esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Antioxidant and Radical Scavenging Activities of Cow Yogurts with Different Fat Content  
The antioxidant activities and scavenging of ROS capacities of cow yogurt with 4%, 2% or 0% fat were also assessed. Specifically, the antioxidant activities as determined by DPPH and Folin assays are presented in Table 7 and as determined by the FRAP assay in Table 8.EC\({}_{50}\) values of yogurt pHAP extracts followed the order 4% \(>\) 2% \(>\) 0% indicating that, in DPPH scavenging, non-fat yogurt was the most active followed by semi-fat and full-fat yogurt. As in the case of different full-fat cow, goat and ewe yogurts (Section 3.1), the EC\({}_{50}\) values of cow yogurts with different fat content were 3000-fold higher than those of gallic acid and Trolox standards attributable to the fact that the latter two compounds were pure antioxidants. Antioxidant activities of both pHAP and UC extracts as determined by Folin assay and FRAP assay followed the order 0% \(>\) 2% \(>\) 4%. In both assays, the UC extracts of all the examined yogurts exhibited higher antioxidant activity values than the respective ones in pHAP extracts. This is related to the simplicity of UC procedure (just one centrifugation) against the complex pre-treatment steps of pHAP process (pH adjustment, thermal \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**\% Fat of Yogurt**} & \multicolumn{2}{c}{**DPPH Assay**} & \multicolumn{2}{c}{**Folin Assay**} \\  & **EC\({}_{90}\) (g Yogurt/L Reaction Mixture)** & **(mg Gallic Acid/kg Yogurt)** & **(mg Trolox/kg Yogurt)** \\ \cline{2-5}  & **pHAP Extract** & **pHAP Extract** & **UC Extract** & **pHAP Extract** & **UC Extract** \\ \hline
0 & 1106 \({}^{\text{a}}\)\(\pm\) 11 & 86.8 \({}^{\text{a}\text{A}}\)\(\pm\) 2.8 & 93.2 \({}^{\text{a}\text{B}}\)\(\pm\) 1.9 & 76.5 \({}^{\text{a}\text{A}}\)\(\pm\) 2.4 & 81.8 \({}^{\text{a}\text{B}}\)\(\pm\) 1.7 \\
2 & 1155 \({}^{\text{b}}\)\(\pm\) 11 & 73.7 \({}^{\text{b}\text{A}}\)\(\pm\) 2.6 & 84.3 \({}^{\text{b}\text{B}}\)\(\pm\) 2.4 & 65.0 \({}^{\text{b}\text{A}}\)\(\pm\) 2.3 & 74.1 \({}^{\text{b}\text{B}}\)\(\pm\) 2.1 \\
4 & 1207 \({}^{\text{c}}\)\(\pm\) 10 & 55.1 \({}^{\text{c}\text{A}}\)\(\pm\) 2.9 & 67.9 \({}^{\text{c}\text{B}}\)\(\pm\) 2.5 & 48.5 \({}^{\text{c}\text{A}}\)\(\pm\) 2.6 & 59.6 \({}^{\text{c}\text{B}}\)\(\pm\) 2.2 \\ \hline \end{tabular}  
* Each value was expressed as mean \(\pm\) standard deviation of three replicates. Different lowercase letters in the same column represent significant differences in values (\(p<0.05\)) between cow yogurts with different fat content. Different capital letters in the same row represent significant differences in values (\(p<0.05\)) between pHAP, UC UC preparations of the same yogurt.  
\end{table} 
Table 7: Antioxidant activities of cow yogurts with different fat content preparation obtained by pH adjustment and precipitation (pHAP) or ultra-centrifugation procedure, as determined by DPPH and Folin assays \({}^{1}\).
