esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In recent years, rapid urbanization in the Southern Jiangsu urban area has significantly altered land use patterns, impacting local ecosystem service value (ESV). This study examines land use changes (LUCs) from 2000 to 2020 and assesses ESV changes with the equivalent factor method. The PLUS model is also used to project future LUCs in line with the \"Land and Space Planning of Jiangsu Province (2021-2035)\". The simulation considers scenarios for natural development (NDS), ecological protection (EPS), farmland protection (FPS), and comprehensive development (CDS) for the year 2035. The research findings show that over the past two decades, urbanized areas have persistently grown, whereas there has been a steady decline in the extents of farmland, forested areas, and grasslands. The total ESV has shown a decreasing trend, with the spatial distribution of ESV exhibiting higher values in the eastern regions and lower values in the west. The relationship between land use and ESV is negative, as evidenced by both the comprehensive land use (LA) and the Moran's I index. Scenario predictions reveal that farmland, forest land, and grassland show a decreasing trend under the NDS, while it is the opposite under the EPS. The FPS is predominant in farmland area, and all land types in the CDS comply with national land planning requirements. Overall, the research findings reveal and predict the influence of LUCs on ESV in the study area under four scenarios, which is beneficial optimizing regional resource planning schemes and formulating ecological compensation policies.  
urban agglomeration; land use change; ecosystem services value; multi-scenario simulation; PLUS model +
Footnote †: journal: Applied sciences
## 4 Case Studies
### Algorithm Performance Comparision
#### 4.3.2 The Effect of Heating Network Dynamic Properties on Optimal Operation  
In order to explore the influence of the dynamic characteristics of the heating network on the overall optimization operation of the system, this paper draws the correlation between CHP output, external heat source energy supply and heat load under the condition of neglecting the dynamic characteristics of the heating network and considering the dynamic characteristics of the heating network. Ignore the dynamic characteristics of the heating network, that is, ignore Equations (11), (12), (13), and replace them by the following Equation (45) instead:  
\[T_{k,t}^{\text{in}}=T_{k,t}^{\text{out}} \tag{45}\]  
As shown in Figure 7, under the condition of neglecting the dynamic characteristics of the heating network, the CHP output and the external heat source output are constrained by the heat load, and the output and load are coincident. After considering the dynamic characteristics of the heating network, the CHP output and the heat source output are no longer subject to the heat load. During 5-6 h, 16-22 h, the heat load is higher than the heat output, and the heat load is satisfied by CHP, external heat source and heat storage. In the rest of the time, the heat output is higher than the heat load, so the excess heat energy is stored in the heat network as the heat storage energy.  
It can be seen that after considering the dynamic characteristics of the heating network, it can be used as energy storage to decouple the heat source output and heat load to a certain extent. When the heating cost is low or the renewable energy needs to be consumed, the heating network performs energy storage, and the energy storage is called during the peak of heating, which improves the flexibility of system scheduling.
## 3 Findings
### Diagnostics for Unit Systems
#### 3.2.3 Data Management  
The need for more flexible and efficient data management in manufacturing systems is necessary to secure the maximum productivity for many manufacturing organizations. The systems require precise and current information as ongoing activity to meet users' expectations. For example, information and communication technology take part in a significant role in the factors of Industry 4.0, and data management becomes a major problem for different types of manufacturing systems. The related literature, such as [PERSON] et al. [59], focused on data management that explains the defective data generated by the unsuitable operation of cyber components of a manufacturing cyber-physical system. Similarly, [PERSON] et al. [60] proposed an application of a Digital Twin technology in the manufacturing area to show a significant effect in enabling the manufacturing data management.
## 5 Discussion  
This paper has presented an alternative method, based on fully Cartesian coordinates for the modeling and generation of the shaking force and shaking moment reactions of mechanical systems in general. No angular variables were used at all. Different advantages with respect to previous modeling techniques have been pointed out, such as the ease to be automated and the direct way to get the dynamic reactions in analytical form. It has been also clear that the balancing conditions can be identified directly from the generated mathematical expressions. All these expressions are written in terms solely of the mass and of the local coordinates of the CoM of each body, making the them more clear.  
