esa-sceva/satcom-chunk-collection huggingface dataset:
# Ultimate Compressive Strength of H-Section Stub Columns Subject to Random Fitting Corrosion Damage
## 3 Results and Analyses
### Influence of Width-to-Thickness Ratio of Plate
#### 3.2.2 Influence of Web Thickness  
The influence of the width-to-thickness ratio of the web was examined under two different flange thicknesses of 7.5 and 11.5 mm. The web thickness was varied as 9.5, 8 and 7.5 mm. Figure 12 depicts the impact of the web width-to-thickness ratio on the ultimate strength of randomly pitted columns. Evidently, the change in web thickness did not significantly affect the reduction in ultimate strength at the same level of pitting intensity. For the thinner flange (\(t_{f}\) = 7.5 mm), the strength reductions were 14.9%, 12.7% and 18.1%, respectively, due to the change in web thickness (9.5, 8 and 7.5 mm), at the \(DOV\) 4.8%, as shown in Figure 12a. Similarly, at the \(DOV\) 13.8%, the strength reductions for the three web thicknesses were 25.5%, 27.1% and 26.6%, respectively.  
Similarly, for the thicker flange (\(t_{f}\) = 11.5 mm), the strength reductions for three web thicknesses (9.5, 8 and 7.5 mm) at the \(DOV\) 4.8% were 9.8%, 11.4% and 12.6% respectively, as illustrated in Figure 12b. Likewise, at the \(DOV\) 13.8%, the strength reductions for the three web thicknesses were 23.0%, 24.0% and 24.2%, respectively. In conclusion, the variation in flange and web thickness insignificantly impacts the reduction in ultimate strength in randomly pitted H-section columns.
# Investigation of Red Clay Internal Stress Anisotropy and Influence Factors
## 3 Results and Discussion
### The Correlation between Permeability Coefficient and Porosity  
The previous analysis has shown that under the dual influence of overburden load and stress effects, the development and distribution of void structures are significantly reshaped, thereby markedly affecting the intensity of water stress within the soil. To clarify the correlation between permeation characteristics and void development, permeability coefficients and porosity ratios at respective stages were calculated based on permeation tests under different overburden loads, and their relationship curves were constructed, as shown in Figure 6.  
As can be seen from Figure 6, there is a very strong correlation between the permeability coefficient and the porosity ratio. Specifically, the correlation between the porosity ratio and the horizontal permeability coefficient reaches 0.99, and with the vertical permeability coefficient, it reaches 0.97. This further proves that the degree of development of void structures within the soil has a key impact on the permeation characteristics in different directions of the soil. Moreover, based on regression analysis, it was found that the logarithmic values of both the horizontal and vertical permeability coefficients of red clay have a linear relationship with the porosity ratio within the soil. From the permeability coefficient in one direction, the degree of void development can be predicted, and thus, the permeation characteristics in another direction within the soil can be inferred.  
Figure 5: The relationship between permeability ratio and overlying load.  
Figure 6: Relationship between permeability coefficient and porosity ratio.
# An Optimization Routing Algorithm Based on Segment Routing in Software-Defined Networks
## 3 Algorithm Design
### Comprehensive Evaluation Model
#### 3.2.5 Calculate the Performance Evaluation of Entire Network  
The value of the performance evaluation of the whole network is calculated according to the preference of weight vector of the three types of application business. The result of comparison between the paths is obtained according to (20):  
\[P_{j}=W^{\prime}\times A^{\mathrm{T}};\;0\leq P_{j}\leq 1 \tag{20}\]  
where \(P_{j}\) represents the assessed value of total network performance of path \(j\); \(W^{\prime}\) represents the weight vector of the business scheme; \(A\) represents the vector of the assessed value of the business performance of the path in the web interaction, voice communication, and multimedia service.
