 and COX2 expression in UV-induced inflammation in a non-dose-dependent manner [22]. Phenolic acid contents in the _Crisium eriophorum_ cell extract were discovered to play a role in the regulation of the inflammatory response, negatively modulating the overexpression of pro-inflammatory cytokines IL-1\(\alpha\), IL-1\(\beta\), IL-8, and tumor necrosis factor alpha (TNF-\(\alpha\)) in keratinocytes, due to microbial aggression [53]. All in all, the findings of the abovementioned studies indicate that plant stem cell extracts are effective anti-inflammatory agents in UV-induced and bacterial inflammation.
## 6 Applications of VSNs  
Actually the development of wireless sensor networks was originally motivated by military applications such as battlefield surveillance. However, wireless sensor networks are now used in many civilian applications, including environment and habitat monitoring, healthcare applications, smart homes, and traffic control. In the following subsections we consider the application of VSNs in battlefield monitoring, rock slides and animal crossing and smart houses [22, 57, 58, 59, 60, 61]. We have briefly explained all the applications in the field VSN with possible case studies in some cases. We do not provide all the cases in all the applications since it would greatly increase the span of the survey.