esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Stability Analysis and Discussion  
Based on the method presented in the Section 2, the cutting process stability about the process with VHCVSS will be analyzed. For the convenience of analysis, similar to the idea in [49], four kinds of cutting processes are defined at first: Process I (i.e., conventional cutting, see the combination of Figure 1a,c), Process II (i.e., the cutting with VSS, see the combination of Figure 1b,c), Process III (i.e., the cutting with VHC, see the combination of Figure 1a,e), and Process IV (the cutting with VSS and VHC, see combination of Figure 1b,e).  
The main purpose, here, is as follows: (1) Apply the method proposed in this paper to above four processes, carry out the stability prediction about the corresponding 1-DOF (see Figure 2a) and 2-DOF (see Figure 2b) systems, and effectively expand the application scope of the original methods; (2) The effectiveness and feasibility of chatter suppression by the combination process with VHCVSS are explored, and its influence on cutting stability is investigated.
## 4 Discussion
### Contributions of Tested Strains in Baijiu Fermentation
#### 4.1.3 P. acidilactici  
_P. acidilactici_ has been reported to play important roles in many fermented foods, such as wheat sourdough bread [40] and fruit juices [41], mostly contributing to the acidification of raw materials. _P. acidilactici_ is also commonly found during Baijiu fermentation, such as Luzhoulaojiao-jiu aged pit mud [42] and fermented grains of sesame-flavor Baijiu [43]. A study of [PERSON] et al. [44] investigated the characteristic of carbon utilization of LAB isolated from fermented grains of sesame-flavored Baijiu. The results revealed that most tested LAB had a better ability to use sugars such as dextrin, d- maltose, cellobiose, \(\alpha\)-p-glucose, etc., but there were significant differences between different kinds of species. _P. acidilactici_ was proved to have a lower capacity to utilize glucose when compared to other substance utilization, such as d-cellobiose, and this might explain the low glucose consumption of most tested _P. acidilactici_ (Figure 2). In the study, _P. acidilactici_ strain (P-4) were able to tolerate 10% alcohol (Table 1). It is known that many factors can be involved regarding the alcohol tolerance of microbes, such as the changes induced by ethanol about plasma membrane composition, or deactivation of cytosolic enzymes like glycolytic enzymes and ATPase [45]. Other LAB species such as _P. pentosacus_ and _L. plantarum_ strains also show obvious alcohol tolerance, for solvent-induced changes about membrane lipid composition [46]. _P. acidilactici_ has a good ability to produce the DL-lactic acid in accordance with mechanism of homolactic fermentation, which was observed in our results (Figure 3). This species can also generate bacterioxins, hydrogen peroxide, diacetyl, organic acid, and other antibacterial compounds [47], which contribute to safeguard the microbiological quality of food. However, _P. acidilactici_ might contribute little to the production of aroma compounds in the Baijiu fermentation process, which was suggested by the PCA analysis of metabolite profiles (Figure 4).
## 7 Security and Privacy Challenges and Limitations in AMRSys
### Data Confidentiality of a Channel between the User and Robot
#### 7.1.1 First, Via a Mobile App or Tablet App  
In this method, technology such as Bluetooth or an unlicensed free frequency connection via a local home wireless router could be adopted. To facilitate a remote connection, access could also be made available via an internet connection.
# Healthy Effects of Pomegranate (_Punica granatum_ L.) in Internal Medicine and Dentistry
## 5 Pomegranate in Internal Medicine
### Neurodegenerative Diseases  
PJ seems to be able to attenuate neuro-inflammation, suggesting that this fruit can be useful in counteracting the onset and symptoms of age-associated neurodegenerative pathologies, such as Alzheimer's and Parkinson's diseases [141].  
Pomegranate polyphenic compounds reduce neuro-inflammation by several mechanisms, which include: (i) the inhibition of NF-kB, a transcription factor involved in the inflammatory process [97]; (ii) the reduction in the pro-inflammatory cytokines, such as IL-2, IL-6, IL-18, and TNF-\(\alpha\)[98]; (iii) the reduction in the beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) gene expression, responsible for the production and the deposition of the \(\beta\)-amyloid peptide, involved in Alzheimer's disease; (iv) the reduction in COX-2 activity [99]; (v) the reduction in the catalytic activity of caspases [100].  
