esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
This paper proposes a framework for classifying and identifying defects of underground PE gas transmission pipes. Fast and accurate detection of defects in PE pipelines is made possible through experimental verification. The following are the main results of this experiment.  
1. Based on the similarity of images of continuous pipelines, the images were first grayed out using the weighted average method and then preliminary screening of the acquired images was conducted to identify images with suspected defects, which improved the acquisition efficiency of defect image. For the defective PE gas pipeline images, contrast was enhanced using gamma transform, and finally noise was removed using the dual filtering method. The results show that the pre-processing technique can speed up image processing while retaining much of the detail of the originals.
2. In order to detect the edges of image defects, an improved Sobel algorithm was presented. An adaptive thresholding segmentation method was used to segment the defects in the image. Then, after morphologically processing the image to obtain a binary image, the feature parameters of the defects were extracted.
3. The obtained binary images were trained using VGG16, and the classifier was completed by selecting appropriate parameters for classification of various defects in images of the PE gas pipes. The experimental test results reveal that the highest accuracy of the classification approach adopted in this paper is 97% and it can be used not only for the identification of defective types of underground PE gas transmission pipes, but also for steel pipes, cast iron pipes, etc.  
Conceptualization, Y.W.; data curation, Q.F.; formal analysis, Y.W. and N.L.; funding acquisition, Y.W.; investigation, Y.W. and T.E.; methodology, N.L.; project administration, Y.W.; resources, Y.W. and N.L.; software, N.L.; supervision, Y.W. and H.L.; validation, H.Z.; visualization, Q.F.; writing--original draft, Q.F. and H.Z.; writing--review and editing, T.E. and H.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (no. 11903072), the Xinjiang University Doctoral Start-up Foundation (no. 620321029) and the Science and technology planning project of State Administration for Market Regulation (no. 2022 MK201).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available.  
The authors wish to thank all the reviewers who participated in the review during the preparation of this manuscript.  
The authors declare no conflict of interest.  
Figure 14: Comparison of three algorithms confusion matrix.
## 3 Inter Symbol Interference
The convolution is represented by the weight function h(n), which overlays the input signal, resulting in the sum of the input samples being weighted by the filter coefficients. The sum is the response of the filter at a certain moment. Therefore, a noisy output of the equivalent discrete channel y(n) is given by:  
\[\mathrm{y(n)}=\sum_{k=0}^{L-1}h(k)x(n-k)+w(n), \tag{4}\]  
The C(n) equalizer is defined by the C\({}_{k}\) coefficients, and its output \(\hat{x}(n)\) is the sum of the received signal samples weighted by the equalizer coefficients. Therefore, the equalizer output \(\hat{x}(n)\) is given by:  
\[\hat{x}(n)=\sum_{k=0}^{L-1}C_{k}y(n-k), \tag{5}\]  
It is useful to adopt matrix notation for the equalizer output, such as:  
\[\hat{x}(n)=\sum_{k=0}^{L-1}C_{k}y(n-k)=C^{T}y(n)=y^{T}(n)C, \tag{6}\]  
where C = \(\left[C_{0}\quad C_{1}\quad\ldots\quad C_{L-1}\right]^{T}\) is a vector of length L containing the coefficients of the equalizer, and \(y(n)=\left[y(n)\quad y(n-1)\quad\ldots\quad y(n-L+1)\right]\) is the vector of the most recent input data. The equalization function makes it possible to find from the received sequence y(n), which is affected by ISI, the transmitted sequence x(n) [41].
## 3 Materials and Methodology  
### Data  
In this study, we obtained snow cover, precipitation, and temperature data from the Agency of Hydrometeorology of the Committee of Environmental Protection under the Government of the Republic of Tajikistan. A detail description of the data is given in Table 1.  
