esa-sceva/satcom-chunk-collection huggingface dataset:
# Spatial Distribution and Monitoring of Land Subsidence Using Sentinel-1 SAR Data in Java, Indonesia
## 4 Discussion
### Spatial Changes in Land Subsidence  
In the greater area of Semarang, the spatial distribution of LS has changed since the first study was conducted. Observations between 2006 and 2011 indicate that the LS rate in this particular area was insignificant [5]. Another notable change is the eastward expansion of the LS area, extending further into Demak Regency. The LS area has expanded by more than 500 km\({}^{2}\) to the east compared to data observed in 2007 [5].  
Another significant spatial change in LS has also been observed in the Bandung area. The maximum rate of LS has shifted from the industrial area in the western side of Bandung  
\begin{table}
\begin{tabular}{c c c} \hline
**Aspect** & **Impacts** & **Reference(s)** \\ \hline Social & shift in land use to poorer activities & [59] \\  & health problems due o declining water quality & [60] \\  & low adaptation ability to climate change & [61; 62] \\  & loss of livelihood & [61; 63] \\ \hline Economy & higher costs to produce good and clean water & [59; 60; 64] \\ \hline Physical & damage to buildings & [65] \\  & loss of high-value transitional areas & [60; 66] \\  & decrease in agricultural land & [37] \\  & degradation of drainage system & [12; 67] \\ \hline Environmental & geological-related damage, such as change in both \\  & ground- and underground water flow \\  & groundwater storage loss & [4; 69] \\  & expansion of flood-prone areas & [70; 71] \\  & coastal flood and land loss & [2; 71] \\ \hline \end{tabular}
\end{table}
Table 1: Impact of LS, especially on Java Island.  
City to the southern part, from 60 mm /year to 150 mm /year. However, the LS rate in several industrial areas in Bandung, such as Majalaya and Banjaran, has remained unchanged since 2006. Recently, residential areas in Bandung have been facing a substantially higher LS rate compared to 20 years ago, and the rate is now potentially comparable to that in industrial areas [74].  
In Cirebon, the LS phenomenon did not exist 10 years ago. Rapid infrastructure development in accordance with groundwater exploitation in Cirebon City may instigate LS in the region. A single oval-shaped area in Cirebon and Cianjur suggests that the causes may originate from several adjacent sources. Moreover, LS detected in this study along the Cirebon shoreline may also contribute to the rapid abrasion of the city's shoreline [75].
# A Novel GBSM for Non-Stationary V2V Channels Allowing 3D Velocity Variations
## 1 Introduction  
Vehicle-to-vehicle (V2V) communication is the most important development of the modern intelligent transportation systems (ITSs), which are more accurate and realistic. As a result of sharing information among the vehicles, infrastructures, and other devices, it has gained an enormous interest lately because of its great ability to sustain intelligent transportation [1; 2]. In recent years, V2V communication systems have shown key potentiality with the help of the fifth-generation (5G) and beyond 5G (B5G), along with the future sixth-generation (6G) technologies [3; 4]. Because of the traffic efficiency and security-relevant cases, V2V communication helps to improve the safety of lives and resources by sharing information in real time under sophisticated transportation [5; 6; 7; 8]. However, the ability and credibility of V2V communications are impacted by crowded space, vehicles, movements of scatterers, etc. [9; 10]. Furthermore, the motions of both terminals and scatterers result in the time-variant feature of the platform, which differentiates V2V channels from conventional fixed-to-mobile (F2M) channels [11; 12; 13]. Thus, a realistic, precise, and easy channel model is needed.
## 4 Conclusions  
Due to the advances in technologies applied to geosciences, the InSAR method has gained an important role in research in the field of earthquake deformations. Therefore, we presented a spatial-temporal distribution of deformations and trends of deformation during the 2017 year, which was derived from 12 Sentinel-1B images using the InSAR method. On the other hand, the seismic activity was analyzed, and the geoinformation obtained from the InSAR analysis was corroborated with the daily seismic records. Based on the results, the following was found:  
(1) The central coast of Chile is characterized by seismic events of micro, minor, and slight magnitudes with a prevalence of 93.03% for the study period. Based on kernel analysis, the coastal zone is identified as having a high density of daily earthquakes, located from the bay of Arauco to the ocean.  
