esa-sceva/satcom-chunk-collection huggingface dataset:
# Experimental Study of High-Strength Concrete-Steel Plate Composite Shear Walls
## 3 Experimental Results and Discussions
### Progression of Damage and Failure Modes
As for specimens with the aspect ratio of 2.7, the flexure-dominant failure mode is identified with horizontal cracks  
Figure 9: Failure Modes of Shear Wall Specimens. initiating at the ends, concrete spalling, and tensile fracturing of steel bars. A special characteristic that is observed in RCSPSW specimens is that the embedded steel plate tended to buckle when failure occurred, which was accompanied by severe concrete spalling in the lower portion of the wall. In general, more characteristics of shear failure were observed on the specimens with the decrease of the aspect ratio. A higher axial compression ratio restrained the development of inclined cracks in the web for the reason that the principle tensile stress would be reduced with the increase of the axial load based on experimental observations. Additionally, the \"distance\" between concrete spalling and wall failure drastically reduces as the axial compression ratio increasing, which results in a more brittle failure mode. The wall panel in RCSPSW is divided into two halves by the embedded steel plate when compared with conventional RCSW, which results in relatively weaker mechanical collaboration between concrete and steel. It is very important to ensure the effective bonding between two parts to support the engineering application of RCSPSW, although no debonding failure was observed in the quasi-static test. Potential approaches include: (1) using ribbed steel bars with rough surface to increase the mechanical adhesion and friction; (2) specifying sufficient concrete cover to effectively confine steel reinforcement; (3) connecting reinforcement mesh to the embedded steel plate with steel ties, so that the RCSPSW works as a monolithic system; and, (4) adding steel fibers in the concrete to increase the bond strength, as suggested by [PERSON] [44] and [PERSON] [45]. Besides, the use of fiber composite elements is helpful in strengthening the bonding between concrete and steel, and the techniques that were developed by [PERSON] [46] using glass fiber reinforced polymer (GFRP) can be deployed.
## Materials and Methods
### Dataset  
Patient data were recorded at the Department of Nuclear Medicine of the University Hospital of Patras from 16 February 2018 to 28 February 2022. Over this period, 2036 consecutive patients underwent gated-SPECT MPI with 99 mTc-tetrofosmin. Two-hybrid SPECT/CT gamma camera systems (Varicam, Hawkeye and Infinia, Hawkey-4, GE Healthcare, Chicago, IL, USA) were employed for MPI imaging. Computed tomography-based attenuation correction (AC) was applied to stress and rest images in all subjects. Five hundred and six participants were subsequently subjected to ICA within sixty days from MPI for further investigation. Twenty patients were excluded from the dataset due to inconclusive MPI results or missing ICA reports. The final study population included 486 patients (CAD-positive cases refer to 43.82% of the total). Data collection was approved by the ethical committee of the University General Hospital of Patras (Ethical & Research Committee of University Hospital of Patras--protocol number 108/10-3-2022). The study's retrospective nature waived the requirement to obtain informed consent from the participants. All data-related processes were performed anonymously. All procedures in this study followed the Declaration of Helsinki. Three experienced nuclear medicine physicians provided the diagnostic results of MPI SPECT by inspecting the study retrospectively and, independently, the Polar Maps. Between-reader inconsistencies were resolved by consensus.  
Tomographic reconstruction of raw image data on a dedicated workstation (Xeleris 3, GE Healthcare) by the OSEM (ordered subset expectation maximisation) algorithm using two iterations and ten subsets. After reconstruction, a low-pass filter (Butterworth, with power of ten and a cut-off value of 0.40 for stress and 0.45 for rest images) was applied. Apart from 3-plane tomographic slices (in short, vertically long and horizontally long axes), the software automatically created polar maps. A polar map is an image that summarises the results of 3D tomographic slices into a single 2D circular presentation. Polar maps were extracted from the workstation in DICOM (Digital Imaging and Communications in Medicine) format for further processing.
