esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Innovative Approaches for Enzyme Immobilization
### Microfluidic Device for Enzyme Immobilization  
Microfluidics (microreactors) are chip-based systems with micro- to nano-sized channels that process small chemical volumes [173]. They reduce reagent use, save space, and integrate multiple flow functions. Recent applications include enzyme-immobilized systems like wearable devices, microfluidic paper-based analytical devices (uPADs), and point-of-care testing for biomolecule detection, biocatalysis, and environmental monitoring [174]. However, industrial use is limited by complex cleanroom processes (e.g., photolithography, spin-coating) [175; 176]. Emerging solutions include droplet parallelization [177] and soft lithography techniques.  
Microfluidic enzyme reactors (u-IMERs) provide key advantages over traditional systems, including faster mass/heat transfer, high efficiency, compact size, and enhanced safety [178]. Figure 6 shows the common types of enzyme-immobilized microfluidics, including wall-coated reactors, packed-bed reactors, and monolithic reactors, with enzymes immobilized in pores or channels [179]. These systems enable precise fluid control, improving biomolecule detection (e.g., nutrients, metabolites, contaminants) [180]. For example, a continuous-flow microreactor with poly-lysine-supported enzymes can detect hormones and drugs efficiently [181].  
Recent advances in enzyme immobilization and microfluidics have improved biosensors and yielded efficient bioremediation systems. For instance, cholesterol oxidase immobilized on gold electrodes using self-assembled monolayers (SAMs) achieved high sensitivity (93.75 mA/mM/cm\({}^{2}\)), a low detection limit (0.49 nM), and low sample use (<50 uL) [182]. Similarly, microfluidic epidermal patches with lactate oxidase biosensors accurately measured sweat lactate, while reducing pH and temperature interference [183]. Additionally, PEG hydrogel microstructures in microchannels yield fast enzyme assays, with response times under 10 min [184].  
Wireless urea biosensors using nanocomposites (MBs-urease/GO/NiO) achieved high sensitivity (5.582 mV/(mg/dL), while paper-based microreactors (uPADs) detected trace pesticide residues (0.007 ug/mL) [185; 186]. Immobilized enzymes also excel in environmental applications, e.g., a magnetic-nanoparticle microreactor removed 93% of dyes from waste water, and lactose-loaded microcapsules degraded 72% of acetaminophen in 30 min [187; 188].
## 3 Results and Discussion  
### Motor Activity versus Weather Conditions  
The created system, whose key element is data warehouse, also acquires data about weather conditions from weather stations. Therefore, the system records two types of temperature. The first measurement comes from weather stations, which describes atmospheric conditions outdoor, and the second is deciphered directly from the beacons. When determining the influence of surrounding temperature on cattle behavior, it is necessary to determine the _THI_ coefficient. Its value, which is below 72, determined on the basis of temperature and relative humidity, informs us about lack of heat stress. Coefficient was calculated on the basis of the following empirical formula on the basis of \(T_{db}\)\({}^{\circ}\)C (dry thermometer) and relative humidity \(RH\)[18]:  
\[THI=\ 0.8\cdot T_{db}+\frac{RH}{100}\cdot(T_{db}-14.4)\ +\ 46.4 \tag{1}\]  
We can observe proportional relationship between temperature and motor activity of cows, which is well illustrated (see Figure 7). Increase in motor activity together with increase in temperate was also noted in longer period of time on the basis of the research in the years 2015 and 2016. Motor activity connected with the research conducted in 2015 in September was at 27%, and in January and February oil 2016 it was at 21%. When processing data, a relative daily humidity in September 2015 was also included. Thanks to it, it was possible to calculate THI value. It was possible to determine periods, during which animals were in heat stress, which is shown (see Figures 5 and 6).
# A Comprehensive Review of the Application Characteristics of Biodiesel Blends in Diesel Engines
## 4 Combustion Characteristics
### Cylinder Pressure  
Cylinder pressure (CP) is an important parameter usually measured by pressure sensors that reflects the combustion process and the degree of mixing of fuel and air. The ID, heat release rate, combustion mass fraction, cylinder pressure-volume and other information can be gleaned from the cylinder pressure [31]. Some researchers also use the CP to estimate the intake and residual mass of the engine [75] or to develop functions for calculating combustion noise simulation data [76].  