In this work, the statistical techniques of the Sen's slope, modified Mann-Kendall (MMK) test, and Mann-Kendall (MK) test were used to identify trends in an abiding scale of data such as snow cover, precipitation, and temperature from recorded stations on the ground. The Pettit's test was also applied to identify rapid changes.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(\boldsymbol{\mathsf{N}}\) & **Name** & **Datasets** & **Index** & **Lon.** & **Lat.** & **Alt. (m)** & **Period** \\ \hline
1 & Anzob & Temperature, precipitation & 38,719 & 39\({}^{\circ}\)50\({}^{\prime}\) & 68\({}^{\circ}\)52\({}^{\prime}\) & 3373 & 1961–2018 \\
2 & Maykhura & Temperature, precipitation & 38,717 & 39\({}^{\circ}\)01\({}^{\prime}\) & 68\({}^{\circ}\)47\({}^{\prime}\) & 1922 & 1964–2017 \\
3 & Hushyori & Temperature, precipitation & 38,833 & 38\({}^{\circ}\)53\({}^{\prime}\) & 68\({}^{\circ}\)50\({}^{\prime}\) & 1361 & 1960–2018 \\ \hline  & Parameter & Datasets & Temporal resolution & \multicolumn{2}{c}{Spatial resolution} & \\ \hline
4 & MODIS-NDSI & Snow cover, MOD10A1 & Daily & \multicolumn{2}{c}{500 m} & 2001–2022 \\  & Terra/MYD10A1 Aqua & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Coordinate the used meteorological stations and detail the MODIS dataset applied in the Varzob River Basin in Tajikistan.  
Figure 1: The study area (Varzob River Basin in Tajikistan) and the location of the meteorological stations.
# Fooling in Membrane Distillation, Osmotic Distillation and Osmotic Membrane Distillation
## 4 Characterization Techniques for Fouling Analysis
### Ultrasonic Time Domain Reflectometry (UTDR)  
UTDR is a non-invasive technique used to monitor the deposition of combined organic and colloidal fouling on membrane surface [116]. This does not require any sample preparation and is based on the propagation of mechanical waves. The reflection and transmission can occur when an ultrasonic wave encounters an interface between two media. More details can be found in [116; 117; 118]. UTDR technique coupled with differential signal analysis was used to investigate the combined fouling deposition processes on membrane surface [118]. The steady-state waveform of distilled water was considered as the reference and the waveform of fouled membrane was considered as the test waveform. The difference between the two signals represented the signal of the fouling layer. UTDR was used for fouling detection by different authors in filtration processes. As an example, [PERSON], et al. [116] investigated the fouling behavior of mixed silica-BSA solution and silica-NaCl solution using UTDR technique in NF membranes (see Figure 6). The UTDR results of NF experiments showed that the fouling layer obtained from the combined organic-colloidal fouling (mixed silica and bovine serum albumin (BSA) and silica and NaCl solution) was denser than that obtained from the colloidal fouling layer in the presence of NaCl. The formation of the denser fouling layer was due to the electrostatic interactions between foulants and membrane surface as well as the electrostatic interactions among the foulants due to absorption of BSA onto silica [116]. [PERSON], et al. [119] used UTDR technique to provide a good estimation of the fouling layer thickness formed during RO tests. [PERSON], et al. [120] described the extension of UTDR as a non-invasive fouling monitoring technique used for the real-time measurement of particle deposition in a single hollow fiber membrane during MF. [PERSON], et al. [121] used a high-frequency 50-MHz ultrasound system to measure the fouling distribution in spiral wound UF and RO membrane modules. It is necessary to point out that this technique has not been applied yet in MD, OD and OMD fouling.
# Non-Local Effects in Brillouin Optical Time-Domain Analysis Sensors
## 3 Mitigation of Non-Local Effects
### Probe Dithering for Brillouin-Assisted Amplification of Pump Pulses  
Another beneficial side effect of using the probe dithering technique is the amplification of the pump pulses propagated along the fiber [21]. This increases the Brillouin interaction and the SNR of the probe signal received from far away locations along the fiber. A hint on how to achieve this pulse gain can be obtained from observation of Figure 4a. Notice that if the lower optical frequency probe is removed, the pump pulse experiences the gain induced by the higher frequency probe. Moreover, as this gain is broad and flat, all frequency components of the pulse are equally amplified, leading to a non distorted pulse, free from second-order non-local effects. This is a BOTDA sensor operating in a loss configuration, so that the energy is transferred from the probe wave to the pump wave and the Brillouin loss spectrum experienced by the probe is finally measured.  