Pomegranate polyphenols seem to improve synaptic function during Alzheimer's disease. In fact, a study conducted on mouse models subjected to nutritional supplementation with pomegranate extracts (4% \(w/w\)) for 15 months highlighted the protective role of pomegranate against the proteins that improve the synaptic structure, such as synaptophysin, postsynaptic density protein-95 (PSD-95), mammalian uncoordinated-18-1 (Munc18-1) and synaptosomal-associated protein-25 (SNAP25) [101].  
Finally, the supplementation with pomegranate extracts (4% \(w/w\)) would seem to protect the brain from oxidative damage in mouse models affected by Alzheimer's through a reduction in LPO and carbonyl levels and the restoration of antioxidant enzyme activities, such as glutathione peroxidase (GPX), superoxide dismutase (SOD) and glutathione S-transferase (GST) [102].  
Although clinical studies on humans are lacking, in vitro and animal models studies seem encouraging and suggest that pomegranate and its phenolic compounds possess important anti-inflammatory and neuroprotective properties that could be effective against the symptoms of neurodegenerative diseases with neuro-inflammatory etiopathology [142].
## 3 Results and Discussion
### Vickers Microhardness  
For mechanical analysis, Vickers microhardness experiments were performed on the cross-section of enriched samples to characterize the two typical regions produced by the EDM process, as illustrated in Figure 5.  
The hardness trend of the workpiece surface showed a similar distribution in each zone (base metal, heat-affected zone, and recast layer) from the lower to the upper part of Ti-6 Al-4V alloy for each dielectric fluid used, as shown in Figure 5. Two types of behavior for hardness are observed in the thermally affected zone, and a significant hardening in the recast layer compared to the base metal, for both polarities.  
The data showed that the heat-affected zone (HAZ) of samples machined by EDM with DF1-F fluid exhibited the highest average hardness, approximately 645 HV, which is about 200 HV higher than that of the base material (BM). For samples processed with DF2-Ca fluid, the hardness was about 450 HV, which was very similar to the BM.  
In the recast zone, the values observed ranged from 910 HV to 1060 HV, except for the samples treated with the DF2-Ca in the positive polarity, which displayed 1520 HV in the hardness. The increase in microhardness may be attributed to a combination of factors [75; 76]. First, EDS analysis revealed the presence of high oxygen and carbon content on the surface, indicating the formation of titanium oxides (TiO\({}_{2}\)) and carbides (TiC), which are known to enhance resistance to plastic deformation and fracture [35]. The presence of TiO\({}_{2}\) particles dispersed on the surface acts as effective obstacles to dislocation motion. This mechanism, known as oxide dispersion strengthening, requires higher stress for dislocations to bypass or overcome the oxide particles, resulting in increased surface microhardness [77]. Carbides also have extremely high intrinsic hardness and could significantly contribute to the mechanical reinforcement of the recast layer [35]. Moreover, the rapid heating and cooling caused by the electrical discharge machining process may further contribute to hardness enhancement [76]. These improvements in surface microhardness are not only relevant from a mechanical standpoint but may also have practical implications for biomedical applications. In particular, increased hardness can enhance the wear resistance of the implant surface and contribute to its long-term durability. Higher  
Figure 5: Data representing means and standard deviations (n = 5) of Vickers microhardness from three regions of each group of machined samples.  
hardness reduces the formation of wear debris and delays corrosion-related degradation, both of which are critical factors for implant longevity [78].
# Leveraging Static and Dynamic Wear Leveling to Prolong the Lifespan of Solid-State Drives
## 3 Greedy with Migration Pool  
### Overview  
To harness the synergy of static and dynamic wear leveling, we propose the Greedy-MP (Migration Pool) policy, integrating both strategies. Initially, the Greedy-MP policy does not perform wear leveling, aiming to enhance the efficiency of garbage collection and reduce its frequency by employing the greedy policy. In other words, the block with the highest invalidation ratio is selected as the victim block for garbage collection.  
