esa-sceva/satcom-chunk-collection huggingface dataset:
# Temporal and Spatial Diversity of Renewable Groundwater Resources in the River Valley
## 2 Background to the Study Site
### Hydrogeological Conditions  
Detailed characteristics of the hydrogeological conditions of the Vistula valley have been presented in a number of publications based mainly on field reconnaissance and monitoring of groundwater and surface waters, functioning in the region since 1999, providing information on the functioning of GDE areas and confirming their dependence on groundwater based on various statistical methods, i.e., factor analysis [6; 40; 45; 46; 47; 48].  
The groundwater table in the Quaternary deposits of the Vistula valley is unconfined and inclined towards the present-day Vistula River. The recharge of the aquifer occurs mainly through infiltration of precipitation water in the valley area. The lateral inflow from upland areas extending to the east, south and west is minimal [48]. The thickness of the aquifer varies from 9 to 45 m, and its bottom occurs at elevations from 2 to 54 m a.s.l. (Figures 2 and 3). The groundwater resources available for development have been estimated at 31.075 m\({}^{3}\)/d, and 35.2% (0.49 L/s km\({}^{2}\)) of the resources are in use [36]. The Quaternary aquifer is underlain predominantly by Pliocene clays. The Paleogene-Neogene aquifer formation is represented by glauconite sands of Oligocene at a depth below 150 m.  
Figure 3: Groundwater condition scheme in the study area (adapted from [6]).  
The research area was included in the Main Groundwater Basin No. 222-Middle Vistula Valley [49], covering part of the Vistula valley, up to 15 km wide (Figure 1). MGBs are reservoirs established in Poland containing strategic groundwater resources, meeting specific quantitative and qualitative criteria, such as: the potential discharge rate of the well above 70 m\({}^{3}\)/h, well-field discharge rate above 10,000 m\({}^{3}\)/day, transmissivity above 10 m\({}^{2}\)/h and the water has to be suitable for supply purposes to the population in the raw state or after its possible simple treatment by substances of currently used and economically justified technologies.
# Enhancing Methyl Orange Degradation with Laser-Generated ZnO and Ce-Doped ZnO Nanoparticles
## 2 Materials and Methods
### Photocatalytic Activity  
The photocatalytic activity of 1% Ce-doped ZnO NPs and undoped ZnO NPs was evaluated by measuring the rate of MO degradation under two different light sources: UV light at 396 nm (4.397 mW) and natural sunlight. The experiments were carried out in  
Figure 1: Schematic illustration of (**a**) the experimental setup featuring the CO\({}_{2}\) laser. (**b,c**) Digital images depicting the formation of undoped ZnO NPs after CO\({}_{2}\) laser irradiation inside the ceramic boat and 1% Ce/ZnO NPs, respectively.  
Penang, Malaysia, from 9 a.m. to 12 noon, with an average temperature of approximately 29 \(\pm\) 1.5 \({}^{\circ}\)C. The MO dye photodegradation test was performed in a 50 mL beaker, which contained 20 ppm of MO dye and 0.05 g of photocatalysts, as shown in Figure 2a. Prior to irradiation, for achieving adsorption/desorption equilibrium, the solution was stored in the dark for 30 min. During the sequence of experiments, at 10-min intervals over 90 min, 2 mL of the solution was withdrawn each time until the solutions became colorless, indicating dye reduction. Subsequently, the UV-vis spectrum of the sampled solutions was analyzed within the wavelength range of 200 nm to 800 nm. It is important to mention that the standard absorption curve of the MO dye (shown in Figure 2b) exhibited its highest absorption peak at 466 nm.
# Accelerometers in Monitoring Systems for Rail Vehicle Applications: A Literature Review
## 5 Guide for Choosing a Correct Accelerometer
### Sensitivity and Resolution  
An accelerometer is a device that measures movement or acceleration and transforms that motion into an electrical signal. When it outputs data, they are often measured in millivolts per \"g\", which refers to the gravitational force we experience on Earth. For a charge-mode accelerometer, the measurement is given in pC per \"g\". These devices come in various sensitivities, meaning some are better at detecting small movements than others. The best choice of sensitivity will depend on how strong or weak the motion you want to measure is.  