# DNA Barcoding as a Plant Identification Method
## 4 Chloroplast DNA Barcodes
### trnH-psbA  
_trnH-psbA_ is one of the most variable non-coding plastid loci with an intergenic spacer suitable to offer a high level of species discrimination [35; 37]. It is easily amplified with universal primers but as it has high rates of insertion/deletion, alignment can be difficult. Moreover, its length varies among different families, with this region containing copies of _rps19_ in some cases, as well as a pseudogene that is located between _trnH_ and _psbA_; this causes a problem, as despite obtaining high-quality bidirectional sequences, alignment is difficult due to the high length variation. Most researchers have proposed that _trnH-psbA_ should be used in combination with one or more loci to provide adequate resolution [7; 20; 30; 37; 47]. Nevertheless, is has been shown that it is a suitable marker for flowering plants and peptidophytes [6; 21].
# Utilizing Ensemble Learning to Improve the Distance Information for UWB Positioning
###### Abstract  
An ultra-wideband (UWB) positioning system consists of at least three anchors and a tag for the positioning procedure. Via the UWB transceivers mounted on all devices in the system, we can obtain the distance information between each pair of devices and further realize the tag localization. However, the uncertain measurement in the real world may introduce incorrect measurement information, e.g., time, distance, positioning, and so on. Therefore, we intend to incorporate the technique of ensemble learning with UWB positioning to improve its performance. In this paper, we present two methods. The experimental results show that our ideas can be applied to different scenarios and work well. Of note, compared with the existing research in the literature, our first algorithm was more accurate and stable. Further, our second algorithm possessed even better performance than the first. Moreover, we also provide a comprehensive discussion for an ill-advised point, which is often used to evaluate the positioning efficiency in the literature.  
positioning system; distance information; ensemble learning; machine learning +
Footnote †: journal: Applied  
extreme data and works well. Here, we have a question about these thresholds: are they the best threshold values for their filtering method? Hence, we will apply the concept of ensemble learning to set the thresholds independently and automatically and also present a comprehensive discussion with regard to different thresholds. Note that ensemble learning is a critical and interesting concept, which does not directly modify the original models, but combines several weak and independent models in order to achieve a stronger one [6, 7]. In this paper, it is adopted to cascade machine learning algorithms.  
Last but not least, the authors in [5] utilize the positioning error to conduct their evaluation. However, the positioning information and error are calculated by a trilateration, which may implicitly include some error-tolerant or optimization design, such as the digit-by-digit calculation. Obviously, a fairer evaluation mechanism is to evaluate the distance information. Consequently, in this paper, to avoid such a situation, we will consider the distance error to conduct our evaluation instead of the positioning error.  
This paper is organized as follows: first, some preliminaries related to our research are reviewed in Section 2. Then our methods and the experimental results corresponding to different settings and scenarios are presented and discussed in Sections 3 and 4. Finally, this research is concluded in Section 5, and we suggest some feasible future work as well.
## 4 Discussion
### Consistency between Automatic and Manual Scoring  
The kappa values between manually and automatically assigned scores for the six tests were computed in this study. A previous study showed only poor to moderate intermethod agreement (kappa coefficients 0.05 and 0.52) [14]. Their sensor-based semiautomatic system used manual setting kinematic thresholds to correspond to FMS grading criteria. In the present study, the kappa values before feature selection for the trunk stability pushup, deep squat, active straight leg raise, in-line lunge and rotary stability, and hurdle step tests displayed very good, good, moderate, fair, and poor agreement (kw = 0.85, 0.80, 0.42, 0.37 and 0.34, and 0.18), respectively. The overall kappa values were between 0.18 and 0.85, indicating that the machine learning method used to model the kinematic threshold was more accurate than the manual setting. Although we present suitable parameters, because of the large variations in body movement, we recommend using full-body IMU sensors for FMS assessment to obtain the most accurate evaluation.
