esa-sceva/satcom-chunk-collection huggingface dataset:
# A Systematic Review of Ship Wake Detection Methods in Satellite Imagery
## 2 Materials and Methods
### Data Extraction and Synthesis  
For each study that met the inclusion criteria, pertinent information was extracted. Firstly, publication details like authors, year of publication, and source were noted. The objectives and hypotheses of the study were extracted, together with the proposed methodology. The latter was the main focus of this work. Key findings and contributions were also noted, including improvements over previous methods.  
Other information of note was the type of remote sensing data used by the authors, as well as any preprocessing techniques they applied. For datasets built to train DL models, their characteristics and those of their annotations were extracted. In terms of performance metrics, the wide variety of different metrics used for different data through different detection methodologies did not allow for a thorough comparison. While there are some widely accepted metrics for object detection (e.g., accuracy, precision, recall), these were most often not provided by the authors. Moreover, the provided metrics referred to the performance of their methods on different test data. As such, it was not deemed useful to conduct a value comparison.  
The extracted information was organized into categories based on the type of detection method (traditional vs. DL) and image type (optical vs. SAR imagery).
## 2 Related Work
The limitations of current RAG technologies are listed in Table 1.  
In this work, we address the limitations of query and complexity classification in Adaptive-RAG by proposing a framework for categorizing simple and complex queries, termed Layered Query Retrieval (LQR). Specifically, the framework contains a semantic rule-based approach to distinguish between different levels of multi-hop queries. For multi-hop queries, the process begins by parsing the user's query for keywords, followed by a keyword-based document retrieval. Subsequently, we employ a natural language inference (NLI) model to assess whether the retrieved document is relevant to the query. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **RAG Name** & **Limitations** \\ \hline Regular RAG & RAG & \(\bullet\) & Static retrieval processes \\  & & \(\bullet\) & Latency issues with large-scale corpora \\  & & \(\bullet\) & Performing poorly on multi-hop queries \\  & & \(\bullet\) & Fixed retrieval modules may struggle \\ Knowledge-filtered RAG & RAFT, IRCoT & \(\bullet\) & with out-of-domain queries \\  & & \(\bullet\) & Computationally expensive to train and \\  & & & fine-tune \\ RAG adaptive to & & \(\bullet\) & Lacking retrieval robustness \\ query complexity & Adaptive-RAG & \(\bullet\) & Inconsistent information during \\  & & & multi-turn interactions \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of current RAG methods. The system then locates the next-level document based on the initial findings, again using NLI to verify its relevance before combining all relevant results for final input into the model. We test our RAG approach on an agriculture domain-specific dataset for multi-hop queries and compare it with state-of-the-art RAG methods.
## 2 Safe and Efficient UAV Route Construction Method over Wireless Multi-Hop Network
### Method for Constructing Optimal Routes in Terms of Distance and Safety Based on OLSR
#### 2.2.1 Optimized Link State Routing Protocol (OLSR)  
For OLSR, each node periodically sends HELLO and TC messages to update the routing table. The HELLO message performs the tasks of the link discovery, the neighbor node discovery, and the Multipoint Relay (MPR) set discovery.  
TC messages advertise the topology information to the entire network by flooding.  
Each node sends TC messages based on its Local Link Information. When each node receives a TC message, it updates the received topology and updates the routing table. MPR is one of the features of OLSR, which provides an efficient method of flooding TC messages to the entire network by specifying the nodes that forward TC messages as an MPR set. [PERSON], et al. enhanced the OLSR protocol by considering mobility and load balancing for UAV ad hoc networks, closely aligning with the described MPR-based method [39].
