esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 LSTM Recurrent Neural Network  
The LSTM recurrent neural network was proposed by [PERSON] and [PERSON] (1997) [6; 37]. Conventional recurrent neural networks present problems in training because backpropagated gradients tend to grow large or fade with time. After all, the gradient depends not only on the present error but also on past errors. The accumulation of errors causes difficulties in memorizing long-term dependencies [38].  
These problems are solved by LSTM networks, which incorporate a series of steps to decide which information is to be stored and which is to be erased with three gates that control the way information flows in and out of the unit [37], as shown in Figure 2.  
Figure 1: [PERSON] recurrent network base diagram [36].  
* Input gates control when new information can enter the memory.
* Forget gates control when part of the information is forgotten, allowing the cell to discriminate between important and excessive data, thus leaving room for new data.
* Output gates control when it is used as the result of the memories in the cell.  
The cell has a weighting optimization mechanism based on the resulting network output error, which controls each gate. This mechanism is usually implemented with the training algorithm, BPTT. Equations (4)-(8) describe the basic functioning of LSTM neurons.  
\[i_{t}=\sigma(W|\mid xi*x_{t}+W_{hi}*h_{t-1}+W_{ci}*C_{t-1}+b_{i}) \tag{4}\]  
\[f_{t}=\sigma\Big{(}W|\mid xf*x_{t}+W_{hf}*h_{t-1}+W_{cf}*C_{t-1}+b_{f}\Big{)} \tag{5}\]  
\[c_{t}=i_{t}*tanh(W_{xc}*x_{t}+W_{hc}*h_{t-1}+b_{c})+f_{t}*c_{t-1} \tag{6}\]  
\[o_{t}=\sigma(W|\mid x0*x_{t}+W_{h0}*h_{h-1}+W_{c0}*C_{t}+b_{0}) \tag{7}\]  
\[h_{t}=o_{t}*tanh(c_{t}) \tag{8}\]  
where  
* \(x_{t}\): input vector.
* \(f_{t}\): forget gate activation vector.
* \(i_{t}\): input/update gate activation vector.
* \(W\): matrix weights implemented.
* \(o_{t}\): hidden state vector, better known as the LSTM unit output vector.
## 2 Methodology
### Constructing a Pre-Earthquake Satellite Image Database  
To improve the efficiency and the degree of automation of image processing, a pre-earthquake image database can be first constructed using high-resolution optical remote sensing images covering the study area. The construction of the database mainly consists of three steps. First, radiometric calibration, atmospheric correction, and projection coordinate conversion are used to preprocess the pre-earthquake high-resolution satellite images. Then, the preprocessed images are geometrically corrected according to ground control points (GCPs) if GCPs are available. If no GCPs are available in the case of emergency, high-resolution pre-earthquake RS images with high quality and strict orthorectification can be used without geometric correction. Finally, the identity number (ID) and the coordinates of the corresponding high-resolution satellite image are recorded in a coordinate file,as shown in Table 1. The pre-earthquake RS images and the corresponding coordinate files were stored in the same directory to construct the pre-earthquake satellite image database.
# Static Bearing Capacity Investigation of a Novel Prefabricated Light-Steel Beam-Column Connection
## 1 Introduction
In a previous study [23], the authors carried out experimental tests on twelve light-steel tubular K joints consisting of square hollow sections connected by patented U-shaped connectors with pre-drilled screw holes fabricated by stamping thin-walled steel sheets. Four types of U-shaped connectors, including three with different pattens of stamping indentation and one without any stamping indentation, were investigated. As a continued study, in this paper, we report the structural performance of eight cruciform light-steel beam-column connection specimens subjected to monotonic static loading. The beam-column connection specimen consists of three components, including truss beams, an SHS column, and channel connectors welded to the column to accommodating the ends of truss beams, as shown in Figure 1. Compared to traditional light-steel frame structures consisting of profiled I-section columns and beams, the proposed structure has three advantages. First, truss beams have a much larger strength-to-weight ratio compared to profiled I-sections beams; secondly, pipes for water supply and electrical cables can easily pass through truss beams; and thirdly, SHS columns have an identical moment of inertia on two main axes. Research on the connection between truss beams and columns has rarely been reported. Therefore, it is necessary to design such a connection and investigate its structural performance. In this study, failure mode and loading-displacement curve of each specimen are investigated. In addition, the effect of three primary variables are investigated., i.e., truss-beam configuration, truss-beam type, and with or without sleeve tube reinforcing the column on the load-bearing capacity of the beam-column connections.