When dealing with small vibrations, using a very sensitive accelerometer is important. This type of device can pick up signals that are much clearer and stronger than the background noise produced by other electronic parts. For instance, if we expect the vibrations to be very slight (like 0.1 g) and our accelerometer can produce a 10 millivolt (mV) signal for every g, then the output would only be 1 mV. This might not be enough to stand out from the noise, so using an accelerometer with even greater sensitivity would be a good idea.  
Additionally, the concept of resolution is important to understand. This basically refers to the smallest change in vibration that the accelerometer can reliably detect, and it depends on the device's noise level. A lower noise level allows for the better detection of tiny signals.
## 2 Materials and Methods
### Conceptual Model  
The first step in building the conceptual model was defining the dimensions of the modeled area. The data used for this were those on available boreholes and levels of the Danube River. Defining the area's dimensions primarily refers to determining the area within which the calculations will be carried out. Defining the boundaries of the model was directly determined by the sites where the available data on the measured levels were recorded, which were implemented in the model in the form of boundary conditions. In this case study, the layout plan of monitoring wells was obtained from The Urban and Spatial Planning Institute of Novi Sad, Figure 1. Given that the subject area was surrounded by wells S-73, S-112, P-14, S-102, and S-26, in which the groundwater level was continuously measured, with the Danube River on the eastern side, this area was adopted as representative for modeling purposes. The modeled area was formed by connecting boundary wells S-73, S-112, P-14, and S-26 (well S-102 was used for calibration purposes) and the Danube, thus generating a closed polygon within which a grid was formed and simulations were performed. At the well locations and the Danube, corresponding level measurements were set as boundary conditions. Interpolation was performed for each moment in time on the parts of the outline between the wells. By setting the boundary conditions in this way, an area was formed within which the flow was induced exclusively by the measured \"boundary\" conditions, which resulted  
of these layers, corresponding values of hydraulic parameters--the filtration coefficient K and retention coefficient S--along with the parameters describing the permeability and yield of the soil were used. The geotechnical study data were used for the terrain's vertical stratification. These data show that this location is mostly sandy land extending to the floor, estimated at an elevation of 58.0 m. It should be noted that these are data on the narrower locality around the object itself, which, due to the lack of more detailed bases, were adopted as such for the entire modeled area. The disposition of the considered layers of the analyzed area is shown in Figure 3.  
Figure 3: The disposition of the considered layers.  
Figure 2: The accepted grid: (**a**) lower resolution of the broader region; (**b**) higher resolution around the structure itself.
## 3 Results and Discussion
### Aroma Compounds  
The OPLS-DA was applied to identify the most characteristic marker compounds for wine region discrimination. As shown in Figure 2A,B, a clear separation was obtained by a reliable OPLS-DA model (\(R^{2}X=0.708\), \(R^{2}Y=0.799\), and \(Q^{2}=0.545\)), except for the similarity between the XJ and LP Marselan wines. Interestingly, the OPLS-DA models showed a clear separation between two classes (Class 1 includes JDP and BHB; Class 2 includes HZB, LP, and XJ) based on the first component. It is well known that the discrimination of similar-style wines made from the same variety in different regions is typically ascribed to differences in the environmental conditions.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Region** & **Alcohol (\%)** & **Reducing Sugar (g/L)** & **Total Acidity (g/L)** & **pH** & **Glycerol (g/L)** \\ \hline Jiaodong Peninsula (JDP) & 12.75 \(\pm\) 0.70 b & 2.93 \(\pm\) 0.81 c & 4.87 \(\pm\) 0.53 b & 3.69 \(\pm\) 0.07 a & 8.31 \(\pm\) 0.57 bc \\ Bohai Bay (BHB) & 12.45 \(\pm\) 0.79 b & 3.46 \(\pm\) 1.04 bc & 5.18 \(\pm\) 0.75 ab & 3.85 \(\pm\) 0.09 a & 7.78 \(\pm\) 0.85 c \\ Huaizhuo Basin (HZB) & 13.54 \(\pm\) 0.80 ab & 3.46 \(\pm\) 0.50 bc & 5.84 \(\pm\) 0.80 a & 3.63 \(\pm\) 0.18 a & 9.57 \(\pm\) 1.21 a \\ Loess Plateau (LP) & 13.52 \(\pm\) 1.53 ab & 4.11 \(\pm\) 0.41 ab & 5.71 \(\pm\) 1.17 ab & 3.74 \(\pm\) 0.32 a & 9.07 \(\pm\) 1.43 ab \\ Xinjiang (XJ) & 14.24 \(\pm\) 0.77 a & 4.36 \(\pm\) 0.92 a & 5.70 \(\pm\) 0.35 ab & 3.77 \(\pm\) 0.21 a & 9.49 \(\pm\) 0.94 a \\ \hline \hline \end{tabular}  
* Averages and standard deviation followed by different letters are significant at \(p<0.05\), [PERSON]’s multiple range test.  