Changes in CP will be affected by parameters such as fuel type, engine speed, engine load, fuel injection pressure and injection timing. According to research by [PERSON] et al., the CP of B10 (10% castor oil methyl ester + 90% diesel) tends to rise earlier, and the rise rate is slightly higher, and the peak pressure is also larger compared with diesel [8]. Other studies [34; 77] reached similar conclusions. However, [PERSON] et al. found that at 1500 rpm, under full load, the released peak CPs of diesel are 70.7, 73.6 and 77.6 bar, respectively, at injection timings of 21, 24, and 27\({}^{\circ}\) bTDC. Pure fish oil biodiesel generated lower peak CPs that were 63.8, 67.1 and 73.8 bar, respectively, under the same conditions [33]. [PERSON] et al. also found that the maximum rate of pressure rise increases with retardation in injection timing, decreases with injection timing advance and increases with load. as shown in Figure 7[67]. The trend variation of CP of the same biodiesel blends is not unique. [PERSON] et al. found that under the same operating conditions, the blends with 20 vol% corn biodiesel has the larger CP at an injection pressure of 190 bar, but at 200 bar, the CP of pure diesel was larger [78]. Other studies [4; 37] also showed that the maximum combustion pressure did not change much when using biodiesel, and the peak positions were also very similar. Biodiesel and the blends mixed with diesel usually have a higher cetane number and a shorter ID, so CP tends to rise earlier than diesel. Higher oxygen content and earlier combustion will cause the peak pressure to increase. For stoichiometric flames, biodiesel-containing fuels are more reactive, which is also an important factor [8]. However, the lower calorific value of biodiesel also affects the peak CP. Similarly, the higher viscosity and density of biodiesel will affect the volatilization and atomization effect of the fuel, which may cause the peak CP to be even lower than diesel [26; 78].  
Figure 6: Effect of load on ignition delay of fuel blends [73].
## 5 Conclusions  
In this paper, an internal meshing cylindrical gears with a curved meshing line was designed, and its tooth contact and wear characteristics were deeply studied. The advantages of the introduced novel gears in wear resistance are demonstrated based on simulation results. From the present study, the following conclusions are drawn.  
(1) The sliding coefficients of the introduced novel gears with curved meshing lines were similar to that of the involute gears; the relative curvature was greater than that of the involute gears; and the normal contact force was lower than that of the involute gears because the contact ratio of the introduced gears was larger than that of involute gears.  
(2) Under the same running times, the sliding distance and wear depth of the inner gear and the outer gear of the curved meshing line were smaller than those of the involute gears. The reduction in wear was beneficial, increasing the effective running life of the gear pair.  
(3) The peak wear depth of the introduced novel gears occurred at the moment when the gear entered and exited the meshing, at which time the contact stress was higher, so the wear depth was greater. When meshing at the pitch circle, there was almost no relative sliding between the two tooth surfaces, so there was almost no wear.  
(4) The peak value of wear depth could be reduced by tooth modification because the load distribution of tooth surface was improved via tooth modification. The installation errors increased the peak wear depth because the installation errors worsened the load distribution and exacerbated the stress concentration of the tooth surface.  
Figure 22: Variation in maximum wear depth of introduced novel gears with installation errors and stress cycles.  
**Author Contributions:** Conceptualization, C.J.; Methodology, C.J.; Software, G.Z.; Validation, G.Z.; Data curation, G.L.; Writing--original draft, G.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** The work described in this paper was supported by the National Natural Science Foundation of China (Grant Nos. 52375044 and 52005107) and the Fujian Provincial Science and Technology Major Special Projects (Grant No. 2021 HZ024006).  
**Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 2 Materials and Methods
### The Main Method
#### 2.1.1 The Hardware System Configuration  
The whole assistive system is wearable and contains an embedded device--Jetson AGX Xavier launched by Nvidia [22], a binocular camera named ZED 2. Additionally, a voice prompt manager is installed in the AGX. This work connects a sound card between the AGX and the headphone to produce voice prompts. The AGX featuring a Tegra System on Chip (Xavier SoC) comprises 8 NVIDIA Carmel CPU Cores (architecture compatible with ARMv8.2) and an integrated GPU based on the NVIDIA Volta architecture with 512 CUDA cores. In addition, it also adds a Tensor Core, an NVIDIA deep learning accelerator, a VILW (Very long instruction word) video processor, and an image signal processor (ISP) to enhance AI computing performance. The ZED 2 is a stereoscopic camera designed for tracking vehicles and people with a vast field of view. It offers a more excellent depth detection with a 120-degree wide-angle field of view. These functions provide a great sense of safety to visually impaired people. The aim here is to combine depth-of-field detection (up to 20 m) with object detection. The whole assistive system is shown in Figure 1, powered by a lithium battery with a capacity of 5200 mAh (Figure 1a). The battery with fully charged (16.8V) can supply the system operation time of about 2.5 h. The battery and AGX are installed on the backboard of the user. The ZED 2 is fixed on the brim of the user's cap (see Figure 1b). Moreover, the headset is connected to the sound card, and the voice instruction will be output to the user.
# Composite Kernel Method for PolSAR Image Classification Based on Polarimetric-Spatial Information
## 4 Experiment  
To demonstrate the superiority of the composite kernel method, in this section, the composite kernel method is compared to the polarimetric feature method (only considering polarimetric features), the morphological profile method (only considering spatial feature), and the vector stacking method. Firstly, we give the information of the used PolSAR data set. Then, we present the experimental setting. Finally, for each PolSAR image, four approaches are applied and evaluated both qualitatively and quantitatively.
# Thermal Modelling and Experimental Validation in the Perspective of Tool Steel Laser Polishing
## 3 Results and Discussion
### Moving Experiment: High-Speed Imaging
#### 3.2.1 Experimental Results
(**b**) Second line with an overlap of 30% also at 35 mm/s and 415 W also in the steady state. (**c**) Second line at 100 mm/s and 561 W in the steady state. (**d**) Average of the light intensity of all images in the steady state for the first line at 35 mm/s and 415 W. (**e**) Average of the light intensity of all images in the steady state for the second line at 35 mm/s and 415 W. (**f**) Combination of 50% (**d**) and 50% (**e**). (**g**) Average of the light intensity of all images in the steady state for the first line at 100 mm/s and 561 W. (**h**) Average of the light intensity of all images in the steady state for the second line at 100 mm/s and 561 W. (**i**) Combination of 50% (**g**) and 50% (**h**). For a scale indication, the ellipses in (**f,i**) represent the spot diameter of 0.9 mm and so main axes give the scale in \(x\) and \(y\) directions. All images have the same scale. As the camera and laser positions are fixed and did not change during the first line or second line, it is interesting to superpose both pictures to evaluate the position of the melt pool relative to the laser position. The combined image is obtained by superposing the image from the first line with the image of the second line and taking 50% of the pixel intensity of each picture. The resulting images are shown in Figure 13f,i for 35 and 100 mm/s, respectively. The two melt pools form a kind of Venn diagram as they appear darker where they intersect as both melt pools are dark and with a medium shade of grey where only one of the melt pools is present. The solid EDM surface is a light grey all around. Based on these observations, the theoretical position of the laser beam can be positioned at the center of the intersection of the two melt pools (see red ellipses). As can be seen for both melt pools, a large part of the melt pool is trailing the laser spot and is not situated in the laser spot. The melt pool starts only after a third of the spot diameter for 35 mm/s and close to half the diameter at 100 mm/s. The melt pool is also trailing further behind the laser spot as the speed increases.
## 4 Results and Discussion
### Discussion  
In this study, the integration of Bi-GRU with the hybrid feature engineering techniques achieved a higher forecasting performance on the Rossmann and Walmart datasets when compared with [PERSON] et al. [38], [PERSON] [39], and [PERSON] [40]. The results are superior to the those of the existing regression models, like linear regression, LSTM, Bi-LSTM, and GRU. The proposed Bi-GRU model has minimal NRMSEs of 0.08 and 0.01, NDs of 0.07 and 0.03, RMSSEs of 0.08 and 0.08, MAEs of 0.05 and 0.07, and MSEs of 0.04 and 0.03, as well as high R2 values of 0.98 and 0.99, on the Rossmann and Walmart datasets, which are shown in Tables 2 and 3, respectively.  