###### Abstract  
Citrus waste has been used as a source of bioplastics for research in different ways. Because the juice industry produces significant amounts of residue each year, it would be advantageous to use the byproducts in the creation of new materials. Researchers have long explored eco-friendly methods to convert citrus and other organic waste into polymers for producing biodegradable films. The goal of this study is to create biofilms from orange waste (OW) and ginger waste (GW) using an ultrafine grinder and study the films' properties. Since pectin has the ability to gel, and because cellulosic fibers are strong, citrus waste has been studied for its potential to produce biofilms. After being washed, dried, and milled, orange and ginger waste was shaped into films using a casting process. Tensile testing was used to determine the mechanical properties of biofilms, while dynamic mechanical thermal analysis (DMTA), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) were used to determine their thermal properties. As the number of grinding cycles increased, the suspension's viscosity increased from 29 mPa.s to 57 mPa.s for OW and from 217 mPa.s to 376 mPa.s for GW, while the particle size in the suspension significantly decreased. For OW and GW films, the highest tensile strength was 17 MPa and 15 MPa, respectively. The maximum strain obtained among all films was 4.8%. All the tested films were stable up to 150 \({}^{\circ}\)C, and maximum degradation occured after 300 \({}^{\circ}\)C.  
biofilm; bioplastic; orange waste; ginger waste; mechanical properties; thermal properties +
Footnote †: journal: Applied Sciences
## 2 Materials and Methods
### Mesh Generation and Grid Independence Study
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Grid**} & \multirow{2}{*}{**\#Nodes**} & \multirow{2}{*}{**Base**} & \multirow{2}{*}{**\#Cells**} & \multirow{2}{*}{**Runtime/h**} & \multicolumn{3}{c}{**Average Wave**} & \multicolumn{3}{c}{**Average over the Last Second, of**} \\  & & & & & **Runtime/h** & \multicolumn{3}{c}{**Height over the**} & \multicolumn{3}{c}{**Velocity Magnitude**} \\  & & & & **Setup 1 per 100 s** & \multicolumn{3}{c}{**Setup 2 per 100 s**} & \multicolumn{3}{c}{**Last X Seconds/m**} & \multicolumn{3}{c}{**at Probes/m/s**} \\ \cline{5-12}  & & & & **1 s** & **2 s** & **3 s** & **Probe 1** & **Probe 2** & **Probe 3** & **Probe 4** \\ \hline
1 & 32 & 2.3 & 0.7\(\times\)10\({}^{6}\) & 06:13 & - & - & - & - & - & - & - & - \\
2 & 32 & 1.1 & 1.1\(\times\)10\({}^{6}\) & 06:20 & 16:50 & 0.96 & 0.94 & 0.95 & 2.88 & 5.03 & 5.29 & 5.42 \\
3 & **32** & **0.6** & **2.2 \(\times\)10\({}^{6}\)** & **10:16** & **19:46** & **0.92** & **0.92** & **0.93** & **2.68** & **5.00** & **5.28** & **5.35** \\
4 & 32 & 0.5 & 3.2\(\times\)10\({}^{6}\) & 12:39 & 22:03 & 0.98 & 0.98 & 0.98 & 2.96 & 5.01 & 4.96 & 5.27 \\
5 & 64 & 0.4 & 5\(\times\)10\({}^{6}\) & 16:38 & 28:24 & 0.90 & 0.90 & 0.92 & 2.96 & 5.02 & 4.98 & 5.37 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Grids and runtimes used for the grid independence study. Setup 2 results in numerical instabilities on the coarsest grid. Results of the grid independence study: the average wave height over the last 1, 5, and 10 s, and the average velocities at different probe locations (see Figure 5) over the last second. For further simulations, Grid 3 is used as a compromise between accuracy and computation time. Also, the grid resolution is sufficient to resolve geometric features such as baffles. Figure 5: Visualization of probe locations for velocity measurements (1–4, red dots) and the wave height measurement (5, black line), which were selected to facilitate validation. The light blue arrow indicates the flow direction.
## 11 Conclusions  
The integration of big data and blockchain technology represents a significant leap forward for decentralized decision-making across various industries. This comprehensive review has explored how these two powerful technologies intersect, examining their combined benefits, challenges, and real-world applications.  
Blockchain technology, with its decentralized, immutable ledger, provides a secure and transparent framework for data management. Its ability to ensure data integrity and prevent unauthorized tampering makes it an ideal partner for big data, which is characterized by the five V's: volume, velocity, variety, veracity, and value. By leveraging blockchain's strengths, organizations can enhance the reliability and security of their big data initiatives.  
Big data analytics, on the other hand, offers the tools needed to process and analyze vast amounts of data in real time, extracting meaningful insights that drive informed decision-making. When integrated with blockchain, these analytics can operate on a more secure and trustworthy data foundation, ensuring that decisions are based on accurate and untampered information.  
