esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Laser Surface Treatment on the Corrosion Resistance of Zircaloy-4 at High Temperature
###### Abstract  
A 700 V pulsed laser was used for the surface treatment of Zircaloy-4. Phases including the treatment layer, morphology and the distributions of alloying elements of the treatment layer were detected via X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). The results showed that the laser surface treatment (LST) layer is also \(\alpha\)-Zr phase layer, the morphology of the treatment layer was \"cauliflower-like\" and the Fe-Cr precipitates in the LST layer were dissolved. The corrosion tests of the LST and the no-laser surface treatment (NLST) specimens were conducted in steam at 1100 \({}^{\circ}\)C using TGA (NETZSCH STA 449 F). The results showed that LST can enhance the corrosion resistance of the Zircaloy-4 in high-temperature steam. More microcracks distributed in the oxide film formed on the NLST specimen than on the LST specimen. And the volume fraction of the tetragonal zirconia (t-ZrO\({}_{2}\)) phase in the oxide film on the surface of the LST specimen was higher than that of NLST specimen. The main reason for this phenomena could be attributed to the dissolving Fe-Cr precipitates and higher solid solution of Fe and Cr in the laser treatment layer.  
Zircaloy-4; laser surface treatment; corrosion resistance; accident-tolerant fuels; oxide +
Footnote †: journal: Applied  
**Citation:** [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Effect of Laser Surface Treatment on the Corrosion Resistance of Zircaloy-4 at High Temperature. _Appl. Sci._**2024, 14, #77. [[https://doi.org/10.3390/app14124977](https://doi.org/10.3390/app14124977)]([https://doi.org/10.3390/app14124977](https://doi.org/10.3390/app14124977))**
## 3 Machine Learning Modeling
### Assessment  
The assessment included two parts: one was to assess the energy variation of the airflow caused by the upwelling water temperature and flow rate, and the other was to assess the predictive capability of the models.  
Humidity and heat exchange occurs between airflow and thermal water during water passing through, and the power driving the heat and humidity exchange is an enthalpy difference [58]. The latent heat variation can be characterized with the enthalpy difference of the water vapor, and the sensible heat variation is characterized with the enthalpy difference of the dry air. The total enthalpy difference of the airflow reflects the airflowenergy change and also serves as the basis for calculation of the coldness needed for roadway cooling, and it is calculated with Equations (9)-(12):  
\[\Delta i=\Delta i_{39L}-\Delta i_{1L}=(i_{39L-F}-i_{39L-S})-(i_{1L-F}-i_{1L-S}) \tag{9}\]  
\[i=1.0045t_{d}+d\cdot(2501+1.85t_{d}) \tag{10}\]  
\[d=0.622\cdot\varphi f_{1}/(P_{1}-\varphi f_{1}) \tag{11}\]  
\[f_{1}=0.6099\exp[17.27t_{d}/(237.3+t_{d})] \tag{12}\]  
where \(\Delta i\) is the enthalpy difference, kJ/kg; \(i_{39L-F}\) and \(i_{39L-S}\) are the enthalpies at a position 39 \(L\) at the beginning and end of water passing through, respectively, kJ/kg; \(i_{1L-F}\) and \(i_{1L-S}\) have a similar meaning to the above; 1.0045t\({}_{d}\) represents the enthalpy of 1 kg of dry air, kJ/kg; \(d\) denotes the humidity ratio in air, kg/kg; 2501 is the latent heat of vaporization of water vapor, kJ/kg; 1.85 is the mean specific heat at constant pressure of water vapor at normal temperature, kJ/(kg-K); \(t_{d}\) is the dry bulb temperature, \({}^{\circ}\)C; \(\varphi\) is the relative humidity of air, %; \(P_{1}\) is the atmospheric pressure, KPa; and \(f_{1}\) is the saturated vapor pressure of air at \(t_{d}\), kPa.  
Regarding the generalization ability of the constructed model, MSE and \(R^{2}\), two parameters extensively used for reflecting the generalization ability of models from different aspects [35; 59; 60], were selected as evaluation indices. Their expressions are given as:  
\[\text{MSE}=\frac{1}{m}{\sum\limits_{i=1}^{m}{(y^{(i)}-\hat{y}^{(i)})}^{2}} \tag{13}\]  
\[R^{2}=1-\frac{\sum\limits_{i=1}^{m}{(\hat{y}^{(i)}-y^{(i)})}^{2}}{\sum\limits _{i=1}^{m}{(\overline{y}-y^{(i)})}^{2}} \tag{14}\]  
where \(m\) is the number of samples; \(y^{(i)}\) is the actual value of sample \(i\); \(\hat{y}^{(i)}\) is the predicted value of sample \(i\); and \(\overline{y}\) is the average value of the samples.