\end{table}
Table 1: Basic parameters of Marselan wines from different regions of China *.  
Figure 2: OPLS-DA models based on the flavor compounds of Marselan wine samples from different regions of China. (**A**) Score scatter plot for Marselan wine samples based on the concentrations of volatile compounds. (**B**) Loading plot for the volatile compounds of Marselan wine samples. (**C**) Score plot for Marselan wine samples based on the concentrations of phenolic compounds. (**D**) Loading plot for the phenolic compounds of Marselan wine samples.  
The volatile aroma compounds that showed differences (\(p<0.05\)) across the regions are presented in Table 2. As expected, the majority of the potential maker compounds for discrimination displayed differences in concentration. In order to interpret the volatile aroma compound differences between varieties, the potential marker compounds with differences are summarized and discussed according to their origins (e.g., grapes and fermentation) and chemical categories (e.g., terpen, norisoprenoids, ethyl esters, and acetates).
# Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard
###### Abstract  
An intelligent emergency system for hazard monitoring and building evacuation is a very important application area in Internet of Things (IoT) technology. Through the use of smart sensors, such a system can provide more vital and reliable information to first-responders and also reduce the incidents of false alarms. Several smart monitoring and warning systems do already exist, though they exhibit key weaknesses such as a limited monitoring coverage and security, which have not yet been sufficiently addressed. In this paper, we propose a monitoring and emergency response method for buildings by utilizing beacons and Unmanned Aerial Vehicles (UAVs) on an IoT security platform. In order to demonstrate the practicability of our method, we also implement a proof of concept prototype, which we call the UAV-EMOR (UAV-assisted Emergency Monitoring and Response) system. Our UAV-EMOR system provides the following novel features: (1) secure communications between UAVs, smart sensors, the control server and a smartphone app for security managers; (2) enhanced coordination between smart sensors and indoor/outdoor UAVs to expand real-time monitoring coverage; and (3) beacon-aided rescue and building evacuation.  
sensors and beacons; unmanned aerial vehicles; monitoring and emergency response systems; Internet of Things; security +
Footnote †: journal: Sensors
# Application of the Reed-Solomon Algorithm as a Remote Sensing Data Fusion Tool for Land Use Studies
## 1 Introduction
One-modality of observations may be difficult to interpret [4]. A statistical sample of research projects concerning LU/LC revealed that data fusion provided results with higher accuracy than either of the datasets individually [5].