We have experimentally demonstrated this idea in a 100-km BOTDA sensor, obtaining a measurement uncertainty of 1 MHz at the worst-contrast position for 1-m spatial resolution. The obtained BGS with the FM modulated dual-probe BOTDA and for the BOTDA amplification of the pump pulse technique in the same conditions are depicted in Figure 5a,b, respectively. Notice that the amplitude of the measured spectra is reduced as the pulse propagates along the fiber. However, for the system with Brillouin-assisted amplification, the amplitude starts to increase and recover at mid-link when the gain provided by the probe wave starts to be significant.  
Figure 5: Brillouin gain distribution measured with (**a**) dual-probe-sideband BOTDA sensor using frequency modulation of the probe wave and (**b**) novel BOTDA with pulse amplification. A pulse duration of 45 ns was deployed in both measurements. (From [PERSON], [PERSON], and [PERSON], “Brillouin optical time-domain analysis sensor with pump pulse amplification”, _Opt. Express_**2016**, 24, 12672–12681. With permission. Copyright 2016 Optical Society of America).
## 3 Preliminary Design
### IWT Sections
#### 3.3.4 Diffuser and Corners  
The diffuser is placed after the test section, and slows down the flow velocity with minimum pressure losses before the flow reaches the fan. By decreasing the velocity, the flow losses are reduced and the static pressure is restored for proper fan operation. In its final section, the diffuser also converts the rectangular section of the tunnel to the circular section of the fan.  
The diffuser is very sensitive to design errors that can lead to the detachment of the current [64], increasing the flow losses of the entire tunnel and even causing vibrations affecting the fan or the stability of the speed in the test section [65]. Since it is also one of the sections with the highest pressure loss in the entire circuit, its design is particularly critical for the performance of the tunnel.  
The main limitation is the length of the refrigerated chamber, which prevents the use of an ideal diffuser, which would be one without corners, with a cone angle of 3\({}^{\circ}\), a minimum length of 2.4 m (3 to 4 times the length of the test section is recommended) and an area ratio of 1 to 2-3 between the start and end [40] (p. 81).  
As it is not possible to use a straight diffuser, it is necessary to incorporate corners, and the diffuser has the following subsections: first diffuser (horizontal), first corner, second diffuser (vertical ascending), second corner and third diffuser (horizontal, which adapts the rectangular section to the circular section of the fan).  
The first two sections of the diffuser are rectangular in cross-section, so although the angle of each face to the centre line is 4\({}^{\circ}\), the angle of the equivalent cone is greater, in this case around 4.5\({}^{\circ}\). The equivalent conicity of the third fan adapter diffuser is 6.0\({}^{\circ}\).  
The final full diffuser, after the iterative process described below, has a final to initial area ratio of 7.15 and an equivalent length of 5.16 m, with an overall conicity of 3.5\({}^{\circ}\), due to the equivalent length of the corners, where there is no increase in the section.  
Expanding corners are sometime used [66; 67; 68; 69], but they add complexity in both design and manufacture, resulting in higher costs. In addition, they use higher-chordturning vanes, which add frictional resistance and ultimately do not represent a substantial improvement.
## 4 Discussion
### Regional Aspects of Complexity Indices: The Role of Posterior Regions  
We observed an association between complexity indices and global activity levels, highlighting the crucial role of suitable network activity in sustaining complex model dynamics (Table S4). However, we found a significant heterogeneity in how various local manipulations affected complexity, and this variation could not be straightforwardly accounted for by the global activity levels. As outlined in previous works [41], local, rather than global, activity features might underlie network complexity. Indeed, experimental EEG and fMRI studies conducted on humans, monkeys, and rats (during sleep, anesthesia, and following severe brain injuries) have linked the loss and recovery of consciousness to brain complexity based on the activity of posterior regions [69; 70; 71]. In this regard, a recent whole-brain modeling study [40] identified a few key nodes centered around the 'posterior hot zone' (i.e., precuneus and posterior cingulate cortex) that were pivotal for maintaining the model in an awake-like state. Reducing the activity of these nodes led to a shift in model dynamics, akin to unconscious states.  