## 4 Experimental Measurements
### Abrasion with the Use of Lubricating Lithium Grease CX80  
This is a multi-purpose product; thus, it is used for the lubrication of industrial and agricultural systems and for the systems of motor vehicles. It ensures excellent lubrication, even under the toughest conditions.  
It is resistant to water and oxidation, protects against attrition and corrosion, extends the life of bearings [4, 5], contains EP additives, is mechanically stable, and, due to its soft consistency, is easy to apply. It passes the SKF EMCOR test, with operating temperatures ranging from \(-20\) to \(+130\)\({}^{\circ}\)C. Its density is 0.807 g/cm at 20 \({}^{\circ}\)C. The measured values with lithium grease are presented in Table 3 and in Figure 10.  
Figure 10: Dependence of the emerging force \(F_{OL}\) on time.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No. of Measurements** & **1** & **2** & **3** & **4** & **5** \\ \hline Loading—tightening torque \(M_{TL}\) (_Nm_) & 4.0 & 8.0 & 12.0 & 16.0 & 20.0 \\ \hline Emerging axial force \(F_{OL}\) (_N_) & 836.2 & 1678.5 & 2518.4 & 3322.8 & 4092.3 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Values determined via measurement with lubricant CX80—lithium grease.  
The calculated coefficients of friction \(f^{\prime}\) for the individual tightening torques in abrasion with lubricating lithium grease CX80 are as follows:  
\[\begin{split} f_{L1}=\frac{2\pi\cdot M_{T1}-F_{L01}\cdot s}{\pi \cdot F_{OL1}\cdot d_{s}}=\frac{2\pi\cdot 4\ Nm-8362\ N\cdot 0.0025\ m}{\pi\cdot 836 2\ N\cdot 0.018376\ m}=0.4773\\ f_{L2}=\frac{2\pi\cdot M_{T12}-F_{L02}\cdot s}{\pi\cdot F_{OL2}\cdot s }=\frac{2\pi\cdot 8\ Nm-12678\ N\cdot 0.0025\ m}{\pi\cdot 16785\ N\cdot 0.018376\ m}=0.4754\\ f_{L3}=\frac{2\pi\cdot M_{T12}-F_{OL3}\cdot s}{\pi\cdot F_{OL3}\cdot d _{s}}=\frac{2\pi\cdot 12\ Nm-25184\ N\cdot 0.0025\ m}{\pi\cdot 25184\ N\cdot 0.018376\ m}=0.4752\\ f_{L4}=\frac{2\pi\cdot M_{T14}-F_{OL4}\cdot s}{\pi\cdot F_{OL4}\cdot d _{s}}=\frac{2\pi\cdot 16\ Nm-33228\ N\cdot 0.0025\ m}{\pi\cdot 33228\ N\cdot 0.018376\ m}=0.4807\\ f_{L5}=\frac{2\pi\cdot M_{T15}-F_{OL5}\cdot s}{\pi\cdot F_{OL5}\cdot d _{s}}=\frac{2\pi\cdot 20\ Nm-4092\ N\cdot 0.0025\ m}{\pi\cdot 4092\ N\cdot 0.018376\ m}=0.4886\\ \end{split} \tag{13}\]  
The actual coefficients of friction \(f\) for the individual tightening torques in abrasion with lubricating lithium grease CX80 are as follows:  
\[\begin{split} f_{L1}=f_{L1}\cdot\cos\frac{\alpha}{2}=0.4773\cdot \cos\frac{60^{\circ}}{2}=0.3092\\ f_{L2}=f_{L2}\cdot\cos\frac{\alpha}{2}=0.4754\cdot\cos\frac{60^{ \circ}}{2}=0.3080\\ f_{L3}=f_{L3}\cdot\cos\frac{\alpha}{2}=0.4752\cdot\cos\frac{60^{ \circ}}{2}=0.3079\\ f_{L4}=f_{L4}\cdot\cos\frac{\alpha}{2}=0.4807\cdot\cos\frac{60^{ \circ}}{2}=0.3114\\ f_{L5}=f_{L5}\cdot\cos\frac{\alpha}{2}=0.4886\cdot\cos\frac{60^{ \circ}}{2}=0.3165\\ \end{split} \tag{14}\]
## 2 Drifting from Molecular to Clinical Evidence
### Anti-Carcinogenic Activity  
Looking at allicin or allicin-containing products as anti-cancer agents (Table 2), allicin has been recently studied for its effectiveness on stage II oral submuc fibrosis in a Chinese patient cohort. During this randomized clinical trial, triamcinolone acetonide (TA) (2 mg/week) or allicin (1 mg/week) were injected intralesionally for 16 weeks. Group A corresponded to the triamcinolone acetonide group and Group B to the allicin-treated group. Mouth opening, burning sensation, and oral health-related quality of life (QoL) were assessed over time. Once the study was over, net gain in mouth opening was \(2.27\pm 0.84\) mm in group A and \(5.16\pm 1.04\) mm in group B; the burning sensation improved by \(2.79\pm 0.87\) in group A and by \(4.33\pm 1.04\) in group B, while the oral health impact profile (OHIP) score improved by \(4.67\pm 2.94\) in group A and by \(12.58\pm 9.82\) in group B. Concerning the 48 subjects included in this study, no adverse effects were stated, therefore highlighting the potential use of allicin as an adjunctive therapeutic drug [19]. [PERSON] et al. (2015) found that allicin intralesional injection improved the associated signs and symptoms with stage II oral submuc fibrosis (OSF) without notable side effects [19].  