## 6 Performance Evaluation and Discussion
### Quantitative Performance and Discussion  
To implement accurate adhesive path planning, displacement-to-height curves (Section 4.1.3) were calibrated using a custom three-level block (Figure 29). The average height errors were 0.34 mm (left), 0.35 mm (right), and 0.13 mm (top), all within industrial tolerances. Repeatability tests using a fixed-size lasted upper showed deviations between \(-\)0.4 mm and +0.5 mm, well below the \(\pm\)1 mm tolerance common in footwear production. These variations had no adverse impact on spraying performance. The robotic arm maintained stable contact with the guide plate, resulting in accurate and uniform adhesive application.  
A minor glue-deficient area near the toe cap was observed (Figure 28), likely due to the difficulty of following the bonding line across a sharp curvature. This localized issue is discussed as a direction for future mechanical refinement.  
As shown in Figure 30, the straight lower edge of the baffle cannot conform to the curved toe cap, causing adhesive to overflow beyond the bonding line. Adjusting the spraying path inward reduced the overflow but led to the partial blockage of the bonding area, resulting in localized glue deficiency. This trade-off reveals a design limitation of the current baffle when handling complex curves. Future improvements--such as using a flexible or contoured baffle or integrating dynamic nozzle orientation--may resolve this issue.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Process Stage** & **Time (s)** \\ \hline First drying (1 st oven) & 60 \\ \hline
3D scanning and transport & 10 \\ \hline Pick and place of the lasted upper \(\times\) 7 & 15 \(\times\) 7 = 105 \\ \hline Spraying operation \(\times\) 2 & 45 \\ \hline Second drying (2 nd oven) & 180 \\ \hline Third drying stage (3 rd shared oven) & 180 \\ \hline Total process time & 580 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Time consumption of each stage in the lasted upper gluing process. The total cycle time is optimized through pipeline synchronization, while the drying stages remain fixed due to adhesive curing requirements.  
Figure 28: UV-based verification of adhesive spraying results. The fluorescent dye enables the visualization of the adhesive coverage under UV light. From left to right: toe, heel, left side, and right side. The sprayed adhesive closely follows the bonding lines, with a slight deviation observed at the toe.
## 2 Numerical Model and Parameters
### Boundary Condition  
(1) Inlet boundary conditions: The inlet boundary condition is a velocity-inlet with an exponential rate-averaged wind profile. Refer to Equation (1):  
\[v(y)=v_{b}\Big{(}\frac{y}{10}\Big{)}^{\alpha} \tag{1}\]  
where \(z\) is any height; \(v(y)\) is the average wind speed at height \(y\); \(v_{b}\) is the average wind speed at a height of 10 m. As per the specifications in [21], the wind speed obtained after converting the basic wind pressure with a return period of 20 years was 25 m\(\cdot\)s\({}^{-1}\). The selection of B-type terrain, as specified by the load criteria [21], encompasses fields, villages, forests, hills, and sparsely populated townships and suburban areas, for a B-type terrain with a roughness length coefficient of \(\alpha=0.15\)[21].  
The turbulence characteristics at the inlet are defined by directly giving the turbulent kinetic energy \(k\) and the turbulent dissipation rate \(\varepsilon\), whose expressions are given in Equations (2) and (3).  
\[k=\left[v(y)I(y)\right]^{2} \tag{2}\]  
\[\varepsilon=0.09^{0.75}k^{1.5}/l \tag{3}\]  
\[l=100(y/30)^{0.5} \tag{4}\]  
where \(l\) is the turbulence integration scale, as expressed in Equation (4). \(I(y)\) is the turbulence intensity, as shown in Equation (5).  
\[I(y)=\left\{\begin{array}{ll}0.23&(y\leq 5m)\\ 0.1(y/350)^{-\alpha-0.05}&(5m<y\leq 350m)\end{array}\right. \tag{5}\]  
(2) Outlet boundary conditions: A fully developed outflow boundary condition was used, where the physical quantities do not change along the flow direction.  