## 1 Introduction
However, most of the current optimization work of RDMA for distributed file systems only uses RDMA libraries or plug-ins as communication submodules of the system, and does not make full use of the excellent features of RDMA [8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27]. Accelio, the RDMA middleware used in CephFS, encapsulates the underlying RDMA network functions and only provides an abstract call interface [28; 29]. In this way, the application cannot customize RDMA network transmission according to the characteristics of its own network transmission. The work of [PERSON] et al. for HDFS was also carried out by supporting RDMA network modules; it has been difficult to further improve performance through the rich features of RDMA and full use of high-performance network resources has not been achieved. GlusterFS's strategy is to apply RDMA libraries instead of TCP/IP to complete network transmission, but there is no customization of transmission schemes according to different application scenarios, nor is it supported by a more effective memory model [30]. In summary, in these optimized designs, the network transport layer of the distributed file system is basically strictly isolated from the logical processing layer. In addition, they do not effectively integrate and adapt with the data processing mechanism of the file system according to the characteristics of RDMA transmission, and the software and hardware advantages of RDMA transmission cannot be fully utilized by replacing the data transmission function in the system. In the case of GlusterFS, software latency accounts for about 1-3% of total latency in disk media file systems, and close to 100% in memory file systems with stronger storage hardware [31]. Obviously, after the storage performance and network performance are improved, the isolation of the file system software layer and the network transport layer makes the distributed system too complex, making the software part of the system a bottleneck and limiting the performance of hardware devices. In view of the objective requirements of distributed systems' RDMA network transmission in a high-performance hardware environment and the inability of current research work to effectively coordinate the system software layer and network layer to give full play to the performance of RDMA, in this paper, we propose a lightweight distributed file system based on RDMA technology that focuses on the RDMA communication module of FastDPS and proceeds from the communication process. The system optimizes the communication process to maximize the advantages of RDMA communication technology, improves the performance of the original FastDPS distributed file system, and achieves the purpose of improving system bandwidth, reducing latency, and reducing server CPU utilization.
## 7 Conclusions  
In recent years, smart farming technology has rapidly advanced and has significantly contributed to the improvement of crop yields. To further improve the efficiency of data collection in smart farming, this research proposes a framework that utilizes unmanned aerial vehicles (UAVs) and Internet of Things (IoT) devices. However, this open environment is vulnerable to intrusions, which can hinder the data collection process and ultimately reduce agricultural productivity. To address this potential threat, the research proposes an intrusion detection system (IDS) integrated into a fog-based UAV-IoT farm data collection system. The IDS utilizes machine learning algorithms that are trained on the CICIDS2017 dataset, which is publicly available, to detect and prevent intrusions. A layer-based intrusion detection approach is considered to detect both known and zero-day attacks. For known attacks, a signature-based IDS is used and uses XGBoost, extra tree, random forest, and decision tree algorithms. For zero-day attacks, clustering techniques are used, which include the K-means algorithm. The evaluation results show that XGBoost provides the best results, as it can detect intrusions with 99.77% accuracy, with an F1 score of 0.1055 RMSE and a 99.81% R-squared score. The modular design is developed to implement and benchmark the proposed work in terms of UAV energy, transmission, and communication delays. The proposed IDS integrated with the fog-based UAV-IoT farm data collection  
Figure 11: Transmission delay between sensors and UAVs.  
system can improve the security and efficiency of smart farming, which can ultimately lead to increased crop yield and improved agricultural productivity. In the future, the research will aim to improve the intrusion detection system using machine vision and extensive deep learning techniques.  
Conceptualization, J.S., Z.A. and A.W.M.; methodology, Z.A. and A.W.M.; software, J.S. and A.W.M; validation, A.W.M; formal analysis, Z.A.; investigation, J.S., K.H., A.W.M. and Z.A.; resources, Z.A. and Z.T.; data curation, J.S., A.W.M. and Z.A.; writing original draft preparation, J.S., K.H., A.W.M, Z.A. and Z.T.; writing review and editing, A.W.M and Z.A.; visualization, J.S, A.W.M. and Z.A.; supervision, K.H., A.W.M., Z.A. and Z.T.; project administration, K.H., A.W.M., Z.A. and Z.T.; funding acquisition, K.H., Z.A. and Z.T. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Sheila and Robert Challey Institute for Global Innovation & Growth at North Dakota State University, USA, and Zayed University under the Cluster Research Grant R20140, UAE.  
Not applicable.  
The data may be requested by reaching out to authors through email.  