The application to a 3 RRR PPM is illustrated, and some interesting results have been presented. It is worth to mention that the nonlinear relation between the trajectory of the end-effector and the trajectory of the CoM of the manipulator is clearly shown. The advantages of guiding the CoM to minimize the shaking force are presented in a clear way, and the effects on the shaking moment are pointed out. Finally, the alternative of a mixed technique, combining balancing by redistributing the mass and the kinematic guidance of the end-effector using a proper motion profile, bang-bang in this case, is presented and its advantages are also shown.  
This research will continue for applications in spatial parallel manipulators and mechanical systems in general. Special attention will be paid additionally to the reduction or elimination of the shaking moment, following an alternative techniques different from the redistribution of mass. Kinematic redundancy combined with actuation redundancy could be a promising direction.  
Conceptualization, M.A. and V.A.; methodology M.A.; software M.A. and M.T.O.-G.; validation R.V. and M.T.O.-G.; writing--original draft preparation, M.A.; writing--review and editing, M.A.; funding acquisition, M.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by _Fomento a la Investigacion UP_ 2019 for the project Balanceo Dinamico de Robots.  
The authors declare no conflict of interest.  
Figure 11: Shaking moment comparison: The blue curve is the shaking moment in the original manipulator. The red curve is the shaking moment when the mass of the driving links are redistributed and the tool is guided with a “bang-bang” profile.
# Event-Triggered Robust Fusion Estimation for Multi-Sensor Time-Delay Systems with Packet Drops
## 3 The Robust Fusion Estimation Procedure
\begin{array} []{c}\frac{\partial\bar{C}_{k+1}^{i}(\varepsilon_{k+1})}{\partial\varepsilon _{k+1}}\bar{B}_{2,k}(\varepsilon_{k})\\ \bar{C}_{k+1}^{i}(\varepsilon_{k+1})\frac{\partial\bar{B}_{2,k}(\varepsilon_{ k})}{\partial\varepsilon_{k}j}\end{array} \right],\] \[j=1,2,\cdots,l.\]  
Let \(\mu_{k}^{i}=\frac{1-\gamma_{k}^{i}}{\gamma_{k}^{i}}\). The detailed realization of the robust state estimation algorithm based on sensitivity penalty is given in Algorithm 1. Here \(P_{k|k}^{i}\) and \(\hat{P}_{k|k}^{i}\) are the pseudo-covariance matrices because \(\hat{P}_{k|k}^{i}\
eq\mathbf{E}\Big{\{}\big{(}X_{k}-\hat{X}_{k|k}^{i}\big{)}^{ T}\big{(}X_{k}-\hat{X}_{k|k}^{i}\big{)}\Big{\}}\) and \(P_{k|k}^{i}\
eq\mathbf{E}\Big{\{}\big{(}X_{k}-\hat{X}_{k|k}^{i}\big{)}^{T}\big{(} X_{k}-\hat{X}_{k|k}^{i}\big{)}\Big{\}}\). Based on the event-triggered transmission strategy in the second part, whether each sensor node sends a local state estimate to the fusion center is determined by \(t_{k}^{i}\). The transmission strategy mentioned above can be expressed as  
\[t_{k}^{i}= \begin{cases}0,\left\|\hat{X}_{k|k}^{i}-\hat{X}_{k|k}^{i}\right\|_{ \Omega_{k}^{i}}^{2}\leq\theta^{i},\\ 1,\text{ others }.\end{cases}  \tag{3}\]  
In order to guarantee the transmission rate \(a^{i}\), the vector \(\hat{X}_{k|k}^{i}\), the positive definite weight coefficient matrix \(\Omega_{k}^{i}\), and the positive real numbers \(\theta^{i}\) must be chosen appropriately. \(\hat{X}_{k|k}^{i}\) is the local state estimate. Notice that each local state estimate can be interpreted as a measurement \(y_{k}^{i}\) of the true state \(X_{k}\) collected through the virtual measurement channel defined as  
\[Y_{k}^{i}=\hat{X}_{k|k}^{i}=X_{k}+\big{(}\hat{X}_{k|k}^{i}-X_{k}\big{)} \tag{4}\]  
where the estimation error \(\hat{X}_{k|k}^{i}-X_{k}\) can be regarded as virtual measurement noise. ```
1 Initialization:\(P_{0|0}^{i}=\left( \begin{array}{c}\left(\mathcal{C}_{0}^{i}(0)\right)^{T}\!\left( \mathcal{R}_{0}^{i}\right)^{-1}\!\mathcal{C}_{0}^{i}(0)\\ +\!\left(\mathcal{I}_{0}^{i}\right)^{-1}\end{array}