## 4 Classification of MAC Protocols Based on Channel
### Cluster-Based Single-Channel MAC Protocols
#### 4.8.2 Enhanced IEEE 802.15.4  
The proposal of a V2R protocol based on the dynamic window algorithm (DWA) improves delay and throughput using a back-off scheme and the IEEE 802.15.4 standard employed for low power. Short-range communication is used in the PHY and MAC layer by CSMA/CA for contention access. A change in the binary exponent back-off (BEB) is implemented for improved performance. The frame structure known as super-frame is divided into two active parts containing a contention-free period (CFP) and a contention-based period (CBP), the inactive part, which is optional. The main objective of DWA is to minimize the delay via an extended back-off period in an exponential back-off scheme. The nodes have queues and are arranged in the form of a cluster. The nodes with empty queues have low priority and nodes with full queues have high priority, i.e., the less frames in the node queue, the smaller the exponential window size. The size of the cluster is also taken into consideration: the more nodes in the cluster, the higher the probability of collision.  
According to the simulation results, the DWA algorithm provides better results even when the cluster size is increased as it structures a balance between the nodes in the cluster and frames in the queues. Future enhancements include switching off at a threshold of different values between BEB and DWA and making the model energy-efficient by minimizing the power requirement with a collision avoidance scheme.
## 5 Conclusions  
Despite its high positioning accuracy, the positioning accuracy of the UWB positioning system when used for indoor positioning is still affected by the non-line-of-sight environment during ranging. Based on the SRD model of the TDOA algorithm, this paper proposed an improved CKF parameter adaptive indoor positioning algorithm, using the Sigmoid function to update the measurement noise matrix in real time. This algorithm was used to correct the dynamic trajectory of the UWB positioning system in the non-line-of-sight environment. The stability and positioning accuracy of the whole positioning system were greatly improved. In the experimental process, in this study, we designed dynamic trajectory static reference checkpoints for UWB positioning in the non-line-of-sight environment and compared the trajectory fitting and accuracy of the proposed algorithm. This study also compared the residual comparison experiments without using SVD decomposition to estimate the covariance matrix, and without using the Sigmoid function to update the measurement noise covariance matrix.  
The experimental results show that the improved UWB indoor positioning algorithm based on the Sigmoid function proposed in this paper can solve the problem of maintaining the positive characterization of the estimated covariance. Furthermore, it can reduce the dispersion points away from the real trajectory and improve the outliers in the non-visual range environment during the ranging process of UWB dynamic positioning. Moreover, it also enhances the stability and accuracy of the UWB positioning system. The elevation was not considered in this experiment, which could be enhanced in future research. The next step is to use this method for multi-sensor fusion to improve the accuracy of multi-source fusion indoor positioning.  
[PERSON]. ([PERSON]), [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON]. ([PERSON]) conceived and designed this study. [PERSON]. ([PERSON]), [PERSON] and [PERSON]. ([PERSON]) performed the experiments. [PERSON]. ([PERSON]) wrote the paper. [PERSON], [PERSON] and [PERSON] corrected the grammar errors and formatted the manuscript. All authors have read and agreed to the published version of the manuscript.  
The research was supported by the Science and Technology Department of Henan Province through the project Research on key technology of intelligent air-ground unmanned systems for autonomous co-operation and high dynamic tracking and landing (No. 242102210028) and the project Research on Key Technologies for the Fully Autonomous Operation of Multi-Rotor Agricultural Plant Protection UAVs (No. 222102110029).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
Figure 9: Comparative analysis of residuals at (300, 400 th) for reference checkpoints.  
Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
## 5 Conclusions  
Hence, this study demonstrates that SMOTEENN, a hybrid approach combining oversampling and undersampling techniques, consistently outperforms SMOTE in handling class imbalance across various ML models and sampling strategies. SMOTEENN achieved higher accuracy, lower mean squared error, and better generalization capabilities, as evidenced by the healthier learning curves and cross-validation results. The optimal performance of SMOTEENN was observed at a sampling strategy of 200 instances, highlighting the importance of finding the right balance in data augmentation. These findings suggest that SMOTEENN can significantly improve the reliability and accuracy of predictive models in imbalanced classification tasks, potentially leading to more effective applications in diverse fields.  