While LZc was largely explained by the activity of the most firing nodes irrespective of their spatial location (Supplementary Results, Section S4 and Figure S6), our model showed a similar dependency of PCI on the activity of posterior regions (Figures 4 and S5). Specifically, our analysis revealed that the regional spontaneous activity (MFR\({}_{\text{ROI}}\)) displaying the highest correlations with PCI included the retrosplenial cingulate cortex, the medial parietal cortex (precuneus), and the posterior cingulate cortex. Similar findings, encompassing a similar set of posterior regions, were found for the Hconn model (Figure S4D). These results nicely complement recent empirical observations involving rats under ketamine anesthesia [72], which found a strong correlation between PCI and activity in posteromedial regions. This study demonstrated that deactivation of these posteromedial regions was associated with disruptions in long-lasting and widespread cortical interactions following electrical stimulation. Altogether, these findings suggest the central hub role of posterior regions for long-range communications in cortical networks. Consistently, we have observed a positive correlation (Figures 5 and S7) between the weighted degree (a metric quantifying hub centrality), particularly when applied to functional connectivity estimates (Figures 5c,d and S7B,C) and the PCI-R\({}^{2}\) topographies (but not for LZc-R\({}^{2}\)).
## 4 Modelling & Simulation Results
### Control System Study
The analysis of the neutron spectrum based on a 2D calculation using the deterministic TRITON/NEWT sequence of the SCALE package is presented in Figure 12. The general neutron spectrum is typical for a fast reactor with the majority of the neutrons between 10 keV and 2 MeV, with almost no thermal neutrons appearing in the system. The two different neutron spectra were both calculated independently and could be interpreted as the neutron spectrum in the upper core part: unreflected in the case the reflector is moved downwards, and the neutron spectrum in the lower core part: reflected since, there, the reflector will still enwrap the core. Both of the neutron spectra shown can be seen as the two extrema since they  
Figure 11: Control reactivity curve dependent on the stepwise downward movement of the reflector for systems with different thicknesses of the reflector. are calculated for an axially infinite system. Thus, in the region where the top end of the reflector is located, some mix of both spectra will appear. The spectrum for the unreflected case is somewhat harder than for the reflected case where some lower-energy neutrons are reflected back into the core after they have lost energy in the reflector. The appearance of neutrons with energies around 1 keV was indicated in [4] as neutrons which almost solely exist in the reflector where no fission events take place. As soon as these neutrons penetrate back into the core, they will be absorbed and have a high probability of creating fission reactions. Thus, the fission density in the outer core area will be slightly higher in the reflected core part. When the instrumentation for the zero-power core is designed well, this change will hopefully be recognizable. Thus, a neutron flux distribution can be measured for the reflected and the unreflected core to identify the effect of the reflector on future reactor operation where the reflector will be a design feature to improve the neutron economy in the core, even if it is expected that the effect of the reflector will be lower with increasing core size, as it is already visible in Figure 8.  
Following the separate study of a potential reactor shutdown system and a reactor control system, the next chapter will deliver the analysis of the interplay between both systems which will be relevant for the operation. It is apparent that there will be a noticeable interplay between the systems when analyzing the results presented in Figure 7, where the effect of the presence or absence of the side reflector has a strong influence on the shutdown reactivity.
## 2 Flash Sintering
### The Application of FS in SOFCs
#### 2.2.2 Anode  
NiO-SYSZ composite materials are widely used as anode materials in SOFCs, and their conventional sintering requires temperatures ranging from 1400 to 1500 \({}^{\circ}\)C and several hours of incubation. FS can expedite the manufacturing process and lower production expenses. [PERSON] et al. [87] employed FS to fabricate two distinct compositions of NiO-YSZ composites with varying NiO concentrations, utilizing two different sintering atmospheres. Sintering in air resulted in rapid densification within a few seconds, while sintering in a reducing atmosphere-conditioned FS resulted in the in-situ reduction of NiO to Ni metal but did not contribute to densification. Flash-sintered NiO-SYSZ composite anodes offer substantial energy and cost savings while allowing for the precise control of porosity  
Figure 5: Schematic of DC-sintering device. (Reproduced from [70] with permission from Elsevier).  