However, if a particular block exhibits excessive erasures compared to others, exceeding a predefined threshold, static wear leveling is initiated. During this phase, cold data from other blocks are migrated to the worn-out block, and to prevent this worn-out block from being selected again for garbage collection, the migrated worn-out blocks are segregated into a distinct pool called as the migration pool. Blocks in the migration pool are exempt from being chosen as the victim for garbage collection until their erase counts reach a similar level compared to other blocks, even if their invalidation ratios are elevated. This approach effectively delays the progression of worn-out blocks into bad blocks, thereby extending the operational lifespan of the SSD.
## 3 Numerical Experiments and Discussions
### Simulation Data
#### 3.1.1 GPS System  
In the simulation, the 24 satellite GPS constellation was used to simulate the satellite observations. The peseudorange noises follow the same uncorrelated Gaussian distribution and the diagonal covariance matrices \(\mathbf{\Sigma}_{G(k)}\) satisfies  
\[\mathbf{\Sigma}_{G(k)(i,i)}=\sigma_{t0 RA(k),i}^{2}+\sigma_{mppo(k),i}^{2}+ \sigma_{sur(k),i}^{2} \tag{27}\]  
where \(\mathbf{\Sigma}_{G(k)(i,i)}\) is the \(i^{th}\) diagonal elements of \(\mathbf{\Sigma}_{G(k)}\), \(\sigma_{t0 RA(k),i}\) is the user range accuracy (URA) of the \(i^{th}\) satellite at time \(k\), which is set to be 0.75 m [28]. The error model for tropospheric delay error \(\sigma_{tropo(k),i}\) is defined by:  
\[\sigma_{approx(k),i}=0.12\times 1.001\,/\sqrt{0.002001+\sin(\theta_{i}(k))^{2}}\]  
where \(\theta_{i}(k)\) is the elevation angle of the \(i^{th}\) satellite. As for the other terms in Equation (27), the user error \(\sigma_{user(k),i}\) is modeled according to [29] as:  
\[\sigma_{user(k),i}=\sqrt{\sigma_{MP}^{2}+\sigma_{Noise}^{2}}\sqrt{f_{L1}^{4}+ f_{LS}^{4}}\,/\,f_{L1}^{2}-f_{LS}^{2})\]  
where \(\sigma_{MP}\)=0.13+0.53 exp(-189\({}_{i}\)/ \(\pi\)), \(\sigma_{Noise}\)=0.15+0.43 exp(-180\({}_{i}\)(\(k\)) / 6.9 / \(\pi\)), \(f_{L1}=1575.42\) MHz, and \(f_{LS}=1176.45\) MHz. The bias of the faulty pseudorange was manually set to assert the performance of integrity monitoring.
## 4 Study Results
### Exploratory Factor Analysis Results  
An exploratory factor analysis was performed to verify the latent variable structure for the collected survey questionnaire values. For the fitness test used to perform the factor analysis, [PERSON]'s test for sphericity (\(\chi^{2}\) = 4296.664 (325), \(p\) = 0.000 \(<\) 0.05) and the Kaiser-Meyer-Olkin (KMO) measure value (=0.946 \(>\) 0.6) were calculated. All values satisfied the minimum acceptable score proposed by [PERSON] (1974).  
Direct oblimin and principal component analysis were used for factor analysis rotation and factor extraction, respectively, to perform the exploratory factor analysis. The execution results demonstrated that the factor rotation converged in 14 iterations, and three components whose initial eigenvalues were greater than 1.0 were extracted (Table 6). The minimum acceptable score in the factor loading was set to 0.5 in this study [32]. The factor loadings for C1, C9, C12, and C13--survey questions in which cognition was included--were less than 0.5. Accordingly, these four survey questions and their values were excluded from the final analysis.
## 5 COGNIFOG Evaluation in an IoT Connectivity Testbed
### Network Traffic Types and Characteristics  
In the presented IoT testbed environment, the link between the IoT edge GW and the edge server may accommodate three distinct traffic flows. The characteristics of each traffic type are described below:  
* **A. UDP background streaming flow:** A continuous flow of UDP traffic with a constant data generation rate (\(R_{\text{UDP}}\)) was used to assess the network's performance under streaming-like traffic loads, such as those generated by a CCTV surveillance camera. To generate this traffic flow, a containerized version of the iPerf3 tool was deployed to both the IoT edge GW (acting as the iPerf3 client) and the edge server (acting as the iPerf3 server).