(3) The top and lateral sides of the fluid domain: The symmetry boundary condition was used, which is equivalent to a free-sliding wall.  
(4) Greenhouse model surfaces and floors: Using no-slip wall conditions.
## 3 Experiments and Processes  
### Gas Sealing Performance Test  
After ensuring that all the experimental setups were ready, the air pump was first opened for a short period of time for ventilation. Observations could be made through the casing and flange connection to check for the presence of bubbles in the water, testing whether there was any leakage in the setup.  
After the sealing performance test of setup was completed, the casing with alloy plug sample was placed in the setup. The heating rod was activated to raise the water temperature to the required temperature, insulation was carried out, and the insulation time was set to 2 h to allow heat transfer from the casing to the alloy plug. Then, the gas sealing was completed test. Expanding air inside the casing during heating process might interfere with the experiment. Therefore, the air pressure sensor was installed at the end cap on the top of the setup after 1 h of heat preservation.  
The air pump was opened to increase the air pressure under the alloy plug, which produced a differential pressure across the alloy plug. The differential pressure was gradually increased until the reading of air pressure sensor changed. Pressurizing was then stopped, and monitoring was continued for 2 h, until the pressure readings were stable. The difference of indication between the sensor and the air pump at this moment was recorded as the air pressure difference when the alloy plug failed. Under each condition, a group of alloy plug samples was tested at least three times to exclude the interference of accidental factors in the experimental process.
## 2 TIA Design
### TIA Stage  
Figure 4 shows a schematic of the TIA. A first common-base stage buffers the incoming photocurrent, with biasing provided by resistor \(R_{C-CB}\) at the collector node and a current mirror at the emitter. To limit power consumption and allow the largest possible bandwidth, the minimum transistor size was selected that could provide the required low TIA input impedance (below 50 \(\Omega\)) under maximum f\({}_{\text{t}}\) biasing conditions. Double finger devices (with an emitter area of 0.12 \(\times\) 0.48 \(\,\mathrm{\SIUnitSymbolMicro m}^{2}\) per finger) were selected for this stage (transistors Q1-Q2) with a biasing current of around 1.4 mA per finger. The common-base is loaded by a shunt-feedback (SFB) transimpedance stage, implemented as a differential pair using single finger devices (transistors Q3-Q4), with feedback resistors \(R_{f}\) and emitter degeneration and peaking provided by \(R_{E}\) and \(C_{E}\). The SFB stage performs single-ended to differential conversion by AC grounding of one of its inputs through capacitor \(C_{C}\). The dummy common-base is maintained at the grounded input to provide a matched DC level, while keeping layout symmetry and suppressing additional substrate and supply noise. The values for the main circuit components are provided in the accompanying table in Figure 4.  
The common-base stage provides a low input impedance, which is determined by transistor sizing and current, and thus is not dependent on the feedback resistor \(R_{f}\). This helps with speeding up the input node of the TIA in the presence of a relatively large photodetector capacitance. The gain-bandwidth trade-off affecting the SFB topology is now  
Figure 4: Schematic of the TIA stage implementation.  
Figure 3: Compact inductor design used in the input LC high-pass filter: (**a**) Comparison of dual-spiral inductor design, where two inductors with opposite winding directions are connected in series, with a regular single spiral inductor; (**b**) inductance as a function of frequency for the dual and single-spiral inductors obtained by electromagnetic simulation, where the self-resonance frequencies for each design are observed.  
effectively decoupled from the photodetector, and limited now by circuit and technology constraints. As a known drawback, this topology usually features higher noise and power consumption compared to a classical SFB TIA [12]. Although further noise optimization of this stage is possible [13], this was not prioritized in this design. Additional LO laser power can be used instead to push the receiver sensitivity towards the shot-noise limit.
