esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel Approach to Incremental Diffusion for Continuous Dataset Updates in Image Retrieval
## 7 Experiments
### Computational Efficiency  
In this section, we quantitatively evaluate the computational efficiency of runtime and pre-computation. Figure 4 illustrates the efficiency of our proposed method in handling new data. Here, we simulate the data growth by adding extra data samples to the revisited Oxford dataset. Specifically, we compare the extra runtime and pre-computational costs of online diffusion, offline diffusion, and our proposed method. As shown in Figure 4A, online diffusion has the longest runtime and would be longer for datasets that have more queries. On the other hand, since we do not need to run k-NN search again for queries and anchors, our proposed method is even faster than the offline diffusion at runtime when handling new data. For the pre-computation, our method requires the reconstruction of new data from existing anchors, thus resulting in a computational cost linearly related to the number of new data samples. Nevertheless, it is still very efficient compared to recomputing the inverse of the Laplacian required by offline diffusion (see Figure 4B).  
As reported by [5], the overhead of offline diffusion over k-NN search is negligible, making it remarkably faster than the online diffusion at runtime. In particular, the average cost per query is merely \(\sim\)2 ms on the Oxford dataset. Following [5], we run the proposed method 10 times and take the average computational time for comparison. In contrast to the offline diffusion whose runtime complexity is linear to the number of gallery images, the runtime complexity of our proposed method is linear to the number of anchors (\(k<n\)). In consistency with the complexity analysis, our proposed method costs \(\sim\)0.8 ms per query on the Oxford dataset, which is even faster than the offline diffusion.  
Figure 3: Retrieval performance (mAP) vs. the maximum number of nearest anchors used for LAE.  
Now we discuss pre-computational efficiency. The pre-computation of offline diffusion consists of the graph construction and the random walk. Our proposed method takes advantage of the anchor graph and therefore spends less time in these steps. However, we do introduce extra overhead to obtain anchors and perform the local anchor embedding. For anchors, we simply apply K-Means clustering using the efficient FAISS [23]. It allows us to find cluster centers at a negligible cost: it takes less than one second for \(\mathcal{R}\)Oxford. We then focus on investigating the cost of local anchor embedding. As its complexity implies, the cost of LAE depends on three parameters: \(n\), \(k\), and \(s\). We learn from the parameter study that the adjustable parameters \(k\) and \(s\) both have impacts on the retrieval performance. This causes a speed/accuracy trade-off. To reach a balance, we set \(k=2048\) and \(s=50\) to achieve satisfactory performance at an acceptable cost. With this setting, LAE takes about 1.4 ms to reconstruct the feature of each gallery image.
_Applied_  
_sciences_  
_Advticle_  
**Low-Field NMR and MRI to Analyze the Effect of**  
**Edible Coating Incorporated with MAP on Qualities**  
**of Half-Smooth Tongue Cole (Cynoglossus Semilaevis Gunther) Fillets during Refrigerated Storage**  
**[PERSON] 1,2,3, [PERSON] 1,2,3, [PERSON] 1,2,3, [PERSON] 1,2,3,* and [PERSON] 1,2,3,***  
Shanghai Engineering Research Center of Aquatic Product Processing & Preservation, Shanghai Professional  
Technology Service Platform on Cold Chain Equipment Performance and Energy Saving Evaluation,  
Shanghai 201306, China; [EMAIL_ADDRESS] (N.L.); [EMAIL_ADDRESS] (Y.S.); [EMAIL_ADDRESS] (W.L.)  
National Experimental Teaching Demonstration Center for Food Science and Engineering, Shanghai Ocean  
College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China  
Correspondence: [EMAIL_ADDRESS] (J.M.); [EMAIL_ADDRESS] (J.X.)  
