esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The decentralized treatment of wastewater and its on-site infiltration is common practice, especially in rural areas. However, uncertainties exist on the degradation potential of treated wastewater constituents mixed with additional infiltration of large quantities of water originating from precipitation. The intermixture of these waters is causing a reduction of residence times of the treated wastewater as well as an increased water saturation within the unsaturated soil zone. This can lead to a negative influence on the purification efficiency. Laboratory-scale 1D column experiments, accompanied by numerical simulations of water flow using the software code HYDRUS 1D, have been performed to evaluate the risks for a reduction of the degradation efficiency. Water content measurements and analysis of relevant organic substances in samples taken at different depths were the basis for evaluating the influence of the joint infiltration on the purification efficiency. The results highlight that a joint infiltration of treated wastewater and additional water originating from precipitation is not affecting the degradation efficiency for treated wastewater constituents. Degradation rates under these conditions were similar to the infiltration of treated wastewater alone. Timeframes with high water saturation were limited to the duration of the precipitation event.  
Keywords:column experiments; treated wastewater infiltration; precipitation; degradation efficiency; unsaturated soil zone; numerical modeling +
Footnote †: journal: Applied Sciences
## 4 VR-PEKS Scheme and Security Definition
### Scheme Definition  
There are six polynomial time algorithms in the VR-PEKS scheme, described as follows.  
(1) \((pk,sk,k)\leftarrow\mathit{KeyGen}(1^{\lambda})\): The algorithm is executed by KGC. On inputting a security parameter \(\lambda\), it outputs public and private keys \((pk,sk)\) of the FHE encryption algorithm and a key \(k\) of \(\mathit{OPRF}\).  
(2) \((\mathit{CF},I_{S},I_{V})\leftarrow\mathit{Enc}(pk,k,W,F)\): The algorithm is executed by the DS. On input keys \((pk,k)\), keywords \(W=\{w_{1},w_{2},\cdots,w_{m}\}\), and plaintext document set \(F=\{F_{1},F_{2},\cdots,F_{n}\}\), it outputs encrypted data file set \(\mathit{CF}\), a searchable index \(I_{S}\), and a verification index \(I_{V}\).  
(3) \(T_{\mathbf{w}}\leftarrow\mathit{Gen}\mathit{Trapdoor}(pk,\mathbf{w},k)\): The algorithm is executed by DR. On input public key \(pk\), key \(k\), and keyword \(\mathbf{w}\), it outputs keyword trapdoor \(T_{\mathbf{w}}\).  
(4) \((R_{F},ID_{R_{F}})\leftarrow\mathit{Search}(T_{\mathbf{w}}^{*},I_{S})\): The algorithm is executed by CS. On input searchable index \(I_{S}\) and the trapdoor \(T_{\mathbf{w}}^{*}\) of keyword \(\mathbf{w}^{\prime}\), it runs this algorithm to test whether the keyword ciphertexts \(CT_{\mathbf{w}}\) and \(T_{\mathbf{w}}^{*}\) correspond to the same keyword. If \(\mathbf{w}=\mathbf{w}^{\prime}\), it returns the corresponding ciphertext file result set \(R_{F}\) and the file name set \(ID_{R_{F}}\).  
(5) \(Verify(R_{F},ID_{R_{F}},I_{V})\): The algorithm is executed by DR. On input ciphertext file result set \(R_{F}\), file name set \(ID_{R_{F}}\), and encrypted verification index \(I_{V}\), it outputs the file validation result. If it is true, it returns 1; otherwise, the result is 0.  
(6) \(\mathit{Dec}(R_{F},sk)\): The algorithm is executed by DR. On input ciphertext file result set \(R_{F}\) and private key \(sk\), it outputs the plaintext of \(R_{F}\).
## 2 Fundamentals of Ion-Exchanged Glass Waveguide Circuits
We must also underline that, although an empiric approach can be sufficient in many cases to determine the fabrication parameters, a great amount of research work has been devoted to a rigorous physical modeling and numerical simulation of ion exchange in glass, which in turn, is related to the development of different theories on ion exchange in glass [15; 67; 68; 69; 70; 71]. These physical/numerical approaches can be required when the refractive index profile must be known with a great accuracy. In any case, one of the main aims in integrated optical circuits is to obtain single-mode channel guides (paths) that are coupled in certain regions by directional coupling and with phase shifters suitably located, as shown in Figure 6 to achieve an integrated optical circuit with a specific purpose. Finally, it is also worth indicating that sometimes two-mode or even few-mode waveguides can be considered. The modes can be considered in plane yz or also in depth \(x\). In the latter case, it can be considered as a type of three-dimensional integration [27; 72]. On the other hand, two-mode guides in the yz plane have also been considered, for example, for spatial multiplexing [73].