## 3 Experimental Results
### Energy Dissipation Capacity  
Energy dissipation capacity is an important evaluation index of the seismic performance of a structure. In a destructive earthquake, if the energy cannot be absorbed, it will lead to local or overall structural damage. The energy dissipation capacity of the specimen is evaluated by the equivalent viscous damping coefficient \(h_{e}\). The equivalent viscous damping coefficient is the ratio of the energy stored in the specimen to the deformation energy of the specimen in the elastic phase. The formula is as follows:  
\[h_{e}=\frac{1}{2\pi}\frac{area(ABC)}{area(OBD)}, \tag{1}\]  
The calculation diagram is shown in Figure 6. The equivalent viscous coefficients of the specimens are shown in Table 5. By analyzing the data, the following conclusions can be drawn:  
1. Whether it is the whole wall or a seam wall, the energy dissipation capacity of the laminated wall is no worse than the cast-in-place wall, indicating that the laminated wall has as good a seismic performance as the cast-in-place wall.
2. The PCFI-C has a generally higher equivalent viscosity coefficient than PCFI-A, indicating that the energy dissipation of the seam wall is better than that of the whole wall. This may be due to the greater deformation caused by the seam; thus, more energy is dissipated. Such a seam effect is also reported in the literature [44].
3. Compared with PCFI, PCFI has a higher equivalent viscous coefficient, which may be due to the fact that the concrete strength of PCFI is larger than PCFI by about 10%. The structural measures have little effect on its energy consumption capacity.
## 4 Conclusions  
This study demonstrated the feasibility of using LW-PLA in drone fuselage components to enhance energy absorption during deformation while maintaining a weight limitation. By applying a design-for-additive-manufacturing (DfAM) approach, we developed metastructures that strategically combine different density zones to satisfy both mechanical and mass constraints. This research resulted in the following key findings:  
* Material efficiency: The stiffening core of the LW-PLA metastructure enabled a weight reduction of up to 62.6% while still achieving adequate energy absorption for non-critical drone components.  
* Structural optimization: The modified prototypes, featuring hybrid internal structures (notably the sample where internal buckling of the stiffening core was eliminated), exhibited superior performance under both monotonic and repeated loads, underscoring the significance of core stabilization and internal buckling control.
* Comparative framework: The use of a theoretical deformation energy benchmark (300 J) provided a practical and consistent method for evaluating structural efficiency. However, it does not capture real-world design limitations. Therefore, future research should explore dynamic (impact) testing, the fatigue behavior of materials, and integration with drone systems in realistic environmental conditions.
* Design implications: The experimental findings and design insights suggest utilizing lightweight, consumer-grade polymeric materials and desktop printers for drone prototyping. This approach could lead to broader adoption in academic and hobbyist settings. Additionally, further studies should incorporate sophisticated algorithms to achieve a multi-objective optimization solution.  
Conceptualization, V.G. and D.R.; methodology, V.G. and A.R. ([PERSON]); software, A.R. ([PERSON]); validation, V.G., S.S. and D.R.; formal analysis, V.G.; investigation, A.R. ([PERSON]) and A.R. ([PERSON]); resources, S.S.; data curation, A.R. ([PERSON]); writing--original draft preparation, A.R. ([PERSON]); writing--review and editing, V.G.; visualization, A.R. ([PERSON]) and A.R. ([PERSON]); supervision, V.G.; project administration, S.S.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.  
This research work received funding from the project \"Civil Engineering Research Centre\" (agreement no. S-A-UEI-23-5, SMSM).  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare that they have no conflicts of interest.
# Harnessing Digital Twins for Sustainable Agricultural Water Management: A Systematic Review
## 4 Results
### Key Concept and Applications  
Implementing DT technologies in agricultural water management offers significant benefits across irrigation, hydroponics, aquaponics, and plant and vertical farming.
# On the Quality of Deep Representations for Kepler Light Curves Using Variational Auto-Encoders
## 3 Experimental Setup and Results
### Model Assessment and Implementation  
For assessing the quality in the latent representation of global-folded light curves learned by the proposals, we propose validating the reconstruction task based on that representation, the representation disentanglement, and the true planet classification by using the representation (extrinsic validation).