Received: 30 July 2018; Accepted: 15 August 2018; Published: 17 August 2018  
**Featured Application: The monitoring of quality characteristics of Half-smooth tongue sole (HTS, Cynoglossus semilaevis Gunther) is essential during refrigerated period based on the edible coating incorporated with MAP treatment, which has not displayed in the previous literatures. Meanwhile, the low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) technology has a potential development to assess the quality of aquatic products, which is applied to assess the water distribution and migration of HTS fillets during 24-day storage. This study demonstrate that results of LF-NMR and MRI have the close connection with the physicochemical parameter of HTS fillets and can be applied to monitor water migration in a noninvasive and fast way.**  
**Abstract:** Nondestructive and fast measurement and characterization of fish is highly desired during various processing treatments. This research investigated the effectiveness of low field LF-NMR and MRI as fast monitoring techniques to estimate the qualities of half-smooth tongue sole fillets treated with edible coating combined with modified atmosphere packaging during refrigeration. T\({}_{2}\) relaxation spectra showed three peaks representing bound water (T\({}_{21}\)), immobile water (T\({}_{22}\)), and free water (T\({}_{23}\)), respectively. pT\({}_{22}\) accounted for the largest proportion of three types of water, followed by pT\({}_{23}\). The weighted MRI provided the internal structure information associated with different samples, indicting the combination of edible coating and MAP (70% CO\({}_{2}\) + 30% N\({}_{2}\)) is the best performance in the maintenance of qualities and freshness of HTS fillets. All results demonstrated that the combination of LF-NMR and MRI as fast and nondestructive methods have great potential to monitor qualities deterioration and predict shelf life in of HTS fillets during refrigerated storage.  
**Keywords:** half-smooth tongue sole; LF-NMR; edible coating; modified atmosphere packaging
## 6 Speech Quality and Intelligibility Evaluation
### Objective Evaluation
#### 6.1.3 Hearing Aid Speech Perception Index (HASPI)  
The HASPI uses auditory models to predict intelligibility. The auditory model combines all aspects of normal and impaired peripheral auditory function [38] by calculating the correlation value \(c\) (Equation (16)) between the output of the auditory model of the degraded test signal (i.e., the spectral shape of the signal enhanced over time) and the generation of the unprocessed reference input signal.  
\[c=\frac{1}{5}\sum_{j=2}^{6}r(j) \tag{16}\]  
where \(j\) is the basis function number, and \(r(j)\) is the normalized correlation; more details can be found in [38].  
The reference signal is the output of the normal-hearing model, and the input has no noise or other degradation. For normal-hearing listeners, the processed signal is the output of the normal-hearing model with a degraded signal as the input. For hearing-impaired people, the auditory model is used to modify the processed signal to include hearing loss, and the model input includes amplification to compensate for the loss.  
Auditory coherence is used to measure the cross-correlation of the high-level part (expressed as \(a_{high}\)) of the enhanced signal and the clean signal in each frequency band. The envelope is sensitive to the dynamic signal behaviour related to consonants, while the cross-correlation tends to retain the harmonics in stable vowels. Finally, the HASPI score is calculated according to \(c\) and \(a_{high}\). Let \(a_{low}\) be the low-level auditory coherence value, \(a_{mid}\) be the mid-level value, and \(a_{high}\) be the high-level value, then the HASPI intelligibility is given by:  
\[p=-9.047+14.817c+0.0a_{low}+0.0a_{mid}+4.616a_{high} \tag{17}\]  
Details of the HASPI and auditory model are shown in [38,39].
## 1 Introduction
Children are considered a special group because they are particularly susceptible to the effects of background noise [29; 30], with higher SNRs required to achieve similar performance levels as young adults on a wide range of auditory tasks [18; 31; 32]. These difficulties were explained by a combination of central ('top-down') and peripheral ('bottom-up') factors. Immature 'top-down' processes in children are influenced by the developing cognitive and language capabilities. With particular relevance to listening in noisy conditions, children show deficits in their ability to attribute incoming sounds to their corresponding sources or to selectively attend to an auditory object for further processing while disregarding irrelevant auditory information [19; 33; 34; 35; 36]. Despite the fact that the cochlea is developed at birth [37], studies showed age-related increase in sensitivity to frequency differences with pure tones or F0 [38; 39; 40], as well as improved recognition of spectrally reduced speech with age [41; 42], supporting the notion of immature peripheral factors, such as spectral and temporal processing [18; 43; 44] and/or less efficient top-down cognitive processing, including attention and short-term memory [45; 46]. Moreover, in quiet conditions, VD was observed to gradually improve with age in 4-12-year-old children, with the children's formant discrimination becoming adult-like earlier than their F0 discrimination [47]. The presence of background noise may therefore have a different effect on VD for children compared to adults, considering the immaturity of central and auditory processing of the former. The present study aimed to examine the use of voice cues (F0 and formants and a combination of both) for discriminating between speakers with background noise in NH young adult and school-age children. It was hypothesized that in quiet conditions, formant cues will yield better VD compared to F0 cues for both children and adults, whereas in noisy conditions, the adults and children will exhibit distinct outcome patterns, with the adults better utilizing F0 for VD.