This synergy between big data and blockchain facilitates several key advantages. Enhanced data security and integrity are crucial for maintaining the trustworthiness of information used in decision-making. Improved transparency and traceability allow organizations to track data provenance and ensure authenticity, which is particularly valuable in supply chain management and other sectors where tracking the origin and journey of products is essential. Real-time data processing capabilities enable swift responses to emerging trends and threats, while predictive analytics and automation streamline decision-making processes, making them more efficient and reliable.  
Despite these promising benefits, integrating big data and blockchain technology is not without its challenges. Scalability issues, data privacy concerns, interoperability hurdles, regulatory compliance complexities, high implementation costs, and the need for skilled professionals are significant obstacles that need to be addressed. By focusing on innovative solutions to these challenges, organizations can unlock the full potential of these technologies.  
The real-world applications and case studies highlighted in this paper, such as Estonia's blockchain-based healthcare system, IBM and Walmart's Food Trust blockchain platform, and the Brooklyn Microgrid project, demonstrate the transformative impact of integrating big data and blockchain. These examples showcase how these technologies can enhance data security, transparency, and operational efficiency, driving innovation and improving outcomes in the healthcare, supply chain management, and energy sectors.
# Analysis of Application Parameters of Hydraulic Slotting Technology in Jointed Coal Reservoirs
## 4 Field Application
### Application Effect  
As shown in Figure 13, the extraction rate of the optimized slotted borehole was 1.3 times that of the conventional slotted borehole, and the extraction rate of the conventional slotted borehole was 3.8 times that of the conventional borehole. The average gas extraction rate of the optimized slotted borehole, conventional slotted borehole, and conventional borehole was 0.73 m\({}^{3}\)/min, 0.55 m\({}^{3}\)/min, and 0.14 m\({}^{3}\)/min, respectively. The average gas extraction rate over one month was calculated as shown in Figure 14. The variation trends of the gas extraction rate were approximately the same for the two borehole types. The trend gradually decreased as the extraction time increased, and the reduction rate gradually decreased. According to the overall trend, the gas extraction rate after slotting was always higher than that of the conventional borehole, which was approximately 3-4 times equal that of the conventional borehole.  
Moreover, it was found that a borehole with a small angle to the coal seam had a high gas drainage flow, mainly owing to the angle between the water jet impact direction and the coal bedding. An appropriate angle between the cleats and borehole makes it easier for cracks to form on both sides of the cleats, and increases the coal seam permeability. The results revealed that the slot greatly increased the coal seam permeability and enhanced the extraction effect. Additionally, the extraction rate of the optimized slotted borehole was higher, which confirms the results of the aforementioned analysis.
## 3 Results
### Physiological and Phenotype Analysis  
The physiological and phenotypic analyses are presented in Figure 2. The results indicated that salt stress significantly influenced the antioxidant enzyme activities and osmoregulatory substance content in the two _A.__mongholicus_ varieties, with variations in the intensity of their responses. The H\({}_{2}\)O\({}_{2}\) and OFR contents in 'LQ' increased by 41.0% and 13.6%, respectively, which were significantly lower than those in the 'DT' (51.2% and 18.6%) under salt stress. 'LQ' exhibited reduced accumulation of reactive oxygen species (ROS) under salt stress compared to 'DT', indicating a stronger ROS scavenging capacity, which mitigated oxidative stress-induced damage. Additionally, the activities of SOD, POD, and CAT in 'LQ' increased by 22.8%, 10.9%, and 8.8%, respectively, which were significantly higher than 'DT' (2.9%, 8.5%, and 1.4%). The soluble sugar and protein contents in both  
\begin{table}
\begin{tabular}{c c c} \hline \multicolumn{2}{c}{**Gene ID**} & \multicolumn{1}{c}{**Primers (5\({}^{\prime}\) to 3\({}^{\prime}\))**} \\ \hline \multirow{3}{*}{} & EF-1-alpha & F: TCAGGAAGCTCTTCCTG \\  & & R: CAATGTGAGAGGTGTGGCCAG \\ \hline \multirow{3}{*}{} & Cluster-33548.11 & F: GGCTATTGGTACTGCAAACCCAT \\  & & R: ACCACCACCATGTCTTGTCAG \\ \hline \multirow{3}{*}{} & Cluster-46405.0 & F: TGGGAAATGCAAATTCTTCCACTCC \\  & & R: AGAGCCCTTCAAAGTGCAG \\ \hline \multirow{3}{*}{} & Cluster-46405.4 & F: TAACGATTGTATGAGCAAAACCGG \\  & & R: TTACCACTACTACGCCTCGGGC \\ \hline \multirow{3}{*}{} & Cluster-28058.0 & F: ATGGTGATTTCAACCAAGCCT \\  & & R: GTGCCAGCAGGTATCCGG \\ \hline \multirow{3}{*}{} & Cluster-55450.0 & F: ATTGGCCTTGGAGGACTTTG \\  & & R: GGTTGTTAAAGAAGGAGGTTGT \\ \hline \multirow{3}{*}{} & Cluster-45789.7 & F: GCGAGCATGAAGTTTGGTGTGTGT \\  & & R: GACCAGGACCACCCTTCAGAT \\ \hline \end{tabular}
\end{table}
Table 1: qRT-PCR primer sequence information.  
