esa-sceva/satcom-chunk-collection huggingface dataset:
# Needle Segmentation in Volumetric Optical Coherence Tomography Images for Ophthalmic Microsurgery
## 2 Method
### Morphological Features Based Method  
Due to the fact that most of the needle parts in each B-scan are located outside the tissue creating shadows, a morphological feature based method is proposed. The B-scan gray image is transformed into a binary image by thresholding the OCT images. The threshold value is adaptively defined based on statistical measurements of each B-scan. This simple and effective method has been used and evaluated in the automatic segmentation of structures for OCT images [24]. Moreover, a median filter is applied for eliminating the noise. Furthermore, the topmost surface is segmented and considered as the tissue surface. By scanning from left to right, any vertical jump or drop in this surface layer is detected and considered as the beginning and the end of an instrument reflection, respectively. To avoid the misdetection of anatomical features of the eye tissue as a reflection caused by the needle, only reflections with invisible intra-tissue structures are confirmed to be needle reflections. A bounding box is used to cover the region of detected needle part, see Figure 2b-e, and the width of bounding box reflects the width of needle cross-section which can be used to analyze the diameter of the needle. In consideration of the situation for several needle tip parts, the bounding boxes in one B-scan image, whose distance between any two of them is less than a threshold \(d_{b}\), can be merged into one bounding box. The needle refraction fragment will be then removed from the detected results since it is not the real needle position. Removal operation will be performed when either of the conditions is satisfied: (1) the top edge of the needle fragment bounding box is closed to the upper edge of the image; (2) the number of needle pixels is more than a threshold. Here, in the MF method, features are obtained by observation and summarization of the needle patterns in the B-scan image. Some of the parameters are manually decided which may influence the accuracy of segmentation. In the next section, we will introduce another method that can learn the features by itself with the training dataset.  
Figure 3: The different patterns of needle seen in OCT B-scan (The needle fragments are labeled with yellow bounding box). Form (**a**) is the needle tip without clear shadow. Since this part of the object is too small, the result of light diffraction leads to unclear shadow on the background. (**b**) shows the needle tip with clear shadow. In this form the needle is downwards-beveled that can be seen as a single fragment piece in the OCT B-scan. In form (**c**) the needle body has clear shadow. In forms (**d**,**e**) several needle tip fragments with clear shadows can be seen here the needle is upwards-beveled; (**f**) shows the needle refraction fragment in this form the needle is out of OCT image range with a clear refraction in B-scan image.
## 4 Results of The Analysis
### Spatial Configuration Analysis Results
#### 4.2.2 Neighborhood-Level Analysis Results
As shown in Figure 4b,c, the analysis found that nodes on two north-south axes (axes 1 and 2) passing through all of the modern, traditional, and buffer areas in the district containing the market and its vicinity, had shallow spatial depth values, which indicates high integration. Axis 3, with a high degree of integration, was what was once inside the fortress wall, which had north, south, west and east gates; this was once a major road that passed between the north and south gates. Another north-south axis (axis 4) consisting of nodes with high integration at the district's boundary was parallel to axes 1, 2 and 3, and formed along the main road on which public transit operated. There are bus stops along the axis, and the bus stop in front of Yukgeori Market diverges into many bus routes that allow access to all of the areas of the city. Therefore, the public could easily access the axis. Of the four north-south axes, two (axes 1 and 3) intersected with the four east-west axes (axes 5 through 8) consisting of highly integrated nodes. The results indicated that of the four east-west axes, two (axes 5 and 6) form a strong centrality around Cheongju Central Park and a large outdoor parking lot. Axis 7, consisting of highly integrated nodes in the buffer area, included Hanbok Culture Street, where stores sell _hanbok_, the traditional clothing of Korea, and related products (Figure 4a-4). Furthermore, axis 8, also consisting of highly integrated nodes near Yukgeori Market, included the Cheongju Furniture Street, where many furniture stores were agglomerated (Figure 4a-5). These eight axes have a web-shaped spatial configuration, which, according to the space syntax analysis, has a high degree of integration and illustrates a high public level. Therefore, the configuration was interpreted as a spatial structure that can attract many visitors to the traditional market and the highly modernized commercial area. The four north-south axes (axes 1 to 4) were visualized as a spatial configuration that connects the highly modernized sector and the traditional market sector, while the three east-west axes (axes 6 to 8) in the buffer area were visualized as the configuration that separates the two areas. Table 5 presents a comprehensive summary of the spatial network configuration and land-use pattern supported by such configuration at the neighborhood level within the district that includes Yukgeori Market and its vicinity. The land-use pattern was mainly investigated in terms of the eight axes of the district's street network, with relatively high integration. Thereby, it was possible to identify the factors influencing the revitalization of the traditional market by analyzing the characteristics of the land-use patterns and their relationships within the network.