The practical implications of the findings in the context of E-commerce companies are as follows: (i) customer satisfaction by producing timely delivery of the product, and (ii) long-term strategy plan for reliable future growth. Furthermore, the precise retail sales forecasting using the Bi-GRU-APSO model improves their operations by allowing the E-commerce business to effectively allocate resources for managing cash flow and future. Additionally, the retail sales forecasting results in an accurate estimation of revenue and costs based on their long- and short-term performance. The major five benefits of timely retail sales forecasting are (i) eliminates the chances of panic sales, (ii) leverages real time data, (iii) offers simple financial planning, (iv) stabilizes inventory management, and (v) speeds up the process of product delivery.
# Underlay Loosely Coupled Model for Public Safety Networks Based on Device-to-Device Communication
## 3 Underlay D2D Network Based on ProSe Service
### Infrastructure vs. D2D-Based Communication  
Despite all efforts to execute load balancing between cells, the fully centralized approach based on eNBs is not usually suited for public safety situations where a large number of subscribers are grouped in the same area and share a large amount of data. To avoid an eNB overload situation, D2D direct communication can be considered as an alternative solution that creates an underlay network supported and maintained by participant UEs, as illustrated in Figure 5. All the traffic should then be spread among the involved devices through direct communication links. Moreover, partial-coverage D2D communications can be deployed to overcome the lack of coverage issues.
###### Abstract  
The use of nonthermal air plasma is rapidly becoming a novel technology as an alternative source of nitrites in the meat industry. As egg white is a versatile and cost-effective ingredient commonly used to improve the texture of meat products, the effect of its addition after plasma treatment (PTEW) on the yield, pH, residual nitrite, nitrosyl hemochrome, TBARS, color, texture parameters, and aroma profile of pork liver pates was studied. The nitrite ion content of plasma-activated egg whites was adjusted to the positive controls containing 60 ppm (PC1) and 120 ppm (PC2) sodium nitrite by modifying the duration of their plasma treatment (PTEW1 and PTEW2, respectively). A group without the addition of nitrites was also manufactured (NC). Each treatment (NC, PC1, PC2, PTEW1, PTEW2) was analyzed on days 1, 3, 5, and 7 of storage at 4 \({}^{\circ}\)C. The results showed that liver pates containing plasma-treated egg whites had a similar nitrite and nitrosyl hemochrome content compared to samples containing the same amount of nitrite ions derived from sodium nitrite (\(p\geq 0.05\)). In addition, 40 ppm nitrite ions, regardless of the source, was sufficient to achieve the desired reddish-pink color of the product over the entire storage period. Both nitrites from sodium nitrite and plasma-treated egg whites also significantly reduced lipid oxidation compared to the NC group (between 10% and 23% reduction on the last day), but had no significant effect on yield, pH, and texture parameters of the products. Based on the principal component analysis (PCA), the aroma profile of pates differed significantly between the groups with and without nitrites, with the largest differences observed on the first day (approx. 88%). Importantly, PTEW1 and PTEW2 aroma after production was similar to group PC2. The results of our study suggest that plasma-activated egg whites can be used as a potential source of nitrite in liver pate production without adversely affecting the technological properties and shelf life of the final product.  
pork liver pate; curing; sodium nitrite; egg white; atmospheric non-thermal plasma; plasma treatment; residual nitrite; quality 2023134464. [[https://doi.org/10.3390/app13074464](https://doi.org/10.3390/app13074464)]([https://doi.org/10.3390/app13074464](https://doi.org/10.3390/app13074464))
## 3 Methodology and Model
### Two-DimensionalAlgorithm Process  
The steps of the IPSA-DV-Hop localization algorithm in the 2D scenario are stated below:  
1. The initial localization scenario is a square area of \(L\times L\) meters with \(M\) nodes and \(N\) beacon nodes.
2. The beacon node broadcasts its location information; the unknown node receives the broadcast packet to obtain the RSSI value and hop distance information between nodes. The unknown node then forwards the hop distance after incrementing it by one, then compares and saves the minimum hop count information to the beacon node.
3. The first hop distance is refined using the received RSSI value and the hop count between nodes is calculated based on the refined first hop distance.  
4. The unknown node calculates its estimated coordinates using the average hop distance and obtains the average hop distance weighted by the distance error.
5. The node coordinates are determined using a weighted hyperbolic algorithm, which is combined with the DCL of the node group to further refine the position coordinates.
6. The PSA decision variables, constraints, and objective function are initialized. The initial group position coordinates are constructed using the Good Point Set strategy and the fitness function for estimating the unknown node position.