## 3 Results and Discussion
### Compared with the UNFCCC Inventories  
The comparison results of the winter CO fluxes of 15 western European countries inverted by the DA experiments and the corresponding anthropogenic CO emissions extracted from the UNFCCC inventories [46] are listed in Table 12. Figure S5 shows the map of these 15 countries. Up to now, the latest CO emission inventories available from the UNFCCC [46] are for 2019. Using the methodology described by [PERSON] [43], the winter seasonal anthropogenic CO emissions of these 15 countries from 2017 to 2019 were extracted from their national inventories submitted to the UNFCCC [46]. Table 12 indicates that the CO emissions inverted by the DA experiments roughly match the anthropogenic CO emissions extracted from the UNFCCC inventories. The differences between them were 13.36%, \(-\)4.59%, and \(-\)4.76% during the winter seasons from 2017 to 2019, respectively. As expected, the difference of 2017 was much larger than that of the other 2 years. Given the high boundary conditions discussed earlier, a 13.36% difference for 2017 was not too bad.  
The comparisons with the UNFCCC inventories [46] confirmed that the assumption in the experimental design, i.e., that the super majority of CO emissions in the winter season in western Europe was caused by anthropogenic emissions, was reasonable.
# On the Use of Infrared Thermography for the Estimation of Melting Enthalpy
###### Abstract  
A calorimetry method based on infrared thermography is showing promise for material screening, allowing the simultaneous detection of phase transitions of multiple samples at a time, hence enabling the establishment of phase diagrams in a record time. The working principle of this method is similar to the one of Differential Thermal Analysis. Therefore, this work aims at identifying if the melting enthalpy of materials could be estimated on the same basis using infrared thermography. In this work, the melting of six eutectic mixtures of fatty acids is estimated under three considerations. The results are compared to Differential Scanning Calorimetry measurements and literature data. The accuracy of the method is discussed and improvements are proposed.  
infrared thermography; phase transition; calorimetry; latent heat +
Footnote †: journal: Applied Sciences
###### Abstract  
A new controller based on the modified Riccati-like Equation is developed in this paper. The interval type 2 fuzzy model is applied and embedded in the controller to ensure the robustness to parameter uncertainties and also to support calculation progress. The proposed input control includes equivalent control and robustness control. The equivalent control is found from the conventional analysis with the sliding surface, but this control is not sufficient to resolve the uncertainties and disturbances such as error approximation of the fuzzy model. Thus, a proportional-integral-derivative (PID) controller and matrices of the traditional model of Riccati equation are utilized to ensure the robustness. In the synthesis of this control part, the H infinity technique is adopted and the stability of the system is proved using Lyapunov stability. Subsequently, to validate the effectiveness of the proposed controller, it was applied to vibration control of a vehicle seat suspension with a magnetorheological (MR) damper subjected to stiffness variation due to the magnitude of the input current. In this problem, two types of road conditions, bump and random step wave, were adopted and control performance was evaluated in both simulations and experiments. Based on these evaluations, the proposed controller provides high control performances, effectively controlling the acceleration and displacement at the driver position.  
robust control; PID control; H-infinity technique; interval type 2 fuzzy control; hybrid control; vibration control; magnetorheological (MR) damper; vehicle seat suspension +
Footnote †: journal: Applied Soft
## 3 Thermal and Innovative Technologies for PPO Inactivation
### High Pressure Processing  
High pressure processing (HPP) has been considered as an alternative technology to preserve food without heat or chemical preservatives [40]. HPP is a non-thermal process that is very effective in assuring the safety and quality of minimally processed food products. In contrast to thermal treatment, this technology can inactivate foodborne microorganisms and enzymes while maintaining food quality [41]. For high pressure processing, raising treatment pressures will generally result in faster microbial inactivation in shorter times. However, the increased pressure can cause protein denaturation and other potentially harmful changes in food quality, which might affect the appearance and texture of the food [40].  