###### Abstract  
In this research, pectin extraction from grapefruit peel (GPP) was performed using a microwave-assisted high-pressure CO\({}_{2}\)/H\({}_{2}\)O (MW-HPCO\({}_{2}\)) system. The Box-Behnken design of response surface methodology was applied for the optimization of MW-HPCO\({}_{2}\) extraction conditions to obtain the highest pectin yield. The effects of temperature, time, and liquid/solid ratio on pectin yield were examined in the range of 100-150 \({}^{\circ}\)C, 5-15 min, and 10-20 mL g\({}^{-1}\), respectively. Under the optimum extraction conditions (147 \({}^{\circ}\)C, 3 min, and 10 mL g\({}^{-1}\)), pectin was obtained with a yield of 27.53%. The results obtained showed that the extraction temperature and time had a strong effect on the pectin yield, while the effect of the liquid/solid ratio was not significant, and the pectin was effectively extracted from grapefruit peel (GP) using MW-HPCO\({}_{2}\). Additionally, the application of GPP in apricot jam showed that MW-HPCO\({}_{2}\)-GPP can be used as a thickener in the food industry. The yield and physicochemical properties (ash, protein, galacturonic acid, reducing sugar and methoxyl content, degree of esterification, equivalent weight, color, viscosity) of pectin extracted in the optimum conditions of the MW-HPCO\({}_{2}\) method were superior to pectin extracted by the traditional method. The results of this study revealed that MW-HPCO\({}_{2}\) could be an innovative green and rapid technique for pectin extraction.  
pectin; grapefruit peel; extraction; microwave-assisted high-pressure CO\({}_{2}\)/H\({}_{2}\)O
## 4 Experiment and Results
### Ablation Study
#### 4.5.1 Design of the ConvNHS Module  
In the first branch of the LFE block, before the feature map enters the attention mechanism, it will be preprocessed by the convolution block ConvNHS. Whether effective location information can be extracted from the later attention mechanism depends largely on this module. Therefore, the ConvNHS module played a key role. The ConvNHS module is mainly composed of convolution, normalization, and activation functions. Different normalization methods were tested in the ConvNHS module under the GPU environment, and LCN achieved the best effect, followed by BN in Figure 7a. Therefore, LCN with the best effect was used in the GPU, and BN with the best effect in global normalization was used in the CPU.  
Based on the above experiments, LCN was selected for the normalization method. Next, the number of ConvNHS modules was further explored. As shown in Figure 7b, when three ConvNHS modules were inserted into the network, the detection effect was the best. Therefore, three ConvNHS modules were designed for subsequent experiments.
# Safety Evaluation of Crossing Tunnel Engineering: A Case Study
## 4 Conclusions  
This study used the finite element software Midas GTS to establish a numerical model of tunnel excavation and conducted a safety evaluation for the project involving the crossing of the Jijiapo highway tunnel and the Yangmuling railway tunnel. The following conclusions can be drawn:  
1. Analysis of the vertical alignment intersection closeness in tunnels shows that the new railway tunnel has an effect on the existing highway tunnel structure, but the effect is weak, and it usually does not cause harm;
2. The horizontal displacement is the smallest at the invert and vault of the highway tunnel, slightly larger at the left and right arch feet, and the largest at the left and right side walls. The horizontal displacement of the highway tunnel initially remains relatively constant with distance from the front face of the railway tunnel, then increases rapidly, and finally converges without further increase. The maximum horizontal displacement caused by the railway tunnel construction is 0.540 mm and \(-\)0.59 mm;
3. The vertical displacement is the largest at the arch top and the smallest at the invert of the highway tunnel. Similar to the horizontal displacement, the vertical displacement of the highway tunnel also shows an increasing trend with the distance from the face of the railway tunnel. The maximum vertical displacement caused by railway tunnel construction is 1.42 mm;
4. The vibration velocity is highest at the vault of the highway tunnel and increases initially before decreasing with time, reaching a peak value of 1.527 cm/s at 16 ms. Throughout the entire process of blasting construction, the vibration velocity of the highway tunnel remains below 2 cm/s. The results demonstrate that the excavation process for the railway tunnel in this study is safe and manageable for the adjacent highway tunnel.  
Writing--original draft preparation, D.X.; writing--review and editing, W.G.; visualization, Y.M.; supervision, Z.Y.; project administration and funding acquisition, D.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Science and Technology Project of Transportation Department of Hubei Province (2020-2-5-3) and the National Natural Science Foundation of China' Youth Foundation Project (41807263).  
Not applicable.  
Figure 13: Time-history curve of arch vibration of highway tunnel at intersection.