###### Abstract  
To analyze the rock-breaking characteristics of an arcing-blade cutter in cutting red sandstone, a two-cutter cutting model was established based on the finite element method. Then, the cutting processes of the arcing-blade cutter at penetrations of 2 mm, 4 mm, and 6 mm with different cutter spacings were investigated, and the changing rules of the rock-breaking load, rock crushing state, and rock-breaking efficiency were obtained. Subsequently, the obtained simulation results were validated through linear cutting experiments. The research results showed that, as the penetration of the arcing-blade cutter increased, the rock-breaking load also increased; specifically, under 2 mm penetration, the rock-breaking load remained stable, irrespective of the cutter spacing. However, under 4 mm and 6 mm penetration, the vertical and rolling force increased and then stabilized with an increase in the cutter spacing, while the lateral force decreased and then stabilized, attributed to the synergistic effect between the cutters. At 2 mm penetration, the absence of interaction between the cutting of two cutters in sequence resulted in two separate crushed areas on the rock surface. However, at 4 mm and 6 mm penetration, the rock ridge could be crushed under a smaller cutter spacing. Meanwhile, with an increase in the cutter spacing, the synergistic effect between the cutters diminished, causing the rock ridge between two cuttings to remain uncrushed. The specific energy at the 4 mm and 6 mm penetrations decreased initially with an increase in the cutter spacing, then increased, and eventually stabilized. The optimal cutter spacings at these penetrations were determined as 50 mm and 60 mm, respectively. Conversely, at 2 mm penetration, the specific energy remained almost unchanged with an increase in the cutter spacing, maintaining at a high level and resulting in a low efficiency in cutting rock.  
arcing-blade cutter; red sandstone; penetration; cutter spacing; specific energy acmcopyright
## 5 Modelling Rationale
### Modelling Assumptions
#### 5.3.3 Topology Assumptions  
As we have already explained, we want to evaluate the reliability achievable by TSN and PTRF. Moreover, we want this evaluation to be as general as possible and, thus, we do not model any specific system nor any specific network. Instead, we model the network as a set of streams. Thus, we abstract the network topology away and we only keep in our model those aspects that have a significant impact on the reliability of the stream, e.g., the number of hops that the frames of the stream need to traverse.  
We should recall that in Section 3 we have defined a stream as a virtual communication channel which communicates one talker to one or several listeners. Now, we introduce the concept of virtual path, which communicates the talker of a stream to one of the listeners through a number \(n\) of bridges. Thus, each stream has one virtual path for each listener composed of a talker, a listener and \(n\) bridges. For simplicity, from now on we will refer to virtual paths simply as paths.  
In our models all paths are disjunctive, i.e., the paths do not share any network component. This assumption could be considered optimistic, as it implies that all faults are independent e.g., a fault in an output port of the talker only affects one path of one stream. Nonetheless, we can overcome this limitation by tuning the maximum number of paths that can fail before the stream fails. Thus, we can establish that the failure of one path causes the failure of the whole stream, which is a pessimistic assumption as it means that a fault in one component in one path of a stream affects all the paths of that stream.  
In the future we plan to quantify the reliability of specific network topologies, modifying our models to express their particularities. In any case, such quantification is out of the scope of this article.