## 5 Discussion  
### Lithofacies Paleogeography of the Middle Cambrian  
In accordance with the drilling data, the crosswell profile, outcrop data and seismic facies interpretation of the seismic lines crossing through the basin, a lithofacies paleogeography map of the Middle Cambrian in Tarim Basin was compiled (Figure 9). The Taxi platform area of the Tarim basin is dominated by restricted-platform deposits in the Middle Cambrian. The entire Bachu Uplift is dominated by gypsiferous-salt lake deposits, while the Tazhong area is dominated by gypsiferous-dolomite and argillaceous-dolomite deposits, with gypsiferous dolomite-flat and argillaceous dolomite-flat microfades developed. The wells YM 36, LT 1, YH 5 and TS 1 located in the Tabei Uplift are mainly characterized by mud-dolomite flat, gypsum-dolomite flat, and platform-marginal shoal deposits in the Middle Cambrian. Due to the deep burial depth, drilling wells did not reveal the Middle Cambrian in the Manxi area. However, through detailed interpretation of seismic data, the Cambrian seismic event exhibits strong amplitude and high continuous reflection, and has the same reflection characteristics as the survey line representing the gypsum-salt rock in the Bachu Uplift. Therefore, by tracking the seismic facies in the Tabei Depression, it is believed that the lithology of the Manxi area is mainly gypsiferous salt lake sediments in the Middle Cambrian. Due to its high-terrain feature, combined with seismic data interpretation, it is speculated that there is a mainly tidal flat subfacies of muddy dolomite sedimentation in the southwestern area, despite lacking the drilling data.  
The paleogeographic pattern of the Middle Cambrian in the Tarim Basin basically inherited the characteristics of the early Cambrian. The sea level declined slowly, and the deposits of the open-platform facies gradually became smaller, while the deposits of the restricted-platform facies continued to expand. In the early Cambrian, areas developed microfacies such as gypsum-dolomite flat and mud-dolomite flat, especially in higher terrain, and gradually formed gypsiferous salt lake microfacies as the main sedimentary facies. In the Middle Cambrian, deposits of gypsiferous salt lake were widely distributed in the western part of the Bachu Uplift, Tazhong Uplift and the Manxi area. The gypsiferous dolomite flat and argillaceous dolomite flat were distributed outward in a circular belt along the gypsiferous salt lake, while the eastern and northern edges of the rimmed platform were mainly deep-water-basin sedimentary facies. In summary, the lithofacies paleogeography characteristics of the Middle Cambrian in the Tarim Basin are clearly differentiated from east to west and from south to north. From west to east, the sedimentary facies are sequentially mud-domolite flat, gypsiferous dolomite flat, gypsiferous salt lake, gypsiferous dolomite flat, argillaceous dolomite flat, platform margin, slope and basin facies. Meanwhile, there are platform shoal deposits within the gypsiferous dolomite flat subfacies (Figure 9).
## 4 Experiment and Discussion
### Optimization of Incident Light Power  
Incident light power affects the Larmor signal amplitude, the noise level, and the relaxation rate. Increasing the incident light power can increase the Larmor signal amplitude, but the relaxation rate and noise level also increase [10; 28]. At the same time, noise level is not only related to the incident light power, but also related to the noise of the amplifier. It is difficult to find the optimal incident light power value with a simple formula, so the parameter needs to be optimized by experiments. In the experiment, the output DC voltage of the photoelectric detection circuit is used to determine the incident light power. As mentioned in Section 4.2, the noise and relaxation rate are independent of the RF power. Under the condition of each incident light power, the relaxation rate and the noise are measured. The relaxation rate is obtained from the phase curve. In the case of \(\omega_{rf}-\omega_{L}=\Gamma\), the phase difference is 45 degrees. The RF power is optimized, and the maximum Larmor signal amplitude is used to calculate the sensitivity at each incident light power point. The measured results are shown in Figure 12. All the data are obtained when the cell temperature keeps at 35 \({}^{\circ}\)C. Through the experiment, the incident light power with the best sensitivity is obtained.  
Figure 12: **(a)** Result of the relaxation rate changing as a function of the output DC voltage of the amplifier. **(b)** Result of the output noise floor changing as a function of the output DC voltage of the amplifier. **(c)** Result of the output SNR changing as a function of the output DC voltage of the amplifier. **(d)** Result of the sensitivity changing as a function of the output DC voltage of the amplifier.
## 4 Conclusions  
The results of this study suggest the suitability of combining the photo-Fenton process and GAC filtration to remove the textile dyes from a centralised treatment plant. This combination allows the reduction of the photo-Fenton treatment time and extends the GAC lifetime. The maximum reduction of irradiation energy consumption was 75%, and the GAC lifetime was extended by 5 to 7 times depending on the scenario, in both cases, compared to the use of the technologies independently. At the same time, the use of regenerated GAC to adsorb indigo carmine has been shown as a suitable alternative that will reduce the carbon footprint of the process. These results are promising and show that the combination of photo-Fenton and GAC filtration is an interesting alternative to make the scaling up of the photo-Fenton process feasible and more effective.  