Figure 1: Phenotypes of _A.__mongholicus_ leaves.  
varieties significantly increased under salt stress, by 2-fold and 16.9% in 'LQ' and by 67.0% and 18.8% in the 'DT', respectively. Furthermore, salt stress induced the peroxidation of membrane lipids, causing cell membrane damage, with the MDA content in 'LQ' showing an increase of only 14.7%, significantly lower than the 58.0% increase observed in the 'DT'.  
In terms of morphological indicators, the results indicated that salt stress significantly influenced plant height, root length, root thickness, and fresh weight in the two _A.__mongholicus_ germplasms. In LQ, plant height decreased by 29.0%, whereas DT showed a larger reduction of 42.9%. Root length in LQ decreased by 5.0%, compared to a 44.9% reduction in DT. Root thickness in LQ showed a slight decrease of 2.8%, while DT experienced a more significant decrease of 46.3%. Fresh weight decreased by 22.3% in LQ and 41.4% in DT, indicating that LQ demonstrated better resilience to salt stress.
# Low-Order Spherical Harmonic HRTF Restoration Using a Neural Network Approach
## 3 Machine Learning HRTF Restoration
### Model Enhancement
#### 3.3.3 Model With Dropout  
Dropout randomly \"drops out\" a percentage of nodes in the neural network during training. The idea is to avoiding co-adaption between nodes by never guaranteeing that any pair will both be used during the training process to avoid the model over-relying on a few nodes within a layer [63; 64; 65]. It can also been seen as randomly sampling from the exponential number of possible narrow sub-networks during training, and then providing an average the performance of all these combinations in test time or application. Note that a dropout layer can only apply on fully connected layers but not convolutional layers. The model uses a 20 percent dropout ratio on the second to fourth fully connected layer.  
The model (Model D in Table 7) produces worse results with the test data compared to the baseline model, especially with the hold out SADIE II data, but performs slightly better with the validation data. However, such slight differences may be introduced by the randomness of machine learning training. According to the result, dropout seems to have a more negative impact on regularisation compared to weight decay. In theory it is possible to increase the dropout ratio or use a different configuration to increase the regularisation effect. However, finding the optimal architecture and hyper-parameters is beyond the scope of this paper and could be part of the future work.
# Review of the Research Progress in Soft Robots
## 2 Driven Methods and Materials for Soft Robots
### Chemical Reaction Driven  
A chemical reaction is a process in which molecules break into atoms and the atoms rearrange themselves to form new molecules. Chemical reactions can be divided into compound reactions, decomposition reactions, displacement reactions, and metathesis reactions according to the types of reactants and products. Chemical reactions are usually accompanied by changes in energy, so they are chemical reaction-driven soft robots that convert chemical energy into mechanical or kinetic energy by means of combustion, expansion, or catalytic reactions [73].  