(2) Monthly deformation maps were developed for 10 municipalities on the coast of the Biobio region in Central Chile. The data corroborated with daily earthquakes and proximity to fault zones show deformation for all months, highlighting the month of May, with the highest range of displacement (40 and \(-\)24 mm/year). July also recorded the same seismic magnitude, but the range of displacement is smaller than May month, which may be related to the location of the epicenter offshore or the radar perception.  
(3) The coastal zone presented a slight upward deformation tendency in the north and northeast zone (i.e., \(\deltaup\) -3 mm/year), while the south and southwest zone presented a more accentuated upward trend (i.e., \(\deltaup\) -24 mm/year). The municipalities of Lota, Arauco, and Lebu have a greater tendency of deformation.  
Future research will include more radar images with an extension of the analysis period and at the same time corroborate with other techniques, such as the GNSS.  
Conceptualization, L.d.D.J.d.S., L.R.-L., L.G.-R., H.M.C. and M.L.A.: methodology, L.d.D.J.d.S.; software, L.d.D.J.d.S., L.M.C.S., H.M.C. and L.G.-R.; validation, L.d.D.J.d.S.; formal analysis, L.d.D.J.d.S. and M.L.A.: investigation, L.d.D.J.d.S. and M.L.A.: resources, M.I.A.A.; data curation, L.d.D.J.d.S., M.L.A. and H.M.C.; writing--original draft preparation, L.d.D.J.d.S., L.R.-L. and L.G.-R.; writing--review and editing, M.I.A.A. and H.M.C.; visualization, M.I.A.A.; supervision, M.I.A.A.; project administration, M.I.A.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Universidad de Concepcion, Chile.  
Not applicable.  
The authors thank the Kultrum Project-Astronomy Department and Urban Planning Department from the University of Concepcion, Chile to support this research. L.R.-L. thanks to project VRDFAl21/10 of the Universidad San Sebastian and to the CRHIAM Water Center (Project ANID/FONDAP/15130015).  
The authors declare no conflict of interest.
## 1 Introduction
### Wear Measurement Methods
#### 1.6.6 Microscopic Inspection  
Microscopy can be used to observe various wear mechanisms in steel from which TBM disc cutters are made on a microscopic level. Four different micromechanisms can be observed in the predominant wear mechanism (abrasion): microchipping, microplowing, microfatigue, and microfractures [29]. This optical technique enables the visualization of wear patterns and the identification of specific wear mechanisms on a microscopic level. This method is the only one of the abovementioned methods that requires the extraction and preparation of a cross-sectional metallographic sample of the worn disc cutter.  
Microscopy techniques have been used in several studies to investigate the wear of disc cutters. For example, [PERSON] et al. [58], [PERSON] et al. [29], and [PERSON] et al. [59] carried out a microscopic inspection of the surface of a worn disc cutter to analyze wear characteristics and patterns. [PERSON] et al. [58] investigated the influence of corrosion on the abrasive wear of TBM cutter steel in interactions with excavation fluids such as soil conditioners, anti-abrasion additives, and water. They used a scanning electron microscope (SEM; Hitachi S-3400) to study the microstructure of the steel and to examine the topography of the worn material surfaces after the test. [PERSON] et al. [29] used a scanning electron microscope (SEM) to visualize and analyze wear mechanisms on a microscopic level, focusing on microchipping, microplowing, microfatigue, and microfracture. An SEM was used to examine the surface of a hot-work tool steel and metal matrix composite (MMC) material to understand how the microstructure and hard phases of the materials affect the wear resistance of TBM disc cutters, chisel tools, reamer tools, and ripper tools. [PERSON] et al. [59] used a focused ion beam (FIB) microscope to cut precise cross-sections from the worn TBM cutter ring samples and mini cutter ring samples without exposing them to air. This method ensured that the samples remained in a controlled environment during the cutting process. The FIB microscope also enabled simultaneous imaging in which the samples were analyzed using a Zeiss Ultra 55 Limited Edition SEM. This comprehensive approach allowed the researchers to examine the microstructure of the samples in detail and gain insight into the mechanisms of cutter ring wear during hard rock tunneling.  