Future research would benefit from exploring an even wider array of hybrid systems that extend beyond SMOTE and Edited Nearest Neighbors. For instance, approaches that integrate ensemble learning techniques (e.g., boosting or bagging) with modern data-level or algorithm-level interventions could yield powerful synergistic effects. One possibility is to combine cost-sensitive learning or active learning frameworks with SMOTE-based oversampling to further optimize the selection and generation of synthetic examples. By doing so, researchers could reduce the likelihood of committing errors in borderline regions of the dataset, an issue that sometimes arises with SMOTE-only or SMOTEENN approaches.  
Evaluating the performance of SMOTEENN in various real-world domains beyond medical monitoring systems also remains an open direction. While this study highlighted its usefulness in fall risk assessment for bedridden patients, other fields often suffer from skewed data distributions. A systematic evaluation in these different contexts would uncover new insights into how data characteristics (e.g., noise levels and feature dimension ality) influence the effectiveness of SMOTEENN. Such comparative studies could also reveal domain-specific adaptations or parameter settings that maximize performance. Ultimately, expanding the breadth of applications tested will help solidify SMOTEENN's standing as a robust and generalizable resampling solution for modern machine learning tasks.  
Conceptualization, G.H., D.N., R.J., J.M., M.B., T.D. and M.T.; methodology, G.H., D.N. and M.T.; software, G.H. and D.N.; validation, G.H., D.N., R.J., J.M., M.B., T.D. and M.T.; formal analysis, G.H. and D.N.; investigation, G.H., D.N. and M.T.; resources, M.T.; data curation, G.H. and D.N.; writing--original draft preparation, G.H. and D.N.; writing--review and editing, G.H., D.N., R.J., J.M., M.B., T.D. and M.T.; visualization, G.H. and D.N.; supervision, M.T.; project administration, M.T.; funding acquisition, M.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
The authors declare no conflicts of interest.
# Vehicle Speed Estimation Based on 3D ConvNets and Non-Local Blocks
## 4 Experiments and Analysis  
In this section, we explain the experiments with variations of 3D ConvNets to estimate average vehicle speed in the video. The results are encouraging. In addition to variations of models, we comparatively experiment with different inputs. One notable finding is that the model result is sensitive to optical flow. To make the model more robust, we include non-local blocks and multi-scale convolution into IR(2+1)D model. Following is the details of the experiments. The code is in the supplementary material.
## 2 Materials and Methods
### Growth Rates and Cell Harvesting  
During the exposure trials, daily cell counting of _P. tricornutum_ subjected to different glyphosate-based herbicide concentrations was performed using a Neubauer improved counting chamber, with an Olympus BX50 (Tokyo, Japan) inverted microscope, at 400-times magnification. Culture growth was determined from the difference between initial and final logarithmic cell densities divided by the exposure period [54], expressed as the mean specific growth rate per day. Samples for photochemical and biochemical analysis were collected after 48 h of exposure to glyphosate-based herbicide (4 days after inoculation). Based on the glyphosate-based herbicide concentrations, we determined the No Observed Effect Concentration (NOEC) and the Lowest Observed Effect Concentration (LOEC) [55]. Furthermore, by application of a sigmoidal dose-response curve to the endpoint measurement for each exposure concentration, we also determined the Effective Concentration (EC) which inhibited growth by 10% (EC\({}_{10}\)), 25% (EC\({}_{25}\)), and 50% (EC\({}_{50}\)) [55]. At the end of the exposure time and after the chlorophyll fluorescence measurements (see next section), samples of 30 mL of culture were centrifuged at 4000\(\times\)\(g\) for 15 min at 4 \({}^{\circ}\)C (Sigma 2-16K, Sigma Laborzentrifugen GmbH, Germany). The supernatant was removed, and pellets were immediately frozen in liquid nitrogen and stored at \(-\)80 \({}^{\circ}\)C until analysis.
