esa-sceva/satcom-chunk-collection huggingface dataset:
# A Critical Review of the Modelling Tools for the Reactive Transport of Organic Contaminants
## 2 Processes
### Transport
Even within macroscopically homogeneous porous media, migrating hydrocarbons are presumed to follow narrow and irregular pathways. The movement along these favoured flow paths is dictated by competing driving and drag forces. When the driving force is relatively weak, hydrocarbons will migrate along paths where the hydraulic conductivity is relatively high [117]. Moreover, the transition of heavy hydrocarbons into the aqueous phase and subsequent transport with the flow is severely limited due to low solubility, high retardation, and a propensity for sorption and precipitation [118; 119]. Consequently, heavy hydrocarbons are unlikely to migrate over long distances, except perhaps in karstic or fractured media.
# One-Part Alkali-Activated Pastes and Mortars Prepared with Metakaolin and Biomass Ash
###### Abstract  
Common alkali-activated materials (AAMs) are usually manufactured with highly alkaline solutions. However, alkaline solutions are dangerous for workers who must wear gloves, masks, and glasses when handling them. This issue makes common (or two-part) AAMs not user-friendly and problematic for bulk production if no safety procedures are followed. In this paper, the possibility of manufacturing alkali-activated pastes and mortars without alkaline solution is investigated. These innovative one-part AAMs have been prepared with metakaolin as the aluminosilicate precursor, potassium-rich biomass ash as the alkaline activator, and water. AAMs have been prepared by varying the K/Al molar ratio: pastes have been studied in terms of reaction kinetics, through isothermal calorimetry, and mortars have been tested in terms of mechanical compressive strength. Results show that the K/Al molar ratio governs both the reaction kinetics and the mechanical strength of these innovative materials. The highest compressive strength is obtained when the K/Al ratio is equal to 2.5 and the water/solid ratio is equal to 0.49. If biomass ash is heated at 700 \({}^{\circ}\)C to decompose the calcium carbonate, its reactivity and the final compressive strength increase.  
one-part geopolymers; geopolymer; alkali-activated materials; metakaolin; biomass ash; isothermal calorimetry; compressive strength Article
# Architecture Exploration of a Backprojection Algorithm for Real-Time Video SAR
## 4 Experimental Results
### Discussion  
Conventional studies on GPU-based BPA acceleration have mainly presented the imaging time and speed-up ratio after acceleration as performance measures [20; 23], but these studies did not perform comparative studies with the previous literature of different GPU computing and SAR imaging environments.  
For objective comparison of acceleration performance, excluding the effect of different GPUs and the SAR imaging parameters, we define the normalized imaging time as follows.  
\[t_{norm}=t_{i}\cdot\frac{n_{core}\cdot f_{GPU}}{n_{pixel}\cdot N_{p}}, \tag{11}\]  
where \(t_{i}\), \(n_{core}\), \(f_{GPU}\), \(n_{pixel}\) represent the imaging time of one SAR image or frame, the number of CUDA cores, the clock frequency of the GPU, and the number of imaging pixels, respectively.  
Table 9 shows the normalized imaging times for BPA acceleration architectures. We set the imaging time of Arch. F3 of the non-overlapped mode as the reference for comparison. The GPU accelerated BPA architectures in references [20] and [23] are 1.49 and 1.13 times slower than the proposed Arch. F3 with non-overlapped aperture processing. For the proposed architectures, increasing the overlap ratio helps reduce the normalized time, especially for the sub-aperture processing architecture of Arch. S3. For Arch. S3, multi  
Figure 13: Performance comparison: multiple stream and multi-GPU processing.  
stream processing within a single GPU helps utilize the GPU resources efficiently, and the processing speed is scalable to the number of GPUs.