Previously, [PERSON] et al. (2001) analyzed the allicin release from garlic powder tablets under simulated gastrointestinal conditions and found that tablets provided less protection over allicin due to its fast disintegration, release of low allicin amounts and vice versa [46]. Besides, aged garlic extract also has shown a suppressive effect on colorectal adenomas in humans through multiple pathways, i.e., reducing cancer incidence and suppressing its growth and proliferation [47]. Actually, aged garlic administration in patients with advanced cancer of the digestive system led to an improvement of natural killer (NK) cell activity but did not cause improvement in QoL [50]. Also, the use of large doses of allitridum and microdoses of selenium have evidenced to effectively prevent gastric cancer, especially in men [49]. Garlic supplementation, however, had no beneficial effects on precancerous gastric lesion prevalence or gastric cancer incidence [48]. Thus, the main findings from clinical trials assessing the allicin or allicin-containing products' anticancer effects have been associated with improvements at stage II oral submuc fibrosis and on natural killer cell activity, with a suppressive effect on colorectal adenomas and effective prevention of gastric cancer in humans without notable side effects. No beneficial effects, however, have been reported on precancerous gastric lesion prevalence in gastric cancer and QoL.
## 2 Materials and Methods
### Thermal Analysis (TGA)  
Thermal analysis was performed using a Q600 SDT (TA Instruments, New Castle, DE, USA) on fully cured adhesive samples containing 0, 2, 4, and 6 wt.% IPA. The tests were run from room temperature (\(\sim\)23 \({}^{\circ}\)C) to 450 \({}^{\circ}\)C at a heating rate of 5 \({}^{\circ}\)C/min. Argon gas was used as a purge gas. The weight of the samples ranged between 9 and 9.5 \(\upmu\)g.
## 1 Introduction
Many engineers are not aware of the low-frequency cutoff effect and the propagation path of low-frequency noise. Most pipeline mufflers are limited to liquid noise reduction alone, and do not deal with wall vibration ([PERSON], 2019; [PERSON] et al., 2020), which is a serious omission. There have been a number of systematic investigations of acoustic propagation in gas-filled pipelines ([PERSON], 2019; [PERSON] et al., 2020), and the results obtained on noise in such systems can provide some guidance for studies of noise in liquid-filled pipelines. However, these results cannot be carried over completely to the liquid case because of the differences in the characteristic impedance and speed of motion of the respective media ([PERSON], 2019; [PERSON] et al., 2020). There have also been a few theoretical studies of noise generated in fluid-filled elastic pipelines by supersonic flow ([PERSON], 2019), wall vibration ([PERSON], 2019), and bubble oscillations ([PERSON], 2019), but there is a lack of corresponding experimental investigations. The present study aims to improve on the results of previous work by taking full account of the existence of a low-frequency cut-off phenomenon in a fluid-filled pipeline such that sound below a cut-off frequency is mainly propagated through the pipeline wall. It thereby also aims to remedy some shortcomings of previous attempts at pipeline noise reduction. Both theoretical and experimental investigations of acoustic propagation in a fluid-filled PE pipeline are conducted. The remainder of the paper is organized as follows. In Section 2, the eigenequation for the sound field in an elastic PE pipeline is obtained from a theoretical analysis, and the cutoff frequencies of a normal wave in the PE tube are calculated. Section 3 describes the experimental system and the scheme for determining the acoustic propagation characteristics of the fluid-filled PE pipeline. Section 4 discusses the experimental results. The general distribution law of the sound field and the propagation path of noise in the fluid-filled PE pipeline are analyzed. Finally, Section 5 presents the conclusions of this study.