## 1 Introduction
The temperature-dependent elastic and damping parameters were estimated by a genetic algorithm-based parameter identification scheme for different sets of modal contribution. The study found that both the elastic and damping properties of the carbon-epoxy composites vary significantly with temperature. This information is vital for designing and optimizing composite structures for specific thermal conditions  
This paper describes an extended IET procedure with automated excitation for continuous identification of engineering constants across different temperatures, aiming to make the process straightforward and cost effective. The major cost is the climate chamber, which, in many laboratories, is already available for other scientific experiments. The Resonalyser procedure was used for the identification of the complex engineering constants at each temperature step. The next paragraphs describe first the theory and background of the Resonalyser procedure. Next, the automated excitation procedure and execution in a climate chamber are highlighted. At the end of this paper, an example is given of the identification of a bidirectionally glass-fiber-reinforced thermoplastic PA6/Organo composite sample between \(-20\)\({}^{\circ}\)C and \(60\)\({}^{\circ}\)C.
# Review of Structural Health Monitoring Techniques in Pipeline and Wind Turbine Industries
## 3 Health Monitoring in Corrosion
### Conventional Corrosion Sensors
#### 3.1.3 Electrochemical Sensors  
The electrochemical characteristics of corrosion are elevated with the help of electrochemical sensors, which make use of techniques such as galvanic current measurement, linear polarization resistance (LPR), electrochemical impedance spectroscopy (EIS), and electrochemical noise (EN) [10; 67; 69; 70; 71]. Electrochemical sensors are fairly advantageous; they can include the measured corrosion rates, and they also have the ability to investigate the mechanism responsible for the resultant corrosion. There are a myriad of electrochem  
Figure 2: The different types of corrosion coupons installed inside the structure.  
ical techniques, but the LPR-based corrosion technique has been used as a commercial method, since it is simple to operate, and the interpretation of data here is easier as compared to other methods. In most LPR-based investigations (Figure 3) [72], the traditional concept of having of having a three-electrode system is not followed. Rather, the electrodes are made from the same material. In the case of electrochemical sensors, the disadvantage lies in the fact that because of external potential, the corrosion rates can go up. Thus, in order to avoid this, it is necessary that parameters such as overpotential, scan rate, and Tafel slopes are chosen with accurately. There is an additional requirement of an electrolyte that is ionically conducting, making them unfriendly for usage in a non-conductive environment. There is an electrochemical corrosion sensor that can operate even at a temperature of 300 \({}^{\circ}\)C and at a pressure of 5000 psi. This sensor makes use of the galvanic current in a coupled multi-electrode array [73, 74] (Figure 3) [75] to detect the localized corrosion. With the help of an Advanced Electrochemical Sensor (AES), the amount of water and the rate of corrosion in simulated natural gas were measured (Figure 3) [76, 77].
## 2 Graph Based Critical Sensor Assessment
### Figure 1  
The colours attributed to each node represent the optimal floor exit, e.g., nodes coloured in blue will see their occupants exit through the N-E stairs. The red Diamond shows the fire location, the stars show the building exits. (**a**) shows the reference map when there is no fire; (**b**) illustrates a fire outbreak at a non-critical area--causing very little changes compared with the reference map; (**c**) illustrates a fire outbreak at a critical area--highlighted by the profound changes compared with the reference map.  