Although microscopic observations provide valuable insights into wear mechanisms and material behavior on a small scale, they can also have limitations, such as the need for specialized equipment, time-consuming sample preparation, and potential challenges in interpreting complex interactions at the microstructural level.
# A Review of Regional and Global Gridded Forest Biomass Datasets
## 3 Current Gridded Forest Biomass Maps
### High-Resolution AGB Maps from Field Measurements and LiDAR Data
#### 3.3.2 Aboveground Biomass for Penobscot Experimental Forest, Maine, 2012  
[PERSON] et al. [79] combined field inventory data from the Penobscot Experimental Forest in Maine and airborne LiDAR data acquired from a Hyperspectral & Thermal Imager using a space-varying coefficients model, and provided biomass for the Forest in 2012, with a spatial resolution of 13 m. The modelling approach accommodated temporal misalignment between field measurements and remotely sensed data by including multiple time-indexed measurements at plot locations to estimate changes in AGB [80].
## 2 Rigid-Flexible Model for Spacecraft with Hoop-Truss Antenna
\begin{array}{l}\mathbf{M}_{b}\mathbf{A}_{av}\mathbf{a}_{1}-\mathbf{S}_{b} \mathbf{A}_{ab}\dot{\omega}-\left(\mathbf{A}_{ab}\omega\right)^{X}\mathbf{S}_ {b}\mathbf{A}_{ab}\dot{\omega}+\mathbf{M}_{a}\mathbf{A}_{av}\mathbf{a}_{1}\\ +\mathbf{M}_{a}\mathbf{P}_{a}\ddot{\mathbf{\eta}}_{a}-\mathbf{S}_{a}\dot{ \omega}_{a}-\mathbf{S}_{ba}\mathbf{A}_{ab}\dot{\omega}-\left(\mathbf{A}_{ab} \omega\right)^{X}\mathbf{S}_{ba}\mathbf{A}_{ab}\omega=\mathbf{F}\end{array}  \tag{11}\]  
where  
\[ \begin{array}{l}\mathbf{S}_{b}=\sum\limits_{B}\mathbf{r}_{k}^{X}m_{k},\, \mathbf{I}_{b}=\sum\limits_{B}\mathbf{r}_{i}^{X}m_{k}\mathbf{r}_{i}^{X},\, \mathbf{H}_{ab}=\sum\limits_{A}m_{j}\mathbf{r}_{3}^{X}+\mathbf{H}_{b},\, \mathbf{H}_{b}=\sum\limits_{A}m_{j}\mathbf{A}_{ba}\left(\mathbf{r}_{j}^{X}+ \mathbf{u}_{j}^{X}\right)\mathbf{A}_{ab},\\ \mathbf{S}_{a}^{b}=\sum\limits_{A}m_{j}\mathbf{A}_{ba}\mathbf{r}_{j}^{X} \mathbf{A}_{ab},\,\mathbf{I}_{b}^{ab}=\sum\limits_{A}m_{j}\mathbf{r}_{3}^{X} \mathbf{A}_{ab}\mathbf{r}_{j}^{X}\mathbf{A}_{ab},\,\mathbf{I}^{ab}=\sum\limits _{A}m_{j}\left(\mathbf{A}_{ba}\mathbf{r}_{j}^{X}\mathbf{A}_{ab}\right)\left( \mathbf{A}_{ba}\mathbf{r}_{j}^{X}\mathbf{A}_{ab}\right),\\ \mathbf{I}_{ab}^{b}=\sum\limits_{A}m_{j}\left[\mathbf{r}_{3}^{X}\mathbf{A}_{ba }\left(\mathbf{r}_{3}^{X}+\mathbf{r}_{k}^{X}\right)\mathbf{A}_{ab}+\mathbf{A}_{ ba}\left(\mathbf{r}_{3}^{X}+\mathbf{r}_{k}^{X}\right)\mathbf{A}_{ab}\mathbf{A}_{ba} \left(\mathbf{r}_{j}^{X}+\mathbf{u}_{j}^{X}\right)\mathbf{A}_{ab}\right],\\ \mathbf{P}_{a}=\sum\limits_{A}m_{j}\mathbf{Q}_{i},\,\mathbf{S}_{a}=\sum\limits_ {A}m_{j}\mathbf{r}_{j}^{X},\,\mathbf{S}_{ba}=\sum\limits_{A}m_{j}\left[ \mathbf{A}_{ab}\mathbf{r}_{3}^{X}\mathbf{A}_{ba}+\mathbf{r}_{j}^{X}\right], \,\mathbf{I}_{\omega}=\sum\limits_{B}m_{k}\mathbf{r}_{k}^{X}\omega^{X} \mathbf{r}_{k}^{X},\\ \mathbf{I}_{\Omega ab}^{b}=\sum\limits_{A}m_{j}\left[\mathbf{r}_{3}^{X}+\mathbf{ A}_{ba}\left(\mathbf{r}_{j}^{X}+\mathbf{u}_{j}^{X}\right)\mathbf{A}_{ab}\right] \omega^{X}\left[\mathbf{r}_{3}^{X}+\mathbf{A}_{ba}\mathbf{r}_{j}^{X}\mathbf{ A}_{ab}\right],\end{array}  \tag{12}\]  
Equations (10) and (11) are the coupled equations of motion for the whole system that includes the antenna's vibration, the satellite's attitude motion, and the satellite's orbital motion. It is clear that the attitude motion will be affected by the thermal-induced vibration.
# Porous Electrodeposited Cu as a Potential Electrode for Electrochemical Reduction Reactions of CO2
###### Abstract  
In the present study, a systematic investigation is performed to assess the relationship between electroplating parameters, pore morphology and internal surface area of copper deposits which are promising to serve as electrodes for electrochemical reduction reactions of carbon dioxide (CO2). A set of porous copper deposits are fabricated with the dynamic hydrogen bubble template method. The microstructural and Brunauer-Emmett-Teller (BET) analysis demonstrate that current density, deposition time, and bath composition control pore size, strut size, and hence surface area which could be as high as 20 m\({}^{2}\)/g. Selected sets of porous copper electrodes are then employed in the electrochemical reduction reaction test to determine their conversion performance in comparison to a monolithic copper surface. From the gas chromatography (GC) and nuclear magnetic resonance (NMR) analysis, porous copper is shown to provide higher rates of production of some important chemicals, as compared to copper foil electrodes. Porous copper with fern-like morphology serves as a promising electrode that yields relatively high amounts of acetaldehyde, acetate and ethanol. The study thus presents the opportunities to enhance the electrochemical reduction reaction of CO2 through microstructural engineering of the copper surface, which benefits both CO2 reduction and generation of chemical products of high value.  