# A Brief Review on Challenges in Design and Development of Nanorobots for Medical Applications
## 2 Challenges in the Design and Development of Nanorobots
### Data Transmission  
One of the most commonly accepted devices for communication is cellphones, and they can be used as highly functional and effective sensors to obtain wireless transmission of data from medical nanorobots embedded within the patient's body. Cellphones can be a good option for tracking predefined levels (the normal range of values of something (e.g. glucose level) inside a human body to function properly) in various biomedical fields, such as diabetes care and other health concerns. To do this, chemical nanosensors can be inserted into the nanorobot to track glucose levels, for example. The nanorobot can then emit signals to prompt an alert if the patient is in immediate need of his or her doctor's prescription drug. Electromagnetic radio waves are used to monitor and track the current state of the nanorobot inside the patient; this is achieved by a transponder system that emits a magnetic signature to the passive CMOS sensors embedded in the nanorobot, allowing data to be sent and received through electromagnetic fields [114]. The monitoring data of the nanorobot transforms the wave propagation produced by the emitting signal through a well-defined protocol. This information can also transmit back using the resonance of waves [115].  
Some main data considerations include privacy, security, and longevity. All data, communicated during the operation of a robot, should be processed by a data transmission system that could be stored on a local server or on the cloud, depending on the application. To protect the users' privacy, there should be a procedure to limit access to the database through which each user can have access to certain information. The system of information storage and protection is well-known among the users in the field; however, there is a small chance of getting hacked. With a system that is designed to rely on servers fully and cloud data backups, the importance of cybersecurity must be highlighted.
###### Abstract  
The essential oil isolated from clove (_Syzygium aromaticum_) is used in food, medicine, cosmetics, agriculture, and aromatherapy for its antimicrobial, antioxidant, and analgesic properties. This systematic review, following the PRISMA 2020 methodology, evaluates the application of clove essential oil in meat and meat products to determine its effectiveness in preventing oxidative damage and improving product quality. A search was performed in various databases, obtaining 639 studies. After removing duplicates and applying inclusion and exclusion criteria, 43 relevant articles were selected. Studies published between 1999 and 2024 that evaluated clove essential oil in meat for human consumption were included, excluding research on extracts other than essential oil or supplements for animal feed. The studies suggest that clove essential oil improves parameters such as oxidative stability, colour preservation, and the reduction in reactive compounds such as thiobarbituric acid-reactive substances, thereby increasing the shelf life and safety of meat and meat products. Oxidation is reduced through free radical inhibition and lipid protection. The main variability detected includes the type of meat, application method and storage conditions. The concentrations used ranged from 2.65 mL/kg to 5%. Although variability in methodologies and concentrations used is a limitation for meta-analysis, the findings support the potential of clove essential oil as a natural alternative for preserving meat products, responding to consumer demand for safer foods free of synthetic preservatives.  
antioxidant activity; beef; edible films; fish; lipid peroxidation; protein oxidation
# An Overview of Fog Data Analytics for IoT Applications
## 5 Research Challenges  
### Low-Latency Transmission  
IoT devices generate a large amount of data, so we need efficient data processing capabilities to handle that large amount of data within certain time constraints. On the other hand, real-time latency-sensitive applications pose challenges that are not solved only by efficient data processing but also stipulate that the processed data are within a few milliseconds. Some solutions have been proposed to satisfy these requirements, but active research remains because of the inherent complexity and design challenges.  
The challenge of low latency is amplified dramatically when many devices depend on each other for data and responses. Data must often be processed to some extent so that they can be served to another device because of that particular device's interfacing and structural data needs. At this point, if the latency constraint is not taken into account correctly, it will hugely impact the performance and effectiveness of the system of inter-dependent IoT devices because there is already a delay due to some level of pre-processing. A higher latency will worsen the situation, resulting in a waiting time for data and a poor performance, eliminating the comparative advantage of fog computing. Table 1 compares various works that show latency sensitiveness in different areas.  
As a partial solution, Dew Computing can be considered by packing pre-processing capabilities within the devices and establishing a direct communication path between them. However, if devices could use data from multiple devices, this approach could be more economical, and another alternative should be explored. For example, [PERSON] et al. [54] suggest the concept of aqua computing for improving the user experience and offer clone architecture to accommodate lower latency requirements by cloning user-specific data in the edge devices so that they are directly accessible to the user without any delay. The Internet provider is considered to manage these clones to serve the user on demand and is responsible for updating them for the time being. However, managing user-specific clones would be costly in terms of resources.  