For the inactivation of enzymes, the pressure is strongly dependent on the type of endogenous enzymes--some enzymes can deactivate at room temperature by a few hundred MPa [29; 35; 42; 43], while others can withstand 1000 MPa [44; 45]. As some food enzymes are highly stable, pressure must be combined with other factors such as temperature to inactivate them. During the process, hydraulic fluid (typically water) is poured into a chamber and pressurised with a pump. This pressure is then transferred to the food isostatically through the packaging, where the pressure at all sides is at the same magnitude (Isostatic principle). This procedure can increase the product's shelf life without the addition of preservatives while maintaining the product's quality (e.g., nutrients).  
When using a high pressure treatment for food processing, it is crucial to understand the interactions between the processing parameters (pressure, time, and temperature) to figure out the best conditions to achieve desired levels of microbial inactivation while maintaining a high degree of nutritional quality, good flavour, and texture [46]. Increased treatment pressures for high pressure processing will generally result in higher microbial inactivation. However, some food enzymes are extremely stable, so the pressure must be paired with other factors such as temperature to inactivate them. Several studies [29; 47] demonstrated that by utilising higher pressure (600 MPa) and a moderate temperature, fruits juice and puree could achieve PPO inactivation of more than 80%. For example, data by [PERSON] [48] show that Mulberry can achieve 88% of inactivation with pressure 365 MPa and a combination of thermal treatment at 90 \({}^{\circ}\)C. Applying pressure without heat treatment in fruits puree and juice is insufficient to totally inactivate the oxidative enzymes. Temperature assistance is required to achieve significant inactivation of these enzymes, which may improve the shelf stability of the products. The efficiency and effectiveness of HPP can be determined by various factors such as the type of food, processing time, initial pH, and the presence of certain additives in the food. The effect of high pressure processing (HPP) on PPO inactivation of various fruits is shown in Figure 5[9; 43; 48; 35; 43].
## 4 Analysis of Displacement Response Results  
### Relative Displacement at Expansion Joints  
Table 6 presents the relative displacements of expansion joints 1 and 2. The variation in relative displacements under bidirectional and multidirectional excitation by the El Centro wave was inconsistent. The maximum relative displacement between beams 1 and 2 decreased from 39.714 mm, with bidirectional excitation, to 32.155 mm, with multidirectional excitation, while the maximum relative displacement between beams 1 and 3 increased from 5.282 mm to 10.453 mm. With the multidirectional excitation of the El Centro wave, the maximum relative displacement was smaller between beams 1 and 3 than between beams 1 and 2. With the multidirectional excitation of the Lanzhou wave, the maximum relative displacement was 25.131 mm between beams 1 and 2 and was 10.523 mm between beams 1 and 3. This indicated that, under the above conditions, beams 1 and 3 were more prone to collision. Thus, the junction between straight and curved beams should have a relatively large expansion joint, or improved energy dissipation facilities, to reduce the risk of collisions and any resulting structural damage.
## 5 Results  
### Volcanic Ash Deposits Mapping  
Differential _NDVI_ analyses (Section 4.2) were used to detect ash and tephra deposits after the Agung I and Krakatau II events.  
For the _dNDVI_ analysis of ash and tephra deposits after the Agung eruptions, suitable PlanetScope scenes before (18 September 2017) and after (7 December 2017) the event were selected. The post-scene had partially heavy cloud cover, so only the southern region of Agung could be analyzed. Figure 3 visualizes the _NDVI_ changes after the eruptions around 21 November 2017 on Agung. The corresponding _dNDVI_ layer was classified into several change intervals to visualize the magnitude of change [60]. Here, the lower the _dNDVI_ values are, the stronger was the vegetation loss from pre- to post-scene. Areas with low _dNDVI_ values have therefore experienced a large vegetation change due to volcanic activity [18]. The total area of ash visible in the imagery (_dNDVI_\(<-0.4\)) was quantified to be 25.78 km\({}^{2}\). A striking feature is the spatial distribution of ash deposits on the southern flank of Agung, which become more intense with increasing proximity to the crater. In contrast, the immediate surrounding of Agung again shows higher _dNDVI_ values.  