# Smooth 3D Dubins Curves Based Mobile Data Gathering in Sparse Underwater Sensor Networks
###### Abstract  
Sensory data collection is one of the most important concerns in underwater sensor networks (USNs). Because full connectivity cannot be guaranteed, mobile data gathering with autonomous underwater vehicles (AUVs) is widely used in sparse three-dimensional (3D) USNs to solve energy-imbalance problems between different sensor nodes. AUVs with relatively abundant energy and storage can collect sensory data from one sensor node to transmit to another node, so as to avoid energy-intensive multi-hop transmission. As a result, movement control strategy and data collecting path planning for AUVs are very crucial for the performance of data acquisition. This paper proposes a smooth 3D Dubins curves based mobile data gathering mechanism to overcome the kinematic nonholonomic constraints of AUVs. The objective of our proposed method is to collect sensory data along smooth 3D Dubins paths, which are interpolated by continuous Bezier curves in the \(Z\)-axis from 2D Dubins curves. Extensive simulation results verify that the proposed method has a more efficient performance in terms of path smoothness and energy consumption; thus it is very suitable for mobile data collection in 3D underwater sensor networks.  
underwater sensor networks; mobile data gathering; autonomous underwater vehicles; 3D Dubins curve +
Footnote †: journal: Sensors
###### Abstract  
**Purpose:** Footwork speed is closely linked to explosive strength, and both percentage- (PBRT) and velocity-based resistance training (VBRT) are popular methods for developing muscle strength. This study aimed to compare the effects of PBRT and VBRT on lower limb explosive power and footwork movement speed in elite university badminton players over a 6-week training period. **Methods:** A total of 20 elite badminton players (12 males, 8 females) from Tongji University were randomly divided into VBRT (\(n=10\)) and PBRT groups (\(n=10\)). The VBRT group trained with loads determined by target speed and velocity loss, while the PBRT participants used fixed loads based on a percentage of their one-repetition maximum (1 RM). Both the groups performed free-weight back squats with relative loads ranging from 65% to 95% of 1 RM over 6 weeks. The pre- and post-training measurements included back squat 1 RM; countermovement (CMJ), squat (SJ), and standing long jumps (SLJs); self-weighted squat jump speed (SJS); left and right touch line (LRF), full-field four-point (FF), and front and back touch net footwork (FBF). **Results:** (1) The baseline measurements showed no significant differences between the groups (\(p>0.05\)). (2) Post-training, both VBRT and PBRT improved the participants' lower limb explosive power and footwork movement (\(p<0.05\)). (3) The VBRT group demonstrated significantly greater improvements than the PBRT group in all the measures (\(p<0.05\)). **Conclusions:** VBRT was superior to PBRT in boosting lower limb explosive power and footwork speed in badminton players over 6 weeks, leading to more significant strength-related and neural adaptations.  
**Article**  
**The Effects of Velocity- Versus Percentage-Based Resistance Training on Lower Limb Explosive Power and Footwork Movement Speed in Elite University Badminton Players. _Appl. Sci._**2005**, 15, 2044. [[https://doi.org/10.3390/app15052434](https://doi.org/10.3390/app15052434)]([https://doi.org/10.3390/app15052434](https://doi.org/10.3390/app15052434))  
**Copyright:** (c) 2025 by the authors.  
**License MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).**
## 5 Simulations of the Path Tracking Control for the Roadheader
Figure 12: Path tracking through BP neural network for coefficient optimization but without using states estimation: (**a**) the coincidence between expected and simulated tracking paths; (**b**) the position and orientation errors; (**c**) the required angular speeds of the driving wheels. follows: recall that \(x_{e}\) is the summed projection of \(X_{d}-X_{c}\) and \(Y_{d}-Y_{c}\) along the \(x\)-axis of vehicle coordinate system \(xoy\) from the geodetic coordinate system \(XOY\), while \(y_{e}\) is the summed projection of \(X_{d}-X_{c}\) and \(Y_{d}-Y_{c}\) along the \(y\)-axis of \(xoy\). When the orientation \(\theta_{c}\) of the roadheader under the geodetic coordinate system \(XOY\) is close to \(0^{\circ}\), the summed projection along the \(x\)-axis is larger than that along the \(y\)-axis since \(\cos\theta_{c}\) is always larger than \(\sin\theta_{c}\). On the contrary, if \(\theta_{c}\) is inclined to \(90^{\circ}\), \(y_{e}\) would be larger than \(x_{e}\) as long as \(X_{d}-X_{c}\) or \(Y_{d}-Y_{c}\)\(XOY\) is not zero. Since the differences between the expected and real local pose of the roadheader are not likely to be exactly zero, if the designed path follows the \(X\)-axis more likely than the \(Y\)-axis of \(XOY\), the position error \(x_{e}\) would be slightly above zero and \(y_{e}\) as well. This fits the situations shown in Figures 11(b) and 12(b). To summarize based on (1) and (2), under certain levels of processing and measurement noise, such as those specified Sections 3.1 and 3.2, the tracking control proposed in this paper is able to achieve path tracking regardless of whether states estimation is adopted. However, the tracking performance variance between the expected and adjusted paths, the pose error convergence rate, is improved notably by taking the benefits of states estimation by implanting SVD-Unscented Kalman filtering in the process of path tracking control using BP Neural network optimization. It is observed by comparing Figures 11(c) and 12(c) that the angular speeds of the two driving wheels are more stable by applying states estimation. The sharp jumps along the curve in Figure 12(c) correspond to the abrupt change points of the required steering angle speed, which are normal scheduling adjustments. In conclusion, the path tracking simulations of different scenarios show that the proposed scheduling control strategy combining the BP neural network and state estimation is simple in structure and easy to carry out. Compared with the basic pose deviation-based tracking control strategy, the tracking effect of the proposed method is better and more stable. It is of great potential to be applied in practical roadheader scheduling underground in mining and to be included in the intelligence framework for the collaborative control between roadheaders and other equipment in coal mining.