Additionally, no perfect universal solution can exist for low-latency applications, and some trade-off is needed for the high availability, latency, and redundancy. If we consider an application-specific solution, then a large amount of heterogeneity would be added to the network, resulting in difficult tasks to manage.
# Network Diffusion Algorithms and Simulators in IoT and Space IoT: A Systematic Review
## 4 Analysis
### Analysis of Research Question 3 and 5: Network Diffusion Algorithms and Performance Evaluation
#### 4.2.2 Epidemic Models  
Epidemic models, such as the SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible) [223] models, are commonly used to study how information or malware spreads through IoT networks. These models treat devices as nodes, with the diffusion process mimicking how a disease spreads in a population.  
Strengths:  
* Flexibility: These models can adapt to various network topologies like scale-free and small-world networks, which are common in IoT configurations.
* Scalability: Epidemic models are effective in large-scale IoT environments, making them ideal for scenarios with many interconnected devices. Weaknesses:
* Simplification: These models often assume uniform infection and recovery rates, which may not accurately reflect the diversity of device states in the IoT.
* Homogeneity: The assumption of homogeneous networks may not adequately capture the complexity and dynamic behavior of real-world IoT environments. Performance Metrics:
* Propagation Delay: Epidemic models generally introduce delays as they spread information across larger networks, especially if the network topology is complex.
* Resource Utilization: Epidemic models tend to use more resources (e.g., CPU, memory, etc.) as nodes continuously reinfect each other, which can lead to higher energy consumption in resource-constrained IoT devices.  
Example: The SIHR model demonstrated that in scale-free IoT networks, information spreads rapidly but can be difficult to control due to the absence of a clear spreading threshold.
# Pipe Routing with Topology Control for Decentralized and Autonomous UAV Networks +
## 4 Pipe Routing Scheme
### Proactive Route Switching  
Proactive route switching is triggered when the quality of the current route (\(R^{*}\)) degrades below a threshold, given by the conditions (5) and (6), or when a shorter alternate route becomes available in the pipe. In such a situation, the source node initiates a breadth-first search (BFS) algorithm to explore all the routes available within the pipe to the destination node and select the least-cost route (calculated using (7)). When the source node switches to a new route, the existing pipe is abandoned, and a new pipe is formed around the new route. If no suitable alternate route is available, a new route discovery is triggered. Using the local pipe topology when possible, proactive route switching reduces the number of new route discoveries, and thus their overhead and delays, while minimizing the interruptions in data throughput.
# GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
## 4 Method Verification  
### Overview of Case Study Site and Site Data Modeling  
To validate the effectiveness of RPOS, we constructed a test site, as shown below, and developed a BIM model (Figure 4). At the test site, a precast concrete construction method was used for the structural work, and 15 columns were erected according to the construction sequences. The column was 3.5 m long and weighed 0.7 tons. The column installation sequence was same as the number indicated at the column installation points shown in Figure 4. There were 10 places on the site where the columns could be loaded. The site dimensions were 80 \(\times\) 60 m. Additionally, there were places on the site where the mobile crane could not move to. The mobile crane used in the test was assumed to have a maximum boom length (\(R_{W}\)) of 16 m, minimum radius for safe lifting (\(R_{C}\)) of 5 m, a traveling speed of 1 m/s, and an installation/dismantling time of 10 min.  
In the test, the grid size (\(gs\)) was set to be 4 m. The test site was converted into a grid according to the set grid size to create a 20 \(\times\) 15 orthogonal coordinate system. The test site was represented using 300 points, and the point index n followed the linear index arrangement of the matrix. Therefore, according to the installation sequence, the set of column installation points (demand points) were [148, 108, 106, 146, 186, 188, 150, 190, 152, 192, 154, 194, 114, 112, 110], and the set of loading points (supply points) were [49, 53, 57, 78, 82, 161, 218, 247, 254, 288]. The set of points where it was impossible to move and place the mobile crane were [42, 43, 44, 45, 62, 63, 64, 65, 117, 118, 119, 137, 138, 157, 250, 251, 252, 290, 291, 292, 106:114, 126:134, 146:154, 166:174, 186:194, 85:20:205, 95:20:215, 86:94, 206:214).  
Figure 4: Case study site.  
a total of 90 points, including the building-occupied points, soft ground points, loading points, and points where the safe work distance was not secured.