## 6 Discussion on Gaps, Challenges, and Links to Future Works
### Limited Realistic Assumptions  
The lack of sufficient accurate data on evacuee behaviors during wildfire evacuations often necessitates the use of unrealistic assumptions in evacuation models. These assumptions can lead to inaccuracies in simulating evacuation processes, potentially underestimating the outcomes and compromising the safety of communities in WUI areas. It is imperative to bridge the gap between model assumptions and real-world behaviors to improve the reliability and applicability of evacuation models. This can be achieved through continued efforts to collect behavioral data, refine model parameters, and incorporate novel methodologies that better align with real-world evacuee behavior.
# Bearing Anomaly Recognition Using an Intelligent Digital Twin Integrated with Machine Learning
## 4 Conclusions  
In this research, the application of the intelligent digital twin integrated with machine learning was observed for bearing anomaly detection and crack size identification. The proposed algorithm had three main parts: intelligent digital twin, residual signal determination, and anomaly classification, and crack size identification. The first part of the intelligent digital twin was the function approximator. The integration of the mathematical-based vibration signal modeling, autoregressive with Laguerre technique, and support vector regression was recommended for the proposed function approximator. Moreover, the next part of the intelligent digital twin was the signal estimator. The combination of a Kalman filter, the high-order variable structure technique, and the adaptive neural-fuzzy approach was used for signal estimation. After designing the intelligent digital twin, the residual signals were determined. The residual signals were resampled and the RMS feature was extracted from the resampled residual signals. In the final stage of design, the SVM was integrated with an intelligent digital twin to identify the bearing crack sizes and fault patterns. The impact of the proposed scheme was tested by CWRUBD and compared with the MS-RKF and the MS-KF algorithms. Regarding the experimental results, the proposed scheme improved the average accuracy for the bearing fault pattern recognition by 12.55% and 17.4%, respectively, compared with the MS-RKF and the MS-KF algorithms. In addition, in the view of crack size identification, the impact of the proposed technique was 98.7%, 100%, and 100% for the ball, inner, and outer faults, respectively. For future work, the parallel machine/deep learning digital twin will be suggested for fault diagnosis of nonlinear systems with nonstationary signals.  
Conceptualization, F.P. and J.-M.K.; data curation, F.P.; formal analysis, F.P. and J.-M.K.; funding acquisition, J.-M.K.; methodology, F.P. and J.-M.K.; software, F.P.; supervision, J.-M.K.; validation, F.P. and J.-M.K.; visualization, F.P. and J.-M.K.; writing--original draft, F.P.; writing--review and editing, F.P. and J.-M.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by 2021 Research Fund of University of Ulsan.  
The data are publicly available.  
The authors declare no conflict of interest.  
Figure 20: Boxplots of the average CSI metrics over 10 experiments for the MS-HRKF+SVM, the MS-RKF+SVM, and the MS-KF+SVM to test the power of robustness.
## 2 Biological Wastewater Treatment and Emerging Research
### Biological Phosphorus Removal  
Phosphorus accumulation in the environment can result in eutrophication in aquatic water systems, meaning it is crucial to remove it from WWTPs [21]. Phosphorus enters the wastewater treatment plant through residential water that contains a large amount of phosphorus from the use of synthetic detergents that contain high polyphosphate concentrations. Orthophosphates and polyphosphates are the most common forms of phosphorus found in WWTPs, which constitute 70 to 90% of the phosphorus found in WWTPs. The rest are from inorganic compounds.  
Biological phosphorus removal is a sustainable and environmentally friendly method to reduce phosphorus from WWTPs [22]. Traditional biological phosphorus removal involves the use of phosphate-accumulating organisms (PAOs). This process involves the circulation of activated sludge between the anaerobic and aerobic phases. During the introduction of the effluent water into the anaerobic phase, the abundance of degradable carbon sources such as volatile fatty acids (VFAs) present in the sludge induces the uptake of this acid by phosphate-removing bacteria, thereby releasing phosphate into an aqueous solution, while phosphorus uptake occurs in the aerobic phase. It has been shown that wasting excess sludge results in high phosphorus removal [23].  