## 3 Proposed Method  
In this chapter, we discuss image enhancement of computational integral imaging via reducing the scattering artifact. A computational integral imaging reconstruction (CIIR) method can convert an elemental image array into a series of reconstructed images by adjusting the distance. These reconstructed images can suffer from blurring artifacts at out-of-focus locations. In particular, blurring artifacts from occluding objects can be scattered to the target object in reconstructed images. Thus, the reconstructed images for the target object can suffer from the scattering artifact from occluding objects, especially blurring or color changing. To enhance the reconstructed images, it is necessary to remove scattering artifacts caused by occlusion.  
In the previous chapter, it can be observed that the visibility coefficient \(\alpha\) is the most crucial factor in removing the scattering components of the image. Based on this, this paper presents a novel approach for estimating the visibility coefficient and applies it to the proposed computational integral imaging reconstruction method to improve image quality. The proposed method is depicted in Figure 4.  
First, a reconstructed image is obtained from an EIA using the standard CIIR method. It is then separated into a low-band image and a high-band image using a low-pass filter. The visibility coefficient \(\alpha\) is determined by using the probability density function (PDF) of the high-band image. The histogram of the band image is stretched using the parameter \(\alpha\), and the low and high bands are merged to obtain the enhanced image.  
The process that demands the most computational time in our proposed algorithm is the low-pass filter, because the filter size is very large. Thus, we employ a moving average filter as the low-pass filter. As the size of the filter increases, the computational complexity also increases, so we introduce integral images for fast computation. The integral image [42; 43] is an image that contains the sum of pixels up to the current position in the image. By using an integral image, we can quickly calculate the sum of a rectangular region in an image regardless of its size.
# A Medical Image Segmentation Network with Multi-Scale and Dual-Branch Attention
## 2 Related Work
### Attention Mechanism  
In recent years, attention mechanisms have become prevalent in the field of image processing. These mechanisms increase the attention to important information and minimize the attention to less important details. CCNet [37] utilizes a cross-attention module to calculate attention across various positions of the feature map. DANet [38] integrates spatial attention and channel attention, effectively enhancing the correlation between global features and channels. RA-UNet [39] integrates the attention mechanism and residual networks, enhancing segmentation performance by stacking attention modules. SENet [40] employs squeeze and excitation phases to improve the network's ability to capture image details and boost its representational power. GFANet [41] uses two progressive relational decoders to segment images. In Vision Transformer [33], the concept of multi-head attention is introduced, enabling the model to learn multiple distinct attention weights and focus on different subspaces. This paper proposes a novel attention mechanism that utilizes parallel dual-branch attention to guide the network to focus on the region of interest pay more attention to detail information, reduce the interference of irrelevant information, and improve the accuracy of medical image segmentation.
## 3 Experimental Setup, Materials, and Procedure  
### Experimental Apparatus Setup for EIS (Electrical Impedance Spectroscopy)  
In this experiment, the impedance spectra were acquired using two thin steel electrodes. Several electrode geometries for the measurement of various electrical conductivity of liquids were discussed in [41]. The diameter and length of steel sensors were 1 mm and 150 mm, respectively. Crystallization experiments and the subsequent spectroscopic measurements were carried out in a small-scale laboratory crystallizer with a volume of 0.5 L equipped with a magnetic stirrer. The diameter of the glass vessel was 85 mm. Different concentrations of the fine sucrose (Nordic Sugar, Finland) solutions were prepared in deionized water. Technical grade ethanol (C\({}_{2}\)H\({}_{5}\)OH, purity \(\geq\) 99.5 %), as the antisolvent, was used in different proportions.  
Sixteen standard solutions of sucrose each with a volume of 100 mL and concentrations of 33 % w/w, 44 % w/w, 55 % w/w, and 66.67 % w/w (saturated sucrose solution at 20 \({}^{\circ}\)C) were prepared. As tabulated in Table 1, the amount of ethanol was proportional to water so that the ethanol to water ratio of the solutions remained constant at 0, 0.33, 0.66, and 0.99, respectively. Four different volumes of ethanol equivalents of 0, 33, 66, and 99 g were added to each sucrose solution.  