Figure 6: Time dependence of (**a**) different limited current density and applied electric field, (**b**) power dissipation of LSGM samples during SCFS process. (Reproduced from [86] with permission from Elsevier).  
through the manipulation of the electric parameters and sintering environment. Nevertheless, additional investigation and verification are necessary in order to comprehend their electrochemical and mechanical properties.  
GDC exhibits higher conductivity than YSZ in the intermediate-temperature range [88; 89]. Hence, NiO-GDC proves to be a more appropriate choice as an anode material for SOFCs operating at intermediate temperatures. [PERSON] et al. [90] effectively utilized the FS approach on NiO-GDC composite materials, which are extensively employed as anodes in intermediate-temperature SOFC. The researchers successfully achieved dense sintering of NiO-GDC at temperatures below 200 \({}^{\circ}\)C by applying an electric field of 50 V/cm and a current density of 260 mA/mm\({}^{2}\). Flash-sintered NiO-GDC exhibited a notable enhancement in electrical conductivity compared to the conventionally sintered NiO-GDC mentioned in previous studies. Additionally, the electrical performance of flash-sintered NiO-GDC was found to be equal to that of conventionally sintered NiO-GDC samples sintered at 1500 \({}^{\circ}\)C. Nevertheless, the scientists stated that the current displayed preferential flow paths inside the samples instead of a uniform distribution, leading to different rates of shrinkage and causing microstructural non-uniformity.
# In-Depth Co-Design of Mental Health Monitoring Technologies by People with Lived Experience
## 3 Results: Problems and Solutions
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Problem** & **Solutions** \\ \hline \hline \multicolumn{3}{c}{Consumers} \\ \hline \(\bullet\) & Consumers often experience a sense of disempowerment when treatment is mandatory. & \(\bullet\) \\  & This can lead to concealment behaviors such as hiding medication and lying about adherence. & \(\bullet\) \\  & Numerous participants reported multiple reasons for non-adherence, however: losing insight due to illness, struggling with memory, concerns about side effects, a lack of perceived or experienced benefits from taking medication and wishing to avoid medication altogether. & \(\bullet\) \\  & & \\ \hline \hline \multicolumn{3}{c}{Carers} \\ \hline \(\bullet\) & Caers found agency particularly challenging to navigate when consumer capacity was low. Seeing a loved one undergoing crisis & \(\bullet\) \\  & Carers reported helping to manage medication—although the “permission” to do so diminished as consumers became more unwell. & \(\bullet\) \\  & & \\ \hline \multicolumn{3}{c}{Consumers and Caers} \\ \hline \(\bullet\) & Some panel members expressed concern that storing medical records, such as the Australian My Health Records (MyHR) database, was an opt-out rather than opt-in arrangement (in other words, the data are collected unless consumers request for them not to be). MyHR is a central public health database that tracks data relevant to each participating citizen’s publicly rebated medical events, such as prescriptions dispensed, and the medical appointments attended. & \(\bullet\) \\ \hline \multicolumn{3}{c}{Implications for digital mental health monitoring services from Table 3} \\ \hline \(\bullet\) & Consumers noted the importance of being able to feel in control of their own account or story. For some, this was about privacy. For others, this was simply about being able to make their own choices regarding how to best care for themselves. & \(\bullet\) \\  & Optimal designs will enable consumers to set their own agenda regarding what is monitored, when that happens, and what that means. & \(\bullet\) \\  & Full transparency appears to be key to successful outcomes. & \(\bullet\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of problems and solutions relevant to agency. These challenges are reviewed in the following section, alongside proposed solutions and implications for digital mental health monitoring services.