Using a _dNDVI_ analysis, the detection of ash and tephra deposition on Anak Krakatau and surrounding islands (Krakatau II) was possible. For this purpose, a PlanetScope scene before (14 March 2018) and after (1 July 2019) the eruption on 22 December 2018 was selected. In Figure 4, the effects of ash and tephra deposition as well as vegetation destruction due to the tsunami and explosive force of the eruption are visible at Anak Krakatau and the neighboring island of Krakatau Kecil. Overall, vegetation changes (_dNDVI_\(<-0.2\)) are present on a total area of 3.4 km\({}^{2}\). Particularly affected by ash and tephra deposition was Krakatau Kecil, located to the east [42]. Figure 4 shows the decrease in _NDVI_ signal over nearly the entire island area, especially on the west coast. On Anak Krakatau, a sharp decline in vegetation signals can be seen in the east of the island.  
Figure 3: Ash deposits at Agung (I) after the eruptions around 21 November 2017 based on _dNDVI_ changes. Areas with large negative _dNDVI_ values represent strong vegetation changes or ash deposition. Background: PlanetScope pre-scene (18 September 2017). The classification could only cover partial areas to the S and SW of Agung due to strong cloud coverage at the post-scene.
# Blockage Effects in Wind Tunnel Tests for Tall Buildings with Surrounding Buildings
## 1 Introduction  
The blockage effect may lead to a serious distortion of wind tunnel test data. For example, a 5% blockage ratio for a rectangular prism model can increase the pressure coefficient by 20% [1]. The research results of the wind tunnel blockage effect of a single rectangular prism model shows that the windward wind pressure is less affected by the blockage effect, while the lateral and leeward wind pressure are more affected by the blockage effect, which has become a consensus [2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12]. Compared to a single building, the blockage effect of group buildings is usually more significant and complex [13]. Unfortunately, the existing research on the blockage effect of tall buildings mainly focuses on single model tests, while research on the blockage effect of group model tests is very scarce.  
From the traditional point of view, the blockage ratio is generally defined as the ratio of the windward area of the test model compared with the cross-sectional area of the wind tunnel test section. This definition is not ambiguous for the wind tunnel tests of an isolated building, but it is worth discussing whether the definition is applicable for wind tunnel tests of group buildings. For example, according to the traditional definition of the blocking ratio, the blocking ratios of the test models shown in Figure 1 are equal, but the blocking effect may be very different.  
For an isolated building, it is relatively easy to control the blockage ratio and blockage effect by adjusting the scale ratio. Comparatively speaking, wind tunnel tests of group buildings are more likely to cause a significant blockage effect. In practice, super high-rise buildings are usually located within grouped buildings, where the relative height, location, and number of surrounding buildings varies, which may lead to some unpredictable phenomena such as a'small blockage ratio, large blockage effect' and a'same blockage ratio, different blockage effect'. Therefore, it is of great practical significance to study the blockage effect of wind tunnel tests on tall buildings with surrounding buildings, which can provide a reference to determine the scale ratio of test models. In light of this, a series of wind tunnel tests was carried out in this paper.