Recently, it has been shown that denitrification can be achieved by denitrifying PAOs (DPAOs) under anaerobic conditions. This occurs when the PAO ingests high amounts of phosphorus, thereby promoting the uptake of nitrate as a final electron [24]. [PERSON] et al. [25] successfully developed an innovative denitrifying phosphorus removal and partial denitrification anammox process in an ABR-CSTR reactor to improve the nitrogen and phosphorus removal. The author indicated that this process successfully removed up to 97.57% and 95.66% of total inorganic nitrogen and phosphorus, respectively. These results are comparable to the result obtained by [PERSON] et al. [26], who obtained 78.35% and 98.34% removal rates for nitrate-to-nitrite transformation and phosphorus using a novel denitrifying nitrite accumulation and phosphorus removal (DNAPR) process. DPAOs are said to produce 40% less energy as compared to PAOs, meaning DPAOs requires less COD and aeration. This makes DPAOs ideal over PAOs, particularly for the treatment of domestic wastewater, which contains low levels of COD [27]. It has been suggested that more COD could be saved if DPAOs could be used for SND via nitrite. Thus, there has been a rising interest in applying DPAOs for SND.
## 2 Distinguishing the Thrombic Microangiopathy of EHEC-Related HUS
Coagulopathy during TTP results from inherited or immune-acquired deficiency in a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS13), needed to cleave von Willebrand Factor (VWF) released from endothelial cells to prevent accumulation of prothrombotic ultra-large VWF (UL-VWF) oligomers. Murine models of EHEC toxemia do not develop thrombocytopenia and, therefore, do not present with HUS. Recently these Stx models have included bacterial endotoxin (Gram negative lipopolysaccharide, LPS), tumor necrosis factor-\(\alpha\) (TNF\(\alpha\)), adenosine diphosphate (ADP) or similar along with the toxin to induce platelet loss in an effort to replicate full-spectrum HUS [29]. While thrombocytopenia is observed in the mice after LPS + Stx, it is a consequence of pro-inflammatory priming, resulting in endotoxin-induced DIC [30], not Stx-induced HUS, with different coagulation mechanisms. Figure 2: Thrombocytopenia is common to HUS and DIC, but these are clinically distinct entities. Platelet loss occurs with both HUS and DIC, but markers of coagulopathy differ and highlight mechanistic differences. DIC is a consequence of lipopolysaccharide (LPS) in experimental systems (e.g., murine models) or clinically as a complication of underlying diseases such as bacterial sepsis or malignancy. DIC is a consumptive coagulopathy characterized by decreasing fibrinogen and coagulation factors with marked up-regulation of fibrinolysis markers such as fibrin degradation products (FDP) and d-dimer. In contrast, HUS does not consume coagulation factors and fibrinogen levels are often increased in EHEC patients. Moderate levels of fibrinolysis are present, but markers of microangiopathic hemolytic anemia (MAHA), such as schistocytes, are markedly elevated.
# Thin CdTe Layers Deposited by a Chamberless Inline Process using MOCVD, Simulation and Experiment
###### Abstract  
The deposition of thin Cadmium Telluride (CdTe) layers was performed by a chamberless metalorganic chemical vapour deposition process, and trends in growth rates were compared with computational fluid dynamics numerical modelling. Dimethylcalmium and diisopropylltluride were used as the reactants, released from a recently developed coating head orientated above the glass substrate (of area \(15\times 15\) cm\({}^{2}\)). Depositions were performed in static mode and dynamic mode (i.e., over a moving substrate). The deposited CdTe film weights were compared against the calculated theoretical value of the molar supply of the precursors, in order to estimate material utilisation. The numerical simulation gave insight into the effect that the exhaust's restricted flow orifice configuration had on the deposition uniformity observed in the static experiments. It was shown that \(>59\%\) of material utilisation could be achieved under favourable deposition conditions. The activation energy determined from the Arrhenius plot of growth rate was \(\sim\) 60 kJ/mol and was in good agreement with previously reported CdTe growth using metalorganic chemical vapour deposition (MOCVD). Process requirements for using a chamberless environment for the inline deposition of compound semiconductor layers were presented.  
CFD modelling; chamberless inline process (CIP); MOCVD; cadmium telluride +
Footnote †: journal: Applied Sciences