Figure 1: The colours attributed to each node represent the optimal floor exit, e.g., nodes coloured in blue will see their occupants exit through the N-E stairs. The red Diamond shows the fire location, the stars show the building exits. (**a**) shows the reference map when there is no fire; (**b**) illustrates a fire outbreak at a non-critical area—causing very little changes compared with the reference map; (**c**) illustrates a fire outbreak at a critical area—highlighted by the profound changes compared with the reference map.  
**Algorithm 2--Determining the Busiest Nodes During an Evacuation**  
Another definition of a critical node would consider the most used or congested locations during an evacuation as being the most critical. This algorithm iterates through every possible departure point in the graph and increments the ranking metric of each location visited along the shortest exit path. Figure 2 is a graphical representation of its output.  
Algorithm 1's top-ranking nodes are scattered across the building, covering corridor intersections or \"bottlenecks\" such as staircases, and locations near the exits also achieve a high rank. Algorithm 2's top-ranking nodes are mostly found in the vicinity of exits since the collection of all egress paths form trees rooted at each exit, and the most visited locations are at the trunk of each tree. Overall, the top five locations selected by each algorithm are almost completely different; however, as the sample size is increased, the degree of overlap between sets increases: there is only 1 location shared between both sets for the top 5 most critical nodes, whereas the top 10 and top 20 overlap by respectively 4 and 14 locations.
# Unusual Animal Behavior as a Possible Candidate of Earthquake Prediction
## 5 Our Latest Result for a Particular Tokyo EQ on 7 October 2021
### Monitoring Stations of Diary Cows' Milk Yields and Observational Results  
#### 5.2.1 Monitoring Stations  
The EPRC (Earthquake Prediction Research Center, Tokyo, Japan) has been continuing the monitoring of dairy cows' milk yields in the farms at several stations in and around the Tokyo district with the help of ORION Machinery Co., Ltd. (Nagano, Japan). All the farms featured a free stall barn with one-way traffic automatic milking systems ([PERSON], GEA Farm Technologies, Dusseldorf, Germany). Individual milk yields automatically recorded at each milking of all lactating cows using DairyPlan C21 (GEA Farm Technologies, Dusseldorf,  
Figure 1: Locations of the epicenter of the 7 October 2021 Tokyo EQ (indicated by EQ), and four monitoring stations of dairy cows’ milk yields in the Chiba Prefecture (indicated by red circles) (Chiba-shi (city), Asahi, Isumi, and Minami-boso stations).  
Germany) were used for our analysis. Figure 1 illustrates the positions of several monitoring stations used in this paper by red circles, which are all located in the Chiba prefecture. In the order of decreasing latitude: (1) Asahi (geographic coordinates: 35.74\({}^{\circ}\) N, 140.70\({}^{\circ}\) E), (2) Chiba-shi (city) (35.52\({}^{\circ}\) N, 140.24\({}^{\circ}\) E), (3) Isumi (35.20\({}^{\circ}\) N, 140.33\({}^{\circ}\) E), and (4) Minamisboso (35.03\({}^{\circ}\) N, 139.98\({}^{\circ}\) E). Compared with the epicentral location of the Tokyo EQ in Figure 1, we can list the epicentral distances for all these four stations: (1) D = 57 km, (2) D = 15 km, (3) D = 48 km, and (4) D = 63 km. In the following sections, we will show the observational results at the stations starting from the shortest distance to farthest distance.
# Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model
## Materials and Methods
### Response of Phenology Model to Disturbance and EOS Correction Approaches  
The study area experienced two years of normal rainfall which were followed by 2.5 years of long-term drought (Palmer Drought Severity Indices, PDSI \(<-2\)), then 4.5 years of normal or slightly above-average rainfall [36]. In some years, the phenology model indicated that the ecosystem growing season covered the entire year and extended into the next year. In these cases, the end of growing season was truncated to the end of the current year (365 d).  