The addition of the antisolvent to the crystallizer was controlled by a peristaltic syringe pump (Cole-Parmer GmbH) with an accompanying tubing of 2 mm diameter. The addition rate of 5 mL/min and a constant mixing speed of 400 RPM was maintained during the experiments. For each semi-batch operation, a consistent amount of 100 mL solution was taken for the measurement. The effective sucrose to ethanol ratios are shown in Table 1. Figure 3a,b presents a photograph of the experimental setup and the impedance gain, and phase analyser (Hewlett Packard 419 A) used, respectively.  
The overall spectra were recorded for the wideband frequency range of 10 Hz to 1 MHz. This was done in three parts with each part recording 400 equidistant frequency data points. The first part was from 10 Hz to 100 kHz, the second part was from 100 kHz to 300 kHz, and the last part was from  
Figure 2: (**a**) Voltage injected-current detected based electrical resistance tomography (ERT) system schematic; (**b**) finite element method (FEM) mesh created using EIDORS.  
300 kHz to 1 MHz. A total of 1200 data points were acquired for every solution. In order to increase the reliability and repeatability of the results, each experiment was repeated for a total of 5 times and averaged values were used for further post-processing.
## 4 Analysis of Effect Factors
### Effect of the Strength of Block-Matrix Interface  
As the weakest zone connecting rock blocks and matrix, the BMI plays an indispensable role in directly affecting the strength of the SRMs. Nevertheless, it is challenging to identify the strength parameters of the BMI and manage its strength in laboratory experiments due to the tiny size of the cementing surface. Therefore, this paper assigns different strength parameters to BMI to simulate the effect of its strength on the uniaxial compressive strength of the SRMs from the perspective of numerical simulation. In the traditional numerical simulation of concrete, the different ratio value of the strength between the interface transition zone and mortar were applied [34]. Therefore, the ratio of strength parameters between the BMI and matrix was also adopted in this paper to simulate different BMI strengths.  
As presented in Figure 10, with different ratio values of 10%, 20%, 30%, and 40%, the UCS of the SRM is compared. In general, all four groups of models satisfy the above-mentioned law of the effect of VBP on strength (i.e., the higher the volume fraction the lower the strength). Meanwhile, as we can observe that the lower the strength of the cemented surface, the lower the UCS of the SRM at the corresponding volume fraction.  
Figure 9: Comparison chart of simulation results and empirical prediction methods.  
From each set of results, the decreasing trend in the UCS in this group of models tends to level off as the strength of the cemented surface increases.
## 4 Discussion of the Results
The reason for the increase in compressive strength with a decrease in aggregate size in the RFC is that the smaller aggregate sizes are more evenly distributed and form a relatively dense fine structure, in the condition of the same percentage of aggregates. When an external load is applied, the smaller the aggregate size is, the stronger the overall deformation coordination ability of the stressed section of the specimen will be, which slows down the specimen damage caused by stress concentration. Regarding the physical experiments, the compressive strength of the RFC with aggregate size of 150 mm was higher than that of the RFC with aggregate sizes of 75 mm and 50 mm. This was because during the process of aggregate stacking, simple cubic stacking could only be formed by relying on the side support of the mold, which was different from the stable rockfill body in actual engineering (which does not require template support). Additionally, during the casting of SCC, no thick protective layer was set on the edge of the spherical aggregates. During the loading process, the SCC at the corners of the RFC with 150 mm aggregate size was prone to failure first, and then the aggregates bore the main load, resulting in a higher strength. For RFC with aggregate sizes of 75 mm and 50 mm, surface cracks occurred during the loading process, causing the position of the aggregates to shift, and then some spherical aggregates were squeezed out, which led to the instability of the load transfer skeleton and a lower compressive strength. In the subsequent study of how aggregate size affects the mechanical properties of RFC, the thickness of the protective layer on the edge of the aggregates could be increased to prevent the aforementioned phenomena.