Keywords:porous copper; electrochemical CO2 reduction; catalyst; surface microstructure +
Footnote †: journal: Applied Sciences
# Effect of Soil Reinforcement on Tunnel Deformation as a Result of Stress Relief
###### Abstract  
Adjacent geotechnical engineering activities, such as deep excavation, may adversely affect or even damage adjacent tunnels. Ground reinforcement before excavation may be an effective approach to reduce tunnel heave as a result of stress relief. However, there are few quantitative studies on the effect of soil reinforcement on tunnel deformation. Moreover, the reinforcement mechanism of the reinforced soil and the reinforcement depth are not fully understood. In order to investigate the effect of reinforcing the ground on the tunnel response, a finite element analysis was conducted based on a previously reported centrifugal model test with no ground reinforcement. The effect of the Young's modulus and depth of the reinforced soil on tunnel deformation was analyzed. Soil stresses around the tunnel were also considered to explain the tunnel response. The results revealed that the Young's modulus of the reinforced soil and the reinforcement depth had a significant impact on tunnel deformation as a result of basement excavation. The tunnel heave in the longitudinal direction decreased by 18% and 27% for modulus of the reinforced soil, five times and ten times higher than that of the non-reinforced soil, respectively. The reinforcement depth was effective with regard to controlling the tunnel heave caused by stress relief. This is because the reinforced soil blocked the stress transfer and thus reduced the tunnel heave caused by excavation unloading. It is expected that this study will be useful with regard to taking effective measures and ensuring the safety and serviceability of existing metro tunnels during adjacent excavation.  
basement bottom reinforcement; reinforcement depth; Young's modulus of reinforced soil; tunnel heave; numerical analysis Article
# The Role of an Industrial Alkaline Wastewater in the Alkali Activation of Biomass Fly Ash
## 2 Materials and Methods  
### Materials  
Biomass fly ash (FA) from a Portuguese pulp and paper factory (kraft process) and metakaolin (MK) from Univar, ArgicalTM M1200S, were used as precursors. FA has a much coarser particle-size distribution compared with the commercial precursor (MK), the mean particle size being 59 \(\upmu\)m for FA and 5 \(\upmu\)m for MK (see details in [26]). As commercial activators, sodium silicate D40 from Quimiamel (SiO\({}_{2}\)/Na\({}_{2}\)O = 3.1, H\({}_{2}\)O = 62.1 wt.%) and a solution of 10 M NaOH made from ERCROS reagent (99%) were used. An alkaline effluent (pH-11) from the same pulp and paper plant collected at the bleaching stage was used to partially replace the NaOH in the activator solution.  
The biomass fly ash and the metakaolin were characterised by X-ray fluorescence (XRF) with a Philips X'Pert PRO MPD spectrometer. The effluent Na content was obtained by atomic emission (GBC 904 AA with pc control, GBC Avanta AAS Version 2.0). The chemical composition of the industrial wastewater was evaluated by inductively coupled plasma (ICP, Thermo Scientific iCAP 7000 Series, from Horiba Jobin Yvon, model Activa M from Longjumeau, France).
# Space Charge Accumulation and Decay in Dielectric Materials with Dual Discrete Traps
## 3 Bipolar Charge Transport Model  
In dielectric materials subjected to voltages, the injected charges will not only be captured by trapping centers, but also migrate in the shallow traps [1]. We will utilize the bipolar charge transport (BCT) model to investigate the space charge dynamics in the dielectric materials with two discrete traps. We consider a system consisting of a dielectric material with the thickness of \(L\) clamped by two electrodes. A one-dimensional coordinate, \(x\), is set up for the sample. \(X=0\) corresponds to the interface between the material and cathode, and \(x=L\) corresponds to the interface between the material and anode. The schematic of the BCT model of dielectric materials subjected to electric fields is shown in Figure 4.  
Figure 4: Schematic of bipolar charge transport model of dielectric materials containing two discrete traps. Here \(E_{Tk1}\) and \(E_{Tk2}\) are the two discrete deep traps of electrons, while \(E_{Th1}\) and \(E_{Th2}\) are the two discrete deep traps of holes.
## 2 Related Technologies
### Physical Unclonable Technology  
Physical Unclonable Function (PUF) is a security technology that utilizes inherent changes in hardware to generate an unclonable unique response [21]. Similar to human biometrics, PUFs can be employed for the unique identification of each integrated circuit chip. Each IC has different physical variations in path delay, transistor threshold voltage, and voltage gain owing to differences in silicon processing technology. In this system, each  
Figure 1: Blockchain structure diagram.  