In response to water stress after mid-spring, daily GPP declined rapidly [36]. When the maximum rate of GPP decline during summer (June to August) following this short-term drought was greater than the maximum rate of decline during autumn (September to November), the phenology model underestimated the length of the growing season of the ecosystem, resulting in earlier EOS predictions (Figure 3a). However, this short-term drought did not affect the prediction of the SOS. In these cases, we corrected the EOS via two methods: (1) EOS was predicted based on the second highest maximum rate of decline in GPP in autumn using the phenology model itself (\(A_{SL}\)), i.e., we used the second highest  
Figure 2: Schematic diagram of annual ecosystem-scale phenological process characteristics derived from measured cumulative daily gross primary production (GPP). (**a**) \(A(t)\) is the fitted curve shown in red, and the recovery line (\(A_{RL}(t)\)) and the senescence line (\(A_{SL}(t)\)) are shown as black dotted asymptotic lines on the left and right, respectively. (**b**) \(k(t)\) is the fitted curve shown in red, where \(t_{PRD}\) denotes peak recovery day (d), and \(t_{PSD}\) denotes peak senescence day (d) [26].  
maximum rate of decline in GPP as the slope of the \(A_{SL}\) to calculate the EOS (Figure 3); or (2) The autumn date at which GPP recovered to the value of GPP at SOS was used as the corrected EOS. Where possible, the first correction method was used; however, when the phenology model yielded unrealistic predictions for the EOS correction (e.g., estimated EOS exceeded the established time scale), the second method was used. Since low-intensity prescribed fires occurred during the dormant season between winter and early spring (January-March) [37; 45], the phenology model should capture the potential impacts of fire on SOS.
## 5 Numerical Implementation
### Analysis of Scenario 3 (S3)  
This scenario evaluated the performance of the proposed optimization model in a large electrical distribution network, such as the IEEE 85-bus test system. Furthermore, the model was compared to the BWO algorithm, which was designed exclusively for the fixed operation of FACTS. Only SVC devices were considered for installation (see the literature reference [10]). The results regarding their location and size, as well as the objective function values and their reduction, are listed in Table 7 for this test system.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Location** & **Size [Mvar]** & \(z\) **(USD/Year)** & **Reduction [\%]** \\ \hline \hline \multicolumn{5}{c}{Fixed Operation} \\ \hline Benchmark case & – & – & 119,715.63 & – \\ VSA & [21; 64; 61] & [0.0839, 0.4601, 0.1139] & 102,990.79 & 13.97 \\ BWO & [21; 64; 61] & [0.0839, 0.4601, 0.1139] & 102,990.79 & 13.97 \\ \hline Convex model & [21; 64; 61] & [0.0839, 0.4601, 0.1139] & 102,990.79 & 13.97 \\ \hline \multicolumn{5}{c}{Variable operation} \\ \hline Convex model & [21; 64; 61] & [0.0929, 0.5774, 0.1481] & 100,806.50 & 15.79 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Numerical results for scenario 2.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Location** & **Size [Mvar]** & \(z\) **(USD/Year)** & **Reduction [\%]** \\ \hline \hline \multicolumn{5}{c}{Fixed Operation} \\ \hline Benchmark case & – & – & 154,651.95 & – \\ BWO & [12; 34; 67] & [0.2490, 0.3930, 0.3289] & 113,619.97 & 26.53 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Numerical results for scenario 3.  
From Table 7, it can be stated that:  
1. The proposed convex model and the BWO algorithm reach the best configuration with regard to the SVC devices, which constitutes the global solution to the problem. All SVC devices in the IEEE 85-bus test system are located in nodes with bifurcations. This behavior is different in the other two test systems. However, these locations are expected given the characteristics of the IEEE 85-bus grid, i.e., its many circuit branches, distribution of loads, and large size.
2. The SVC device with the highest capacity was installed at node 61. However, unlike the other two test systems, this one did not report a node with heightened sensitivity, since there was no significant difference between the two largest SVCs installed.