The authors declare no conflict of interest.
# Power Control and Link Selection for Wireless Relay Networks with Hybrid Energy Sources
###### Abstract  
The Hybrid energy supply (HES) wireless relay system is a new green network technology, where the source node is powered by the grid and relay is powered by harvested renewable energy. However, the network's performance may degrade due to the intermittent nature of renewable energy. In this paper, our purpose is to minimize grid energy consumption and maximize throughput. However, improving the throughput requires increasing the transmission power of the source node, which will lead to a higher grid energy consumption. Linear weighted summation method is used to turn the two conflicting objectives into a single objective. Link assignment and a power control strategy are adopted to maximize the total reward of the network. The problem is formulated as a discrete Markov decision model. In addition, a backwards induction method based on state deletion is proposed to reduce the computational complexity. Simulation results show that the proposed algorithm can effectively alleviate performance degradation caused by the lack of renewable energy, and present the trade-off between energy consumption and throughput.  
energy harvesting relay; energy consumption; throughput +
Footnote †: journal: Applied Soft. 2019, 9, 2744
# Adsorption of Ibuprofen from Water Using Waste from Rose Geranium (_Pelargonium gravelens_) Stems
## 3 Characterisation
### Adsorption Results  
#### 3.5.1 Time Effect of SPG and Kinetic Models  
The adsorption of IBU was studied at intervals of 1-105 min to understand the rate of uptake (Figure 5). It was found that the adsorption rate in the initial phase between 1 and 45 min was rapid. This is due to the interaction between IBU and the active sites such as functional groups containing oxygen, rough texture, pores, and voids on the surface of SPG [20]. Subsequently, a slow adsorption rate occurred, resulting in little to no adsorption in time intervals of 65-105 min. This is attributed to the progressive saturation of the active sites, which limits the adsorption rate and leads to equilibrium [21].  
The data on the time effect were recorded and fitted to two known kinetic models, which are listed in Table 2. This was to test the model best suited to the data. Pseudo-first-order (PFO) and pseudo-second-order (PSO) kinetic models are based on physisorption and chemisorption, respectively [22]. The selection criterion is based on the comparison of the correlation coefficient (\(r^{2}\)), which is closest to 1. The review shows that PFO has an \(r^{2}\) value closer to 1. This indicates that the data fit PFO rather than PSO. The uptake of IBU on SPG is mainly through physisorption driven by weak van der Waals forces [23]. The model also predicted a Q\({}_{0}\) value closer to the experimental q\({}_{\mathrm{e}}\). The intra-particle diffusion (IPD) kinetic model-estimated pore adsorption (EPA) was 23.44%, and the estimated surface adsorption (ESA) was 76.56%.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**PFO** & **PSO** & & **IPD** & \\ \hline Q\({}_{0}\) (mg/g) & 31.66 & q\({}_{\mathrm{e}}\) (mg/g) & 27.23 & C (mg/g) & 27.23 \\ b (L/mg) & 0.102 & 1/n & 2.56 & K\({}_{\mathrm{i}}\) (g/g\(\cdot\)min\({}^{1/2}\)) & 1.43 \\ R\({}^{2}\) & 0.9918 & k\({}_{\mathrm{f}}\) & 1.007 & R\({}^{2}\) & 0.8187 \\  & & R\({}^{2}\) & 0.8475 & EPA (\%) & 23.44 \\  & & & & ESA (\%) & 76.56 \\ \hline \hline \end{tabular} Experimental (q\({}_{\mathrm{e}}\)) (mg/g) 34.88.  
\end{table}
Table 2: Kinetic models of SPG.  
Figure 5: Time effect on SPG for ibuprofen.
# Strategy for Non-Orthogonal Multiple Access and Performance in 5G and 6G Networks
## 3 NOMA Code-Separated Techniques  
Based on subscriber signal code division, 3 GPP described various NOMA systems [9]. The proposed schemes for existing 5G scenarios did not show a significant advantage over the used 5G technologies; hence NOMA was not included in 5G standards but was further studied for new scenarios [9].