A natural progression of this work will be to evaluate this combination as a further step for the removal of representative CECs in Luxembourg. The two technologies independently and their combination will be studied at Heiderscheidergrund WWTP (Luxembourg) to assess their feasibility as an effective solution for urban effluent deprivation.  
The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/su16041605/s1](https://www.mdpi.com/article/10.3390/su16041605/s1)]([https://www.mdpi.com/article/10.3390/su16041605/s1](https://www.mdpi.com/article/10.3390/su16041605/s1)).  
P.N.-T.: Conceptualization, Investigation, Methodology, Visualization, Writing--Original draft preparation. I.S.: Conceptualization, Methodology, Validation, Writing--Review and Editing. S.V.: Conceptualization, Methodology, Writing--Review and Editing, Project Administration. J.H.: Writing--Review and Editing, Supervision, Project Administration, Funding Acquisition. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Administration de la gestion de l'eau--Ministere du developpement durable et des infrastructures of Luxembourg under the Fentastic Project.  
Not applicable.  
The datasets generated and/or analysed during the current study are available in the Supplementary Materials.  
The authors wish to thank to our project partners SIDEN (Syndicate intercommunal de depollution des eaux residuaires du Nord), Hydro-Ingenieure, TR-Engineering and WiW (Wupperverbandsgesellschaft fur integrale Wasserwirtschaft) mbh.  
The authors declare no conflicts of interest.  
\begin{table}
\begin{tabular}{c c c c c c} \hline  & **Photo-Fenton** & \multicolumn{2}{c}{**GAC Columns**} & \multicolumn{2}{c}{**Combination of Processes**} \\ \hline  & & CarboTech DGF & NRS Carbon & CarboTech DGF & NRS Carbon \\  & & 8x30 GL & GA 0.5–2.5 & 8x30 GL & GA 0.5–2.5 \\ \hline Energy (€/m3) & 0.059 & – & – & 0.010 & 0.010 \\ GAC cost (€/m3) & – & 0.060 & 0.055 & 0.008 & 0.015 \\ Reagents (€/m3) & 0.144 & – & – & 0.144 & 0.144 \\ Total (€/m3) & 0.203 & 0.060 & 0.055 & 0.161 & 0.169 \\ \hline \end{tabular}
\end{table}
Table 3: Operational cost related to each tested scenario for the treatment of real wastewater.
## 4 Current Regulations for UAS
These standards indicate a classification into three different levels for UAS, and its limitations are shown in Table 3.  
* Class A: The operation of the UAS is allowed under the limitations established by UAEAC RAC 91, Appendix 13, and it has a maximum take-off weight between 250 g and 25 kg; it does not require authorization due to its low risk. * Class B: This kind of UAS exceeds the maximum take-off weight and is up to 150 kg; therefore, UAEAC always requires authorization, even though its operation may involve low risk. * Class C: This last classification of UAS corresponds to aircraft that exceed 150 kg at maximum take-off weight and are used to overtly international airspace or transportation for which, for now, their operation in Colombian airspace is not authorized. The authorization for this type of UAS is only for scientific research and development and is highly restrictive from UAEAC [73]. \begin{table}
\begin{tabular}{c c c} \hline
**Class A** & **Class B** & **Class C** \\ \hline \multirow{6}{*}{Maximum takeoff weight 25 kg} & \multirow{6}{*}{Maximum takeoff weight 150 kg} & Class C are mainly experimental aircraft in the country, so, the operations are carried out by duly recognized or authorized public, or private entities for the exclusive purposes of scientific research, innovation, and development. \\  & & \\ \hline Maximum speed 80 km/h. & Maximum speed 100 km/h. & \\ \hline Visual Line of Sight (VLOS) up to 500 m, horizontally during all flights. & Visual Line of Sight (VLOS) up to 750 m, horizontally during all flights. & \\ \hline The operation cannot be directly over the public, crowds, buildings, cities, or other populated areas. & Every flight must be up to 123 m over earth or water. & \\ \hline The entire operation must be daytime only. It is only allowed at night in open spaces and unpopulated areas, free of obstacles, and the UAS must have bright lights to see it. & Visibility conditions cannot be less than 5 km from its location. \\ \hline Every flight must be up to 123 m over earth or water. & Minimum distance from clouds is 150 m. \\ \hline Visibility conditions cannot be less than 5 km from its location. & Its operation cannot be carried out from an aerodrome, heliport or in its vicinity within a radius of 3 km. \\  & & Any operation that requires aerial works other than image capture requires authorization from the UAEAC. \\ \hline The operation may only be carried out within Class G airspace (not regulated). & Rescue and search operations, or similar missions that hinder those carried out by authorities or rescue organizations, cannot be carried out. \\ \hline \end{tabular}
\end{table} 
Table 3: Operation limits by UAEAC authority, based on [73].