# Investigation of Wind Power Potential in Mthatha, Eastern Cape Province, South Africa
## 4 Conclusions  
South Africa's Eastern Cape Province has the lowest household access to electricity, with 82.64% in 2018, and has experienced a prolonged load shedding for more than a decade. Grid extension in some remote areas of the province is hampered by the remoteness of certain areas and the lack of supportive infrastructure. Thus, there is a need to promote renewable energy technologies like wind to facilitate standalone and mini grid systems to alleviate load shedding and provide electricity to remote areas. This study investigated the wind potential for Mthatha, which is an important step in determining the country's wind energy potential. The 2 WPDF and 3 WPDF were used for modelling the wind speed for the period from January 2013 to August 2023. The MLM and MOM were applied to obtain the Weibull parameters, and their performance for fitting the data was compared using the RMSE. It was established that the Mthatha area is dominated with low wind speeds, with an annual wind speed average of 3.3009 m/s. The probability of receiving wind speeds of above 3 m/s was found to be 57. 5707%. The area is not suitable for most wind turbines that are available on the wind energy market, which are designed for wind speeds of greater than 5 m/s [31; 32]. It is recommended that wind speed augmentation mechanisms be employed in the area, if wind turbines are to be used for providing energy.  
Conceptualization, methodology, formal analysis, and writing--original draft preparation, C.S.; writing--review and editing, methodology, and formal analysis, N.S.; writing--review, editing, methodology, formal analysis, supervision, and funding acquisition, P.M. and G.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding. It received internal funding from Govan Mbeki Research and Development Centre (GMRDC).  
Not applicable.  
Restrictions apply to the availability of these data. Data was obtained from the South African Weather Services (SAWS) and are available from the authors with the permission of SAWS.  
The authors express their gratitude to SAWS for providing data for this re-search at no cost.  
The authors declare no conflict of interest.
## 1 Introduction
Type/biological origin of starch and processing conditions (e.g., use of acid vs. \(\alpha\)- or \(\beta\)-amylase hydrolysis, mechanical, hydrothermal, or ultrasound treatment) are key factors that affect emulsion and powder final properties [16]. In general, the use of low molecular weight OSA-starch tends to provide high encapsulation efficiency and capacity, while for high molecular weight results, the opposite is true (more data in [15]). To date, OSA-starches have been used, for example, to encapsulate avocado oil [17] and fish oil [18], and the obtained powders had good oxidative stability. Although maltodextrin and OSA-starch are popular wall matrix ingredients, there is still a need to look for reduced-calorie wall materials. Such materials can be prebiotics like Nutriose(r) and inulin. Nutriose(r) is a soluble fibre obtained from non-GMO raw materials (wheat, corn, or pea), produced by Roquette company [19]. In this preparation, the distribution of \(\alpha\)-D 1,4-, 1,6-, 1,2-, and 1,3-glycoside bonds is 41%, 32%, 13%, and 14%, respectively [20]. Only 15% of Nutriose(r) is enzymatically digested in the small intestine and provides 1.7 kcal/g [20]. The molecular weight of Nutriose(r) varies from 3500 to 6000 Da [21; 22]. In contrast, inulin is extracted primarily from the chicory root, but it is also found in garlic, onion, Jerusalem artichoke, and other plants [23]. It is a fructan consisting of fructosyl units linked by \(\beta\)-D (2,1) glycosidic bonds with a fully proven prebiotic function [24]. The molecular weight of inulin varies from 500 to 13,000 Da [25]. Energy supply by inulin is 1.5 kcal/g [26]. The aim of the study is to compare the effects of soluble dietary fibre Nutriose(r) (SDF N) and soluble dietary fibre inulin (SDF I) used in a mixture with OSA-starch on the properties of linseed oil emulsion and the powder obtained from it by spray-drying. Additionally, a real food model (apple juice) with the resulting linseed oil powders for colour, aroma, and oxidative and physical stability was tested. Apple juice was selected as a model since colour and stability changes can be easily observed because of its optical clarity [27]. Furthermore, it is the most-produced fruit juice in the world [28].