## 4 QoS and QoE  
### Traditional QoS and QoE Metrics  
Quality of service (QoS) measures a computer network's overall performance, with a particular focus on the experience of network users. In packet-switched communication networks, QoS refers to traffic prioritization and resource reservation rather than the achieved service quality. To quantitatively measure QoS in traditional networks, several metrics, such as latency, throughput, packet loss, bit rate, bandwidth, and jitter, are generally considered [27].  
Quality of experience (QoE) measures the satisfaction or annoyance of a customer's experience with a service, with the evaluation results typically presented as a quality score or rating referenced to a specific scale. The mean opinion score (MOS) is the standard metric used to measure QoE, obtained from subjective human tests. QoE in multimedia applications is a multidimensional construct that extends beyond mere technical metrics to capture the holistic user perception of media delivery. It incorporates various factors, such as initial playback delay [28; 29], multimedia synchronization [30], audio/video encoding rate, frame rate [31], stalling or buffering [32; 33], video presentation quality, viewing device, and human factors [34; 35; 36].
# Asphalt Pavement Transverse Cracking Detection Based on Vehicle Dynamic Response
## 4 Optimized Short-Time Fourier Transform (STFT) Algorithm
### Parameter Optimization
#### 4.2.2 Window Length (wl)  
We select _wl_ = 8, 16, 32, 64, and 128 for the analyzed values. Compared with normal pavement, transverse cracks show a significant high-frequency intensity area at the central position. The yellow part indicates the high-frequency intensity and the power spectral density of signal frequency (Figure 6). Normal pavement is relatively uniform, and no concentrated frequency intensity appears. STFT can overcome the problem that noise in the time domain greatly affects the crack feature. By increasing the window movement, the mutation of the signal at the crack can be reflected as the mutation of the intensity of each frequency component in a very short time.  
\begin{table}
\begin{tabular}{c c} \hline
**No.** & **Title 2** \\ \hline a & Rectangle window \\ b & Triangular window \\ c & Hanning window \\ d & Hamming window \\ e & Blackman window \\ \hline \end{tabular}
\end{table}
Table 2: Different window types.  
Figure 5: Different features in the time–frequency domain based on five window types between a transverse crack sample (left) and a normal section sample (right). (**a**) Rectangle window; (**b**) triangular window; (**c**) Hanning window; (**d**) Hamming window; (**e**) Blackman window.  
Figure 6: Time–frequency diagrams based on different \(wl\) between a transverse crack sample (left) and a normal section sample (right). (**a**) \(wl\) = 128; (**b**) \(wl\) = 64; (**c**) \(wl\) = 32; (**d**) \(wl\) = 16; (**e**) \(wl\) = 8.  
Regarding spatial resolution, the window function length is equal to 128, which allows for the maximum frequency resolution. The frequency intensity in the fracture area presents a normal mountain distribution.  
As the \(wl\) increases, the frequency resolution increases. The bar becomes column-like when using the minimum window function length included in this study, 8. The difference in frequency strength between cracks and the intact pavement is no longer obvious. But as the window function length decreases, the time resolution of cracks gradually increases.  
The perception of change on the time scale is more detailed. When \(wl\) is equal to 128, the crack position is located at 0.2-0.3 s, which is quite different from the time domain.  
When \(wl\) is equal to 64, it shows that the crack position is at 0.12-0.23 s, which is still different from the time domain. When \(wl\) is equal to 32, 16, or 8, the crack position is at 0.12-0.18 s, which is the same as the time domain.  
Therefore, we select 32 as the optimal window function length considering both the frequency and time resolutions.
## 3 Results and Discussion
### Effect of CO\({}_{2}\)/CO Molar Ratio in the Feed  
Figure 6 displays the effect of CO\({}_{2}\)/CO molar ratio in the feed (between 1/3 and 1) on CO\({}_{\rm x}\) conversion (Figure 6a), product yield (Figure 6b) and CO\({}_{2}\) conversion (Figure 6c). The other operating conditions are: feed, ternary mixtures of H\({}_{2}\) + CO + CO\({}_{2}\) with H\({}_{2}\)/CO\({}_{\rm x}\) molar ratio of 3; temperature, 275 \({}^{\circ}\)C; pressure, 30 bar; space time, 10 g\({}_{\rm cat}\) h (mol\({}_{\rm C}\))\({}^{-1}\). The results are consistent with those reported in the previous sections and reinforce the fact that an increase in the concentration of CO\({}_{2}\) in the feed leads to a decrease in CO\({}_{\rm x}\) conversion and in DME yield, in good agreement with the results reported in the literature [25]. The upgrade of CO\({}_{2}\) conversion with increasing CO\({}_{2}\)/CO ratio is also confirmed in Figure 6c.  