IoT device integrates a PUF, which is adopted to generate the public identity of the device as a public key, realize message encryption, and achieve secure transmission through the PUF-based IoT security communication protocol. The system realizes the secure transmission of device IDs mainly via PUF technology to upload nodes and verification nodes. PUF technology can be used for the generation and storage of encryption keys because the keys generated by PUF technology are unique and cannot be copied, which noticeably enhances the security of the keys.  
In this paper, a PUF is integrated into each IoT device; a public identifier is generated for each device using PUF technology and used as the public key of the device for message encryption; then, the PUF-based IoT security communication protocol realizes safe transmission. In this system, the PUF is mainly employed to securely transmit the device ID to the upload node and the verification node.
## 3 Results and Discussion
### Experimental Results  
#### 3.2.1 Verification of Theoretical Models of Multiple Parallel Jets  
Equations (8)-(13) were substituted into Equation (7) to obtain \(V_{1}\)-\(V_{6}\). In the fully developed jet zone, seven or eight typical measurement points were selected from the experimental data and compared with the results predicted by the theoretical model, as shown in Figure 8. The velocity predicted by the theoretical models was greater than the measured velocity, except \(V_{2}\) predicted by the [PERSON] theoretical model, which was lower than the measured data. Of the theoretical models, \(V_{5}\) had the largest deviation. However, the variation trend of \(V_{5}\) was consistent with the measured data. With a continuous increase in the outflow distance of the jet, the central velocity of the jet gradually decreased. Comparing the results, it was found that the axial velocity attenuation of \(V_{3}\) was  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Turbulence Model** & **RMSE for Temperature** & **RMSE for Velocity** \\ \hline SKE & 0.72 & 0.107 \\ RNG & 0.81 & 0.142 \\ SST & 0.86 & 0.326 \\ \hline \hline \end{tabular}
\end{table}
Table 6: RMSE of velocities and temperatures in different turbulence models.  
Figure 7: Comparison of different turbulence models and experiments: (**a**) air temperature of Line 1; (**b**) air temperature of Line 4; (**c**) air velocity of Line 1; (**d**) air velocity of Line 4.  
closest to the measured data for the three cases; the prediction curve fit the best of the six theoretical models. The RMSE between the measured data and the value of \(V_{3}\) in the three cases was 0.23 m/s, 0.09 m/s, and 0.18 m/s, respectively. Thus, the modified Abramovich formula was the most suitable for attenuation of the axial velocity of multiple parallel jets in SV rooms.
# Soft Periodic Convolutional Recurrent Network for Spatiotemporal Climate Forecast
## 6 Discussion  
First, a clear outcome of this study is that SP-CRN-1 (1,1,0) prediction results of ZH300 and SST are the best among the PRD-1. Considering only nearby one month of PRD-1 can indicate that the phase shifts of periodicity have occurred in the range of one month. During a season (a term of three months), climate variables may have a similar changing tendency. In addition, for ZH300 (Figure 7), plus-1 and self show obvious opposite relationship, while for SST (Figure 11), plus-1 and minus-1 indicate opposite relationship, which may reflect the time-scale of persistence of each change. Second, the SP-CRN-2 (0,4,0), which considers the prior periodic cycle of four years, turns out the best prediction accuracy in PRD-2 of ZH300, and the drastic accuracy improvement when considering for more than four years of SST. Quasi-biennial and ENSO time-scale variations [54] are a possible cause of the four year periodic cycle that is occurred in SP-CRN-2 results.  
Meanwhile, our proposed SP-CRN model has some limitations to consider. First, depending on the property of climate variable, we need to find the best combination of PRD type and its parameter. Second, this study considers the monthly data as the time resolution and the spatial input size of the Northern Hemisphere and the entire globe for the global scale forecasting. If we want the higher time resolution, the larger size in PRD (e.g., array size of 365 for daily data) is needed that consumes the computational and memory resources. Third, it is possible to extend the SP-CRN to multi-scale periodicity as the original Periodic-CRN does (i.e., daily and weekly). However, multi-scale such as daily and yearly periodicity causes huge PRD as well. Therefore, some embedding on PRD to low dimension is needed.