## 2 Numerical Approach
### Governing Equation  
The working medium is seawater, which is a Newtonian fluid. The flow of the seawater in the narrow space between friction surfaces should follow the Navier-Stokes equation. A Navier-Stokes equation is employed to describe the problem studied.  
\[\left\{\begin{array}{l}\frac{\partial u}{\partial x}+\frac{\partial v}{ \partial y}+\frac{\partial w}{\partial z}=0\\ \rho\left(u\frac{\partial u}{\partial x}+v\frac{\partial w}{\partial y}+w\frac {\partial w}{\partial z}\right)=-\frac{\partial p}{\partial x}+\eta\left( \frac{\partial^{2}u}{\partial x^{2}}+\frac{\partial^{2}u}{\partial y^{2}}+ \frac{\partial^{2}u}{\partial z^{2}}\right)\\ \rho\left(u\frac{\partial w}{\partial x}+v\frac{\partial w}{\partial y}+w\frac {\partial w}{\partial z}\right)=-\frac{\partial p}{\partial y}+\eta\left( \frac{\partial^{2}v}{\partial x^{2}}+\frac{\partial^{2}v}{\partial y^{2}}+ \frac{\partial^{2}v}{\partial z^{2}}\right)\\ \rho\left(u\frac{\partial w}{\partial x}+v\frac{\partial w}{\partial y}+w\frac {\partial w}{\partial z}\right)=-\frac{\partial p}{\partial z}+\eta\left( \frac{\partial w}{\partial z^{2}}+\frac{\partial^{2}w}{\partial y^{2}}+\frac {\partial^{2}w}{\partial z^{2}}\right)\end{array}\right. \tag{1}\]  
where \(u\), \(v\) and \(w\) are the velocity vectors in directions \(x\), \(y\) and \(z\); \(\rho\) is the density of seawater (1.025 g/cm\({}^{3}\)); \(\eta\) is the dynamic viscosity of seawater (6.15 \(\times\) 10\({}^{-4}\) Pa\(\cdot\)s); and \(p\) is the pressure of the lubricating film.  
Figure 1: Lubrication model of a friction pair with a hemispherical-pit surface.
## 2 Materials and Methodology  
### Study Area  
With a land area of 6.928 \(\times\) 10\({}^{6}\) km\({}^{2}\) and a total population of 357.23 million people, the Middle East region spans southwestern Asia and northeastern Africa between the latitudes of 12\({}^{\circ}\)06\({}^{\prime}\)N and 42\({}^{\circ}\)07\({}^{\prime}\)N and the longitudes of 25\({}^{\circ}\)E and 63\({}^{\circ}\)17\({}^{\prime}\)E (Figure 1) [49]. It comprises the Arabian Peninsula and the Levant region in addition to Egypt, Iraq, Iran, and Turkey. The dominant land-cover pattern in the region is bare land, which represents almost 65.6% of the total area, while vegetation areas (mainly shrub- and tree-covered areas, grassland, and cropland) cover roughly 31.75% of the total area [50] (See Figure A1). The region's climate pattern is distinguished by a transitional climate that ranges from dry-hot to humid-cold. According to the Koppen-Geiger climate classification, the dominant climate pattern in the region is the hot-dry climate (BWh), which represents almost 67.7% of the total area, followed by the cold-semiarid climate (BWh) and temperate-wet climate (Csa), which represent roughly 9.8% and 6.40% of the total area, respectively [51]. Overall, the rainiest regions are situated in the northern mountain ranges due to orographic effects (e.g., the Zagros and Taurus Mountains), along the coasts of the Mediterranean and the Aegean Sea, and along the southern coasts of the Black and Caspian Seas. Due to topographical and latitudinal gradients, air temperatures are distinguished by high intra-annual variability; the annual mean temperature (1991-2020) ranged from 12 \({}^{\circ}\)C in the Turkish areas to 26 \({}^{\circ}\)C in Saudi Arabia [52]. Rainfall is highly variable over both space and time; the rainy season extends mostly between November and April. Rainfall is controlled largely by the location and frequency of the Mediterranean cyclones. However, a short, rainy summer season dominates the southern part of the region (Yemen, SW Saudi Arabia), which is influenced by the Indian and African monsoons [53].  