When analyzing the effect of CO\({}_{2}\)/CO molar ratio on the conversion of CO\({}_{2}\) for different values of space time (within the 2.5 and 10 g\({}_{\rm cat}\) h (mol\({}_{\rm C}\))\({}^{-1}\) range), (Figure 7), it is observed that the importance of the favorable effect of decreasing space time on the conversion of CO\({}_{2}\) depends on the CO\({}_{2}\)/CO ratio in the feed. Indeed, for low values of this ratio (1/3), the conversion of CO\({}_{2}\) is significantly favored using low space time values. Nevertheless, this effect decreases when increasing CO\({}_{2}\)/CO ratio, that is, under operating conditions of higher CO\({}_{2}\) conversion.  
Figure 5: Effect of H\({}_{2}\)/CO\({}_{\rm x}\) molar ratio in the feed on the conversion of CO\({}_{\rm x}\) and DME yield (**a**); CO\({}_{2}\) conversion (or CO\({}_{2}\) yield, for negative values) (**b**). Reaction conditions: Feed, H\({}_{2}\) + CO + CO\({}_{2}\) with CO\({}_{2}\)/CO molar ratio of 1; 275 \({}^{\circ}\)C; 30 bar; 10 g\({}_{\rm cat}\) h (mol\({}_{\rm C}\))\({}^{-1}\).  
Figure 6: \(Cont.\)Figure 6: Effect of CO\({}_{2}\)/CO molar ratio in the feed on the conversion of CO\({}_{\rm x}\) (**a**); Product yield (**b**); CO\({}_{2}\) conversion (or CO\({}_{2}\) yield, for negative values) (**c**). Reaction conditions: Feed, H\({}_{2}\) + CO + CO\({}_{2}\) with H\({}_{2}\)/CO\({}_{\rm x}\) molar ratio of 3; 275 \({}^{\circ}\)C; 30 bar; 10 g\({}_{\rm cat}\) h (mol\({}_{\rm C}\))\({}^{-1}\).  
Figure 7: Effect of CO\({}_{2}\)/CO molar ratio in the feed on the CO\({}_{2}\) conversion (or CO\({}_{2}\) yield, for negative values), for different space time values. Reaction conditions: Feed, H\({}_{2}\) + CO + CO\({}_{2}\) with H\({}_{2}\)/CO\({}_{\rm x}\) molar ratio of 3; 275 \({}^{\circ}\)C; 30 bar.
## 4 Changing the Cultivation Conditions for Optimizing the Production of Bioactive Compounds
### Compartmentalization of EPA and DHA Synthesis
Lipid analysis of the mutant revealed a decreased level of EPA and of the eukaryotic molecular species of MGDG and an increased proportion of TAG by comparison with the wild-type. Pulse-chase labelling of the wild-type algae with radioactive fatty acid precursors showed an initial incorporation of the fatty acids into PC and TAG. In the chase period, the label of these lipids decreased with time while that of chloroplastic lipids, mainly MGDG, continued to increase. In the mutant, however, the labelling of TAG after the pulse was higher than that of the wild-type and decreased only slightly in the subsequent chase. It was concluded that in wild-type _Porphyridium cruentum_, TAG can supply acyl groups for the biosynthesis of eukaryotic species of MGDG [286]. Concerning the DHA synthesis, some microalgae as _Isochryssis galbana_ or _Pavlova lutheri_ (Haptophyta) are known to produce this fatty acid from C20 metabolism such as EPA [283]. According to previous studies conducted in _Pavlova lutheri_, it could be considered that the DHA synthesis and its incorporation into lipids are specific of the endoplasmic reticulum fraction with a preferential incorporation into the phospholipids and the betaine lipids [265,278]. Furthermore, as EPA is preferentially incorporated into the galactolipid fractions, these lipids being specific of chloroplastic metabolism, it can be considered that after a chloroplastic synthesis, EPA would be exported from this compartment into the endoplasmic reticulum in which it would be elongated and desaturated into DHA before being incorporated into specific polar lipids of this compartment. Another marine microcalga, _Crypthecodimium cohnii_, is known to be rich in DHA without accumulation of other PUFAs of the omega-6 and the omega-3 series. In this microcalga, the DHA level is about 40%-50% of the total fatty acids without intermediate substrates and products of desaturation and elongation steps. This heterotrophic chloroplast-less microalga has a specific metabolism in which other enzyme pools and subcellular compartments are involved in PUFA synthesis [287].