Shown in Figure 7a, Harvard University printed the functional body of a robot directly on a multi-material three-dimensional (3D) printer, by filling it with butane and oxygen, which expanded on the ignition to provide power for cordless jumping [74]. This driving method is similar to pneumatic driving, but the source of the gas medium is different. Due to the effect of the gas production efficiency of the chemical reaction, this kind of driving mode is mostly used for small tethered soft robots. The repetitive use of a chemical reaction that is driven is still a technical challenge for soft robots [75]. Shown in Figure 7b, [PERSON]'s group developed the world's first fully soft-bodied autonomous micro-bionic robot, Octobot. The robot moved by embedding the components required for fuel storage, catalytic decomposition, and actuation. This allowed it to move by expanding the fluid network downstream of the reaction site through the gases generated by the decomposition of the fuel [76]. He et al. designed a chemical reaction self-driven rolling robot. The reaction liquid and catalyst were placed inside the robot. The gas generated by the chemical reaction pushed the reaction liquid to circulate in the multiple cavities of the robot, changing the center of gravity of the robot to achieve rolling [77].
# Antioxidant Production in _Dunaliella_
## 6 Post-Culture Downstream Processing
### Post-Harvesting Storage Processing  
For _Dunaliella_ to be a viable and sustainable natural antioxidant enzyme source, suitable drying and storage of biomass must be established. Optimized post-harvest storage conditions can minimise the loss of antioxidant enzyme activity and increase these valuable compounds' shelf life. Cold storage is commonly used to preserve chemical, nutritional, and sensory properties of post-harvest processed living cells as respiration and other metabolic reactions are reduced at lower temperatures [169]. Biomass can be prepared for cold storage via a dry or a wet route. In the dry route, _Dunaliella_ biomass is freeze-dried or air-dried, then stored at cold temperature. In contrast, in a wet route, biomass is preserved at cold temperature straightway [25]. Several reports demonstrate that antioxidant stability depends on the type of biomass, type of chemical components, length of storage time, storage temperature, and drying method [170; 171; 172; 173]. [PERSON] et al., (2020) compared the storages of both wet and freeze-dried algal biomass and suggested that CAT and SOD activity in freeze-dried _D. tertiolecta_ biomass can be retained for eight months when stored \(-20\)\({}^{\circ}\)C, whereas activities in wet biomass or crude extract remain unchanged for four months when stored at \(-80\)\({}^{\circ}\)C [174; 175; 176]. Therefore, using wet biomass, either fresh or frozen, as feedstock may be an economically feasible method for antioxidant enzyme storage compared to dried cell storage. Extraction procedure of antioxidants from algae biomass depends on the desired products. For example, lipid-soluble antioxidants (e.g., carotenoids,tocopherol, flavonoids, ascorbate) are extracted by organic solvents (e.g., hexane, heptane, methyl tertiary burate, methanol, ethanol) with a mechanical treatment (e.g., ultrasonication, microwave, high pressure) [174; 170; 2; 10]. Water-soluble antioxidants or antioxidant enzymes are recovered from the algae biomass by aqueous solvent or buffer systems together with mechanical assistance [175; 176; 177; 128; 178]. Recently, green solvents (e.g., cyclopentyl methyl ether (CPME), dimethyl carbonate (DMC)), ionic liquids (e.g., ethanol containing 1-n-butyl-3-methylimidazolium) and supercritical CO\({}_{2}\)--based extraction have been used for the recovery of carotenoids (e.g., \(\beta\)-carotene, astraxanthin) [7; 177].
# Evaluation of Adjustment Effects of Highway Guide Signs Based on the TOPSIS Method
## 3 Survey Plan
### Issues Identified in Highway Guide Signs
#### 3.4.2 Layout Design Problems  
An analysis of collected guide signs reveals that the layout design of some signs fails to comply with standard regulations. The following two key issues were identified.  
(1) Information overload on signs  
According to the standards, no more than six destinations should be displayed on a single guide sign, and the total number of destination names on signs within the same gantry structure should not exceed eight [39]. However, the survey found some cases of excessive information, with up to nine destinations shown on a single gantry. This overload can make it difficult for drivers to quickly extract relevant information, potentially compromising road safety.  
(2) Improper sequence of information on distance signs  
The standards recommend that distance signs display up to three rows of information, arranged in descending order of proximity (i.e., from nearest to farthest, top to bottom) [36]. However, the survey found that some signs contained four rows of information, with the sequence sometimes reverse-listed from farthest to nearest. This inconsistency introducesunnecessary complexity, making it harder for drivers to quickly interpret the information, which could lead to delayed decision-making and increased driving risks.