## 2 Vision-Based Structural Displacement Measurement Methods
### Feature-Based Motion Tracking  
Feature extraction-and-matching is another popular vision-based motion tracking method, and Scale Invariant Feature Transform (SIFT) is the most frequently used multi-scale feature [7; 8; 16; 17; 18], among Harris-Tomasi, SIFT, and Speeded Up Robust Features (SURF). However, there are a large amount of computation redundancies, as well as feature mismatching, in structural displacement measurement by feature-based motion tracking method, due to the non-uniformly distributed gray gradients that are caused by dust and oil stains texture on structure surfaces, as shown in Figure 2. [PERSON] [13] proposed a method to constrain motion inconsistency to eliminate the mismatching problems, and [PERSON] [14] proposed a two-staged Random Sample Consensus (RANSAC) and a geometrical prior information method to remove the mismatching. [PERSON] [20] suggested that the accuracy of the displacement measured by feature extraction of natural structure surface texture is low, and that high-reflectance artificial markers or speckles should be prefabricated or installed. Among the problems of feature-based motion tracking methods in full-field displacement measurements, the first is that the non-uniform distribution of feature points, the red points in Figure 2, do not satisfy the requirements of high-precision strain calculation through  
Figure 1: Diagram of template matching process with image sequence.  
displacement interpolation, which prefer uniformly distributed feature points as shown in Figure 3.
# Unraveling the Scale Dependency of SIF-Based Phenology: Amplified Trends and Climate Responses
## 2 Data and Methods
### Methodology  
Figure 2 illustrates the comprehensive research process, which comprises five key steps: (1) based on the deciduous forest range determined by MODIS land cover data, SIF data with 1-km, 5-km, and 50-km resolution within the range were extracted; (2) the phenology metrics of SIF products at different scales and the GPP data were extracted, using the Savitzky--Golay filtering method and the dynamic threshold method; (3) the extracted phenology from GPP site data was used to validate the phenological metrics obtained from data sources at different scales; (4) phenological metrics extracted at different scales were utilized to assess the trends in the spatial and temporal dynamics of deciduous forest phenology within the study area; and (5) the extracted phenological metrics, along with the reanalysis of climatic data, were used to study the mechanisms behind the phenological response to environmental changes at different scales.
## 2 Materials and Methods  
### Sample Materials and Model Compounds for Desorption Testing  
#### 2.1.1 Manufacturing of Polystyrene Sheets Spiked with Model Compounds  
Pairs of spiked sheets with thicknesses of 350 \(\upmu\)m were prepared from GPPS and HIPS polymer for the desorption kinetics into the gas phase. Model compounds were used as surrogates for real contaminants because polystyrene samples with real contaminants in the molecular weight range of interest are rarely available. Two sets of model compounds were spiked homogeneously during polystyrene sheet production. The first sheet was spiked with a mixture of n-alkanes n-octane, n-decane, n-dodecane, up to n-tetracosane. The second sheet was spiked with a mixture of the following substances: acetone, ethyl acetate, toluene, chlorobenzene, phenyl cyclohexane, benzophenone and methyl stearate.