3. The annual energy losses costs are reduced with the installation of SVCs. This reduction is significant for the variable operation. The reductions in the objective functions for the fixed and variable operation of the devices are 26.53% and 30.31%, respectively. This implies that the variable operation saves USD 9251.81/year more than the other.
## 4 Results and Discussions
### The Effect of Temperature on Product Selectivity  
One strength of FT reactor modeling is that analysis of the product selectivity with reaction temperatures can be carried out to find the desired operating conditions. Figures 9-11 illustrate the variation of product selectivity based on mass fraction with operating temperature at three loads of volumetric flow rates (3.5, 5, 7.5 m\({}^{3}\)/h), respectively. As shown in these figures, for all three loads with increasing temperature the light gaseous (C\({}_{1}\)-C\({}_{4}\)), naptha (C\({}_{5}\)-C\({}_{10}\)) and diesel increase whereas, heavier liquid fuels such as wax (C\({}_{20}\)-C\({}_{60}\)) tend to decrease. This trend can be expected since higher temperatures tend to shift the \(\alpha\)-parameter to lower values thus producing more light hydrocarbons (C\({}_{1}\)-C\({}_{4}\)). In the design of the lab-scale SBCR for the FT process, it is advisable to operate the reactor under a narrow temperature range (483-503 K). This prevents catalyst deactivation, avoiding higher increases in methane as well as obtaining selectivity of diesel products [12].  
Figure 8: CO Conversion at base and change load condition based on experimental and model data.  
Figure 9: Influence of operating temperature on product selectivity; D\({}_{\text{t}}\) = 0.1 m, H = 2.5 m, V\({}_{\text{f}}\) = 3.5 m\({}^{3}\)/h, P = 20 bar, \(\varepsilon_{\text{cat}}\) = 0.34.  
It was concluded that by increasing the load of syngas flow rate, the selectivity of wax and diesel remain constant in each corresponding temperature. It was also concluded that there is a homogenous temperature profile within the reactor.
###### Abstract  
A growing interest has been expressed in the issue of building adaptability over the past decade, perceiving it as an intrinsic criterion for sustainability. In light of the circular economy (CE) and its application in the construction sector, more attention has been paid to buildings' design for adaptability (DfA) towards the realization of circular buildings. DfA is considered a key enabler for other circular design strategies such as design for disassembly (DfD), multi-functionality, spatial transformability, and design reversibility. However, implementation and assessment frameworks, and design-support tools for the circular building, are still in development as the characterization of circular buildings continues with endeavors to draw a defined shape by identifying the prerequisites for circularity where the design takes an important place. For the sake of objectifying the role of DfA in circularity frameworks in buildings, this paper carries out an analytical review and discussion on two types of assessment and design-support frameworks; the first addresses adaptability criteria and considerations in assessment frameworks that handle the concept individually while the second classifies existing circularity assessment endeavors into four main categories under which multiple tools are reviewed. A reflection on the scope and objectives for both types is later performed, illustrating the state of adaptability evaluation and criteria as well as its role in circularity frameworks. Results show that the concept of building adaptability lacks quantitative methods that quantify a building's capacity to adapt as well as empirical data that prioritize the most valuable criteria facilitating adaptations. Moreover, many circularity assessment frameworks fail to consider adaptability criteria at all hierarchal levels of a building composition. To address this shortcoming, a series of conceptual considerations and requirements is proposed towards a potential establishment of an inclusive framework of a circularity design-support tool in buildings. The study is concluded by identifying gaps and recommendations for further developments in the field.  
circular economy; circular building adaptability; DfA; assessment framework; design-support tool; criteria; indicators
## Materials and Methods
### Remote Terminal Unit
#### 2.4.4 Rotary Encoders  
The feedback signals of the RTU are generated by two absolute rotary encoders, which can maintain the angular position data when the power is removed from the system, recovering it when the power is applied back to the encoders. The system uses two single-turn absolute rotary encoders model CAS60 RS12A10 SGG with 12 bits of resolution (4096 pulses per revolution), synchronous serial interface (SSI), 5 V operating voltage, and binary code output.