7. The system deviation is calculated and iteratively updated using the PID regulation process. The Cauchy-Gaussian perturbation strategy is incorporated in the later stages of the algorithm to output the optimal node position coordinates.  
The overall flowchart of the 2D algorithm is shown in Figure 2.
# An Enhanced Energy Balanced Data Transmission Protocol for Underwater Acoustic Sensor Networks
## 2 Literature Review
As we can see in the figure, BTM adopts hybrid transmission mechanism and switches between multi-hop and direct transmission mode on the basis of difference in energy levels. While UWDAR assigns in-charge time to each hop-grade periodically according to their traffic characteristics, where, in-charge hop-grade is responsible to collect data from all network nodes and transmit it directly to the sink. This technique works for a limited geographical region due to its backward data transmission constraint.
## 2 Materials and Methods
### Antioxidant Activity
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Extract/Standard**} & **Reducing Power** & **DPPH Scavenging Effect** & **ABTS Scavenging Effect** \\ \cline{2-6}  & **IC\({}_{50}\) (ug mL\({}^{-1}\))** & **IC\({}_{50}\) (ug mL\({}^{-1}\))** & **IC\({}_{50}\) (mg AAE g\({}^{-1}\))** & **IC\({}_{50}\) (ug mL\({}^{-1}\))** & **IC\({}_{50}\) (mg TE g\({}^{-1}\) of Dry Bark)** \\ \hline _Pinus pinaster_ Ait. & & & & & \\ bark polar extract & 22.53 \(\pm\) 0.46 b & 6.79 \(\pm\) 0.48 b & 125.48 \(\pm\) 12.66 & 3.95 \(\pm\) 0.05 a & 255.24 \(\pm\) 10.24 \\ _Pinus pinea_ L. bark & & & & & \\ polar extract & 21.21 \(\pm\) 1.04 b & 6.46 \(\pm\) 0.36 b & 112.68 \(\pm\) 9.04 & 3.89 \(\pm\) 0.40 a & 223.69 \(\pm\) 10.35 \\ Ascorbic acid & - & 3.96 \(\pm\) 0.18 a & - & 3.55 \(\pm\) 0.03 a & - \\ Trolox & 28.82 \(\pm\) 0.60 a & - & - & 4.73 \(\pm\) 0.07 b & - \\ \hline \hline \end{tabular}  
* The values represent the mean \(\pm\) standard deviation. Means with different minor case letters (a, b) within the same column are significantly different (one-way ANOVA, followed by [PERSON]’s HSD test, \(p\) < 0.05). Abbreviations: AAE, Ascorbic acid equivalents; IC\({}_{50}\), inhibitory concentration at 50%. TE, Trolox equivalents.  
\end{table} 
Table 5: Antioxidant activity of _Pinus pinaster_ Ait. and _Pinus pinea_ L. bark polar extracts, through reducing power, DPPH, and ABTS scavenging effects. Pearson correlations were determined between the total phenolic content, the total proanthocyanidins, and the abundances of identified compounds present in the studied pine bark polar extracts and the IC\({}_{50}\) values of the three antioxidant activity tests, as indicated in Table 6.  
The highest Pearson correlation coefficient was observed between the quintic acid content and the IC\({}_{50}\) of the pine bark polar extracts in the reducing power assay (\(r=-0.856\)). There is an increasing attention on the antioxidant activity of cyclic polyols, as quintic acid, in addition to other health-promoting effects, such as the treatment of diabetic diseases [62], paving the way for plentiful applications for this compound. Strong correlations have been also found between the flavononols and taxifolin contents and the IC\({}_{50}\) values of the reducing power (\(r\) values of \(-0.828\) and \(-0.823\), respectively). Although the remaining linear correlations presented in Table 6 did not have statistical significance (\(p>0.05\)), the linear correlations between the taxifolin and flavononols contents and the IC\({}_{50}\) of extracts in the ABTS scavenging effect assay (\(r\) values of \(-0.605\) and \(-0.562\), respectively), as well as the one between the C-type procyanidin trimer isomer **3** abundance and the IC\({}_{50}\) in the DPPH scavenging assay (\(r=-0.416\)), were moderate. Nevertheless, it is important to underline that other non-identified components in the analysed pine bark polar extracts may have interacted with the phenolic compounds.