* **B. Smartwatch simulator:** A number of \(n_{\text{SW}}\) smartwatches were simulated from a web application run in a laptop belonging to the testing network. Every simulated smartwatch sent five messages (\(k_{\text{SW}}~{}=~{}5\)) via Ethernet to the MQTT bridge (with QoS level equal to 0) located at the IoT edge GW every \(t_{\text{SW}}\) seconds with synthetic information about vital signs (namely, heart rate and oximetry), steps, and other complementary information (namely, location and battery level). The MQTT QoS level was set to 0, ensuring best-effort delivery with no acknowledgment by the receiver and, consequently, providing the same guarantee as the underlying TCP protocol. The IoT edge GW, in turn, forwarded those messages to the MQTT broker located at the edge server. The payload size of each of these messages was roughly 350 bytes (\(l_{\text{SW}}~{}=~{}350\) B). The simulated version of the smartwatches employed in this study greatly simplifies the communication challenges associated with a shared channel, such as those potentially encountered in a real-world WiFi-based scenario. Although the mitigation of such issues is out of the scope of the present paper, it is important to note that a key component of the future fully integrated COGNIFOG framework, the _network RAN controller_, has been specifically designed to manage radio access in cellular and wireless networks.
* **C. Real IoT devices:** Two ESP32 boards (\(n_{\text{ESP}}~{}=~{}2\)) were integrated into the testbed, sending one message (\(k_{\text{ESP}}~{}=~{}1\)) via WiFi to the MQTT bridge (with QoS level equal to 0) located at the IoT edge GW every \(t_{\text{ESP}}\) seconds with synthetic information about the heart rate. As in the previous case, the IoT edge GW also forwarded those messages to the edge server. The payload size of these messages was roughly 250 bytes (\(l_{\text{ESP}}~{}=~{}250\) B).
## 4 Evaluation Criteria and Experimental Results
### Aspect Extraction (SA-LDA Model)  
The result shows that SA-LDA extracts valuable aspects and relates them to the main aspect. However, LDA extracts many unrelated aspects along with some adjective words which are considered as opinion words more than aspects. Table 3 compares the results obtained from both models for each domain. The coloured words in'red' indicate the errors or unrelated aspects. We manually evaluated the model based on the number of words that are related to the seed words/aspect which is our manual evaluation of the models. Even with these upsetting words, the proposed models can produce better results. However, the proposed model is flexible in a way that enables it to be adapted in any domain by specifying the seed words for the needed aspects.  
Additionally, when the two results are compared, it is obvious that the proposed model outperforms the baseline model. Tables 3 and 4 illustrate the results of the performance of the two models in light of the three domains. Concerning the accuracy of SA-LDA, as illustrated in Table 4, it is clear that the Restaurant has the highest score with 86.7% while the Movie comes second with a score of 83.3%. Yet, Domestic Saudi Airline has the lowest score of 80%. Conversely, the standard model (LDA) scored lower accuracy results with 54%, 41% and 32% for Movie, Restaurant and Domestic Saudi Airlines, respectively. In conclusion, these results indicate that the proposed model has been more successful in detecting more correlated aspects, and it is likely to yield improved results with better performance.
# Photocatalytic Inactivation as a Method of Elimination of _E. coli_ from Drinking Water
## 3 Inactivation Process by Photocatalysts
### Metal Oxides as Photocatalysts for the Inactivation of E. coli
Thus, different structural modifications of titanium oxide have been carried out to reduce the band gap energy of titanium oxide in order to absorb in the visible region of the solar spectrum, which accounts for the larger percentage of the spectrum. Titanium oxide also displays better bactericidal performance against _E. coli_ when jointly doped with silver and nitrogen. The death of _E. coli_ was ascribed to the disconfiguration of the cell and cell wall thinning through oxidative damage under visible light [60]. [PERSON] et al. [13], for example, reported that TiO\({}_{2}\) inactivated all _E. coli_ cells within 60 min with UV light.