## 3 Construction Risk Evaluation Index System of Deep Foundation Pit Projects
### WBS Decomposition of the Construction Process of Deep Foundation Pit Projects  
According to Risk Management--Guidelines (ISO 31000:2018), the Code for the Design of Building Foundations (GB 50007-2011), the Technical Standard for Monitoring of Building Excavation Engineering (GB 50497-2019), and the Technical Code for Construction Safety of Deep Building Foundation Excavations (JGJ 311-2013), the construction process of deep foundation pit projects can be divided into Construction Preparation (\(W_{1}\)), Earthworks (\(W_{2}\)), Support Construction (\(W_{3}\)), Drainage Engineering (\(W_{4}\)), and Monitoring (\(W_{5}\)).  
Construction Preparation (\(W_{1}\)) includes Pipeline Migration (\(W_{11}\)) and Site Leveling (\(W_{12}\)). Pipeline Migration (\(W_{11}\)) refers to relocating or developing an on-site water supply, drainage, power supply, heating trunk lines, main roads, and flood control projects. Site Leveling (\(W_{12}\)) refers to leveling the ground to prepare the site by excavating and filling. This step includes the construction survey, earthwork allocation, construction machinery selection, and filling and compaction.  
Earthworks (\(W_{2}\)) includes Earthwork Excavation (\(W_{21}\)) and the Erection of Supports (\(W_{22}\)). Earthwork Excavation (\(W_{21}\)) refers to excavation, filling, and transportation of materials. The Erection of Supports (\(W_{22}\)) describes the construction of temporary supports for earthworks rather than supports for deep foundation pit construction.  
Support Construction Engineering (\(W_{3}\)) refers to the measures to support, reinforce, and protect the sidewall and surrounding environment of the deep foundation pit to ensure the safety of underground construction and the environment of the foundation pit. Common supporting projects include an Underground Diaphragm Wall (\(W_{31}\)), Bored Pile (\(W_{32}\)), Bolt Support System (\(W_{33}\)), and other Supporting Structures (\(W_{34}\)).  
Drainage Engineering (\(W_{4}\)) refers to dewatering projects to ensure that the foundation pit remains dry during construction to prevent slope instability, foundation sand flow, pit bottom uplift, pit bottom piping, and foundation bearing capacity decline when the groundwater level is higher than the bottom of the excavation. Commonly used drainage methods are the Open Ditch Plus Collection Well (\(W_{41}\)), Light Well Point (\(W_{42}\)), Jet Well Point (\(W_{43}\)), Electroosmotic Well Point (\(W_{44}\)), and Tube Well Point (\(W_{45}\)) methods.  
Monitoring (\(W_{5}\)) refers to deformation detection and stress detection of the supporting structure system during the construction of the deep foundation pit. It includes the Monitoring Method (\(W_{51}\)), the Measuring Point Layout (\(W_{52}\)), and Emergency Management (\(W_{53}\)).
# Regularized Zero-Forcing Dirty Paper Precoding in a High-Throughput Satellite Communication System
## 1 Introduction
Reference [12] proposes a complete model of atmospheric propagation to improve the estimation and the analysis of atmospheric effects on the signal quality in satellite communications using actual measured parameters. Although the current research on the precoding technology of high-throughput satellite systems has made great progress, the improvement in SINR (signal-to-interference-plus-noise ratio) is still insufficient, and there is still a gap regarding the throughput requirements of high-throughput satellites. Therefore, further research and improvement of high-throughput satellite precoding technology are still needed in order to continue to optimize the SINR. Based on the above research and analyses, after establishing the forward link model considering the effects of free space loss, rainfall attenuation, and beam gain, this paper improves the classical low-complexity zero-forcing precoding algorithm and studies the regularized zero-forcing precoding algorithm, considering the influence of system noise. Based on the idea of dirty paper coding, a low complexity dirty paper regularized zero-forcing precoding algorithm is proposed in this paper, which aims to encode users sequentially according to the channel conditions to maximize the SINR and increase the throughput of the system. The remainder of the paper is organized as follows. Section 2 describes the system architecture and channel model. The regularized zero-forcing dirty paper precoding of a high-throughput satellite communication system is given in Section 3. The simulation results and analysis are presented in Section 4, followed by the conclusion in Section 5.