Figure 1: Location of the study area and Köppen–Geiger classification-based climate patterns [51].
###### Abstract  
The batch, repeated batch and fed-batch cultivation strategies, in stirred tank bioreactors, were evaluated to maximize biomass production and the cells' desulfurization activity (CDA) of _Rhodococcus qingshenggi_ IGTS8. The batch culture reached 2.62 g DCW/L biomass, with a productivity of 0.03 g DCW-L\({}^{-1}\)-h\({}^{-1}\) and only 26% glycerol consumption. The repeated batch strategy reduced cultivation time during the first cycle, increasing biomass production by 15%, with 30% glycerol consumed and productivity 2.3 times higher than the batch process; however, subsequent cycles showed no further improvement. CDA peaked early in both modes but declined to 12-13 U/mg DCW by the end of the exponential growth phase. Fed-batch cultivation achieved 8.35 g DCW/L with 87% glycerol consumption, resulting in a threefold increase in volumetric productivity and a 1.7-fold higher specific growth rate compared with the batch mode. CDA remained stable during the fed-batch process and was approximately 40% higher compared with the batch and repeated batch processes. The fed-batch culture was used directly in a two-phase bubble column bioreactor for the desulfurization of dibenzothiophene (DBT), 4-methyl-dibenzothiophene (4-MDBT) and their mixture. The complete desulfurization of 1.4 mM DBT was achieved at a rate of 21.6 mmol DBT/kg DCW/h, while 0.9 mM 4-MDBT was fully converted but at a 2.5-fold lower rate. The simultaneous conversion of the DBT/4-MDBT mixture showed reduced efficiencies of 59.6% and 41.2%, respectively.  
Rhodococcus qingshenggi IGTS8: Evaluation of Batch, Repeated Batch and Fed-Batch Cultivation Techniques. _Appl. Sci._**2025**, 15, 8349. [[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/)).
# Characteristics and Release Risk of Phosphorus from Sediments in a Karst Canyon Reservoir, China
## 3 Results
### Distribution Characteristics of Phosphorus Forms in Sediments  
The phosphorus content in the sediments of the Wanfeng Reservoir followed the order of Fe/Al-P \(>\) Res-P \(>\) Ca-P \(>\) H\({}_{2}\)O-P \(>\) NaHCO\({}_{3}\) and those trends in phosphorus forms within the sediment columns at each site were consistent with the trends observed for TP content (Figure 3).  
The distribution of phosphorus forms revealed that the proportion of NaHCO\({}_{3}\)-P in Wanfeng Reservoir sediments was the lowest, accounting for 19.52% to 19.49% of TP (mean 18.69%). The proportion of Fe/Al-P was the highest, ranging from 17.34 to 94.39 mg\(\cdot\)kg\({}^{-1}\) (mean 49.86 mg\(\cdot\)kg\({}^{-1}\)), accounting for 20.4% to 31.38% of the TP (mean 22.41%). In terms of lateral distribution, the Fe/Al-P content increased in the sequence of WF3 \(>\) WF1 \(>\) WF2. The presence of higher Fe/Al-P content in the sediments indicates a heavier contamination of phosphorus, reflecting the pollution level of the reservoir [44].  
The average content of Res-P in the sediments was 44.92 mg\(\cdot\)kg\({}^{-1}\), accounting for 20.05% of TP. The average content of Ca-P was 44.15 mg\(\cdot\)kg\({}^{-1}\), accounting for 19.6% of TP. Res-P and Ca-P are considered relatively stable and inert forms of phosphorus, exhibiting limited exchange with the overlying water and being less affected by general changes in environmental conditions. The combined content of H\({}_{2}\)O-P, NaHCO\({}_{3}\)-P and Fe/Al-P accounted for 60.35% of TP, indicating their significant contribution within the sediment phosphorus pool.  
Figure 2: Vertical distribution of total phosphorus (TP) in the three sediment cores (WF1–3).  
Figure 3: Contents of sediment phosphorus fractions across the sampling sites (WF1–3).