###### Abstract  
While transcranial ultrasound imaging is a promising diagnostic modality, it is still hindered due to phase aberration and multiple scattering caused by the skull. In this paper, we compare near-field phase-screen modeling (PS) to a geometry-based phase aberration correction technique (GB) when an ultrafast imaging sequence (five plane waves tilted from \(-15\) to \(+15\) degrees in the cutaneous tissue layer) is used for data acquisition. With simulation data, the aberration profile (AP) of two aberrator models (flat and realistic temporal bone) was estimated in five isoplanatic patches, while the wave-speed of the brain tissue surrounding the point targets was either modeled homogeneously (ideal) or slightly heterogeneously to generate speckle (for mimicking a more realistic brain tissue). For the experiment, a phased array P4-1 transducer was used to image a wire phantom; a 4.2-mm-thick bone-mimicking plate was placed in front of the probe. The AP of the plate was estimated in three isoplanatic patches. The numerical results indicate that, while all the scatterers are detectable in the image reconstructed by the GB method, many scatterers are not detected with the PS method when the dataset used for AP estimation is generated with a realistic bone model and heterogeneous brain tissue. The experimental results show that the GB method increases the signal-to-clutter ratio (SCR) by 7.5 dB and 6.5 dB compared to the PS and conventional reconstruction methods, respectively. The GB method reduces the axial/lateral localization error by 1.97/0.66 mm and 2.08/0.7 mm compared to the PS method and conventional reconstruction, respectively. The lateral spatial resolution (full-width-half-maximum) is also improved by 0.1 mm and 1.06 mm compared to the PS method and conventional reconstruction, respectively. Our comparison study suggests that GB aberration correction outperforms the PS method when an ultrafast multi-angle plane wave sequence is used for transcranial imaging with a single transducer.  
t 2022  
<concept> <concept>  
Our method estimates the position, geometry, and sound speed of the bone layer with ultrasound (no need for a CT or MRI scan) and using one probe [31] and enables real-time imaging [34].  
In this work, we aim to compare the PS approach and the ARC-GB aberration correction technique when an ultrafast imaging sequence (transmission of five multi-angle plane waves) is used for data acquisition and real-time imaging with a single probe. This paper shows that the ARC-GB method results in higher image quality compared to the PS method. Unlike the PS method, the ARC-GB method is not affected by the speckle caused by brain tissue heterogeneity.
# Opportunistic In-Flight INS Alignment Using LEO Satellites and a Rotatory IMU Platform
## 5 Experimental Evaluation and Results
### Doppler Shift Measurements
#### 5.2.2 Flight Experiment  
The flight experiment was on 14 April 2021. During the 10 min of the experiment, five Iridium-Next satellites were observed in two different planes. The downlink bursts of these satellites, Iridium-130, Iridium-131, Iridium-134, Iridium-145, and Iridium-157, were acquired using the MC-SDR. Figure 9 shows the tracked Doppler shifts during the entire trajectory. The Doppler shifts were acquired in the quaternary messaging channel as it was the most powerful and dense measurement obtained by the receiver. The resolution  
Figure 8: Estimated and simulated Doppler shifts for (**a**) Iridium-141 satellite, and (**b**) Orbcomm FM-113 satellite.  
Figure 6: (**a**) Geographical view of the overhead satellites. (**b**) Tracked Doppler shifts from the Iridium 141 in three different channels: quaternary message, primary message, and ring alert.  
Figure 7: Power spectral density (PSD) analysis representation for the transmitted downlinks of Orbcomm FM 113 satellite.  
of the Doppler shift was different for satellites in various orbital planes. In this case, the transmitted messaging bursts from Iridium 130, 131, and 134 were in a range of around \(-40\) kHz to 40 kHz; however, this range for the Iridium 157 and 145 was between \(-20\) kHz to 20 kHz. The distance of each orbital plane led different elevation angles seen by the receiver. Additionally, the quality of the measurement acquired by the satellites in the closer plane was much better, as depicted in Figure 9. This means that the satellites located on the closer plane pass the receiver's location with a maximum elevation angle of \(62.3^{\circ}\); however, the elevation angle for satellites of the other plane was at a maximum at \(21.5^{\circ}\). Figure 9 also represents the orbit path of the satellites and the receiver's location.
## 3 Proposed Method
### Spatial-Channel Attention Gate (scAG)  
sAG and cAG are complementary, where sAG focuses on spatial concepts and cAG concentrates on channel concepts. Therefore, in order to take full advantage of both attention gates, we multiply the input feature with a spatial attention map and channel attention map to construct the final refined features. The refined features are then incorporated with decoder features for further calculation. Figure 4 depicts the combination of the information from the two attention gates.