## 4 Discussion
Under dynamic conditions, however, a homogeneous cell layer is formed, and h1-calponin is present in most of the cells, including cells with well-developed calponin fibers. In this case, increased cell growth and overall improved growth of cells on the surface of decellularized tissue can also be observed under dynamic culture conditions. Analogous to our study, [PERSON] et al. found upregulated expression of SMC markers, alpha smooth muscle actin (aSMA), and smooth muscle myosin heavy chain (SMMHC) in rat bone marrow stromal cells after exposure to pressure-dominant forces or combined flow and pressure forces for 3 days [34]. The authors attribute this differentiation to longer pre-incubation periods (7-21 days). The effects of different types of mechanical stimulation in isolation cyclic strain and cyclic pressure, including cyclic pressure alone, were previously studied in detail in rat bone marrow mesenchymal stem cells plated on collagen type-I coated culture slips [28; 35]. In contrast to our study, they found no SMC markers (including no calponin) via immunohistochemistry after 5 days of CP of different magnitudes. Although the cells were increasing in number under CP in the study by [PERSON] et al. [35], in our study, we initially seeded the cells in a much higher density (90,000 cells/cm\({}^{2}\) vs. 200 cells/cm\({}^{2}\)) to achieve confluence on a 3D biological material--decellularized pericardium. Our setting most probably resulted in simultaneous signaling from more sources: cell-cell contacts, cell-material contacts (natural matrix environment), soluble factors (TGF-\(\beta\)1 and BMP-4), and the mechanical load. These stimuli create synergy in conditioning the cells [36]. This may explain the fact that the cells differentiated towards the intended SMC-phenotype in our system. Additionally, the cells penetrated through the entire wall of the matrix, thus resembling a newly formed vascular tunica media. Cyclic pressure is a known factor that induces the proliferation of several cell types (EC, SMC and MSC) [28; 37; 35]. We believe that these are desired events with respect to vascular tissue engineering and future implantation of this matrix as a cell-seeded cardiovascular patch. In a future study, we plan to prepare autologous cell-seeded cardiovascular patches based on the protocol described here. Cultivation substrate will involve both autologous (porcine) Figure 11, and xenogenous (ovine) Figure 12 decellularized tissues as a substrate. In this planned study, the animals (Prestice pigs) will undergo two surgeries--the first surgery for fat tissue extraction and ASC isolation, and the second surgery in which a patch will be implanted onto an experimental carotid artery defect. Based on the protocol presented here, the time needed for preparing the recellularized autologous patch will be approximately 8-10 days for preparing the autologous ASCs and then 5 days of cultivation in the dynamic bioreactor to prepare the recellularized autologous seeded grafts.
# Gait Energy Response Functions for Gait Recognition against Various Clothing and Carrying Status
## 4 Experiments  
### Datasets  
We used three databases (OU-TD-B and OU-LP-Bag \(\beta\) databases are available at [[http://www.am.sanken.osaka-u.ac.jp/BiometricDB/index.html](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/index.html)]([http://www.am.sanken.osaka-u.ac.jp/BiometricDB/index.html](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/index.html)), CASIA-B database is available at [[http://www.cbsr.ia.ac.cn/english/Gait%20](http://www.cbsr.ia.ac.cn/english/Gait%20) Databases.asp]([http://www.cbsr.ia.ac.cn/english/Gait%20](http://www.cbsr.ia.ac.cn/english/Gait%20) Databases.asp)), i.e., the OU-ISIR Gait Database, the Treadmill Dataset B [21] (OU-TD-B), the OU-ISIR Gait database, Large Population dataset with bag, \(\beta\) version [22] (OU-LP-Bag \(\beta\)) and the CASIA Gait Database B (CASIA-B) [23] for the experiments.  
The OU-TD-B has the largest number of clothing variations, at most 32. It is separated into three subsets. The training set contains 446 sequences of 20 subjects with the range of 15 to 28 different combinations of clothing. The gallery and probe sets constitute a testing set that comprises 48 subjects, which are disjoint from the training set. Standard clothing type (i.e., regular pants and full shirt) is only included in the gallery set, while other clothing types with 856 sequences are included in the probe set.  
The OU-LP-Bag \(\beta\) includes various carrying statuses in the wild. There are 2070 subjects in the dataset and each subject has two sequences, one with carried objects and the other without carried objects. The whole dataset has three subsets: a training set, a gallery set, and a probe set. There are 2068 sequences of 1034 subjects in the training set, while the remaining 1036 subjects are included in  
Figure 4: An example of Global GERF after Gabor filtering. The rows show different scales and the columns show different orientations. In this figure, the number of scales is \(N_{s}=5\) and the number of orientations is \(N_{d}=8\), respectively.  
the gallery and probe sets. The sequences in the gallery set have no carried objects, while the sequences in the probe set have carried objects.  
The CASIA-B contains 124 subjects from 11 views (from 0 to 180 degree with an interval of 18 degree). For each view, there are ten sequences per subject. Six of them are captured under normal walking conditions (NM); two of them are captured when carrying a bag (BG); the rest two are captured when wearing a coat (CL). Among the ten sequences, the first four sequences under normal walking conditions are chosen as the gallery (NM #1-4). The other six sequences are kept as three probe sets under different walking conditions: (1) Set-A contains two NM sequences (NM #5-6); (2) Set-B contains two BG sequences (BG #1-2); (3) Set-C contains two CL sequences (CL #1-2).