This paper is useful in reducing the power consumption and therefore, the batteries size and the cost of the harvesting hardware. Considering that the energy consumption optimization minimizes the energy harvesting, we proposed an algorithm that exploits the selected hardware and the communication protocol in order to achieve the minimum energy consumption at a given time and therefore, minimize the energy harvesting efforts. Taking that into account, the contribution of this paper is a LOw power Konsumption Algorithm (LOKA) that controls the program flow of a more and reduces its energy consumption. It controls the energy mode of each electronic device of the sensor more based on the state of the communication protocol. LOKA forces a low power mode in the idle devices of each mode when they are not working, and changes it when they need more computational power. Then, the reduction of energy consumed will be exponential depending upon the transmission data interval and on the operation time of the WSN application. LOKA is the result of the problems encountered during the testing of a WSN deployed in homes of dependent people for tele-assistance. During the tests, we needed to monitor the people movements and different phenomena of their daily life in conjunction with an assistant telecare robot. We realized that the battery life was very short and we could not count on the monitored people (since they had Alzheimer's disease) for charging the motes. In this sense, with LOKA, we were able to monitor the dependents for more than two months with a single charge instead of a few days as happened initially. This article is organized as follows. Next section introduces the state of the art of solutions in reducing the motes energy consumption. After, Section 3 provides: (i) the reference framework where LOKA can be implemented; (ii) the communication protocol used and (iii) the hardware considerations for LOKA. Then, LOKA is described in detail in Section 4. Next, Section 5 presents the experiments divided in two blocks: the first block shows the design for the mote where LOKA was embedded for the experiments, while the second block explains the method to measure the energy and provides the values obtained in our experiments. Finally, some conclusions are outlined.
## 2 Materials and Methods
### Statistical Analysis and Computer Processing of Transfer Conditions  
We used statistical experimental designs as a method to minimize the experimental conditions for the diffusion transfer of EO in EO-PG. The transfer was presented as flux \(F\). The design matrix used for this purpose was a full factorial design based on three factors, \(X_{i}\):  
* Factor 1 = \(T\): temperature (25 \({}^{\circ}\)C and 30 \({}^{\circ}\)C);
* Factor 2 = \(H\): humidity (50% and 70%);* Factor 3 = \(C\): concentration of the EO fixed on the PG (0.01 \(\mu\)L\(\cdot\)g\({}^{-1}\)\(\cdot\)cm\({}^{-3}\) and 0.02 \(\mu\)L\(\cdot\)g\({}^{-1}\)\(\cdot\)cm\({}^{-3}\)). Each factor with two levels: high level coded as +1 and low level coded as \(-1\). The number of tests for \(k\) factors: \[number\ of\ tests=2^{k}\] (12) \[Number\ of\ tests=2^{3}=8\] (13) This corresponds to 8 tests. The polynomial model presents \[F=a_{0}+\sum_{i=1}^{n}a_{i}X_{i}+\sum_{i=1}^{n}\sum_{j=1}^{n-1}a_{ij}X_{i}X_{j }+a_{ijk}X_{i}X_{j}X_{k}\] (14) or:
* Mean: \(a_{0}\);
* 3 effects for each factor: \(a_{i}\);
* 3 effects present the interactions of 2 nd order: \(a_{ij}\);
* 1 effect presents the interactions of 3 rd order: \(a_{ijk}\). Various factors determine the behavior of essential oil in a porous material. On the one hand, diffusion parameters include flux (\(F\)) and diffusivity (\(D\)). The insecticidal activity is represented by the mortality (\(M\%\)), and the germination parameters are presented by the weight (\(W\)), the length of the aerial part (\(L_{A}\)), and the length of the root part (\(L_{R}\)) of the lentils. However, the numerical values of the parameters are difficult to understand and interpret their meanings. To investigate the interaction between EO behavior in porous media and biological activity, we utilized PCA (principal component analysis), a multivariate statistical analysis. We correlated the matter transfer by diffusion parameters with the biological activity. The work follow-up was carried out on matrices obtained from eight subjects during the optimization of the flow of evaporation in porous materials. Six variables were considered in the analysis, namely, \(F\), \(D\), \(M\%\), \(W\), \(L_{A}\), and \(L_{R}\). The aim was to determine the relationships between the variables and to identify any patterns or trends that could provide insight into the behavior of EO-PG with respect to biological activities. All the analysis was conducted using various computer tools, including MATLAB software for numerical modeling and other programs, such as EXCEL, XLSTAT, and DESIGN EXPERT, for specific calculations and graphical representations. The resulting data were compared with experimental results to identify relevant parameters and ensure maximum interpretation.
## 5 Further Analyses and Discussion: Towards the Unwanted Chain of Errors Avoidance  
As a technical achievement, the ECDIS has been conventionally accepted as a primary navigational means, having brought many benefits to seafarers. Generally speaking, this fact has been expected. Nevertheless, it would be reasonable to elaborate on the opinions of the seafarers from both the researches who have favoured PNCs and traditional navigational means. There is a division of seafarers [30], as to whether they have developed their navigational skills before or after the electronic means have taken place globally, requiring their roles and working experience to be considered. The overall results have been subsequently analysed by years and participants' rank. A first analysis has been made on the basis of the questionnaire submission year. The results in terms of three answering options (yes/no/no answer) have been plotted using a 100% stacked column chart (Figure 8). This allowed comparison of the percentage of contribution for each category, showing that the most significant share on the PNC removal was in 2018, equal to more than 65%. The second analysis regarded both the navigational rank and the questionnaire submission year (Table 1 and Figure 9, respectively). Figure 8: ECDIS EHO survey participants’ opinions regarding PNC removal divided by years. Source: Authors. Figure 9: ECDIS EHO participants’ opinions regarding PNC removal divided by years and rank (Q1: Do you agree with the fact of the withdrawal of the paper charts from the service if certain conditions are met regarding the ECDIS system, i.e., there is no further obligation to possess the same?) Source: Authors. When comparing years 2014 and 2018, an even opinion or slight increase among all navigational ranks, with an exception of second officers, has been noted regarding the favouring of electronic navigation means, as opposed to traditional navigation. When analysing the first six months of the year 2018 (_EHO_) and the time frame before mandatory system implementation, there were still 50% of the masters, who have not agreed with the PNC removal. Staff captains and safety officers were equally divided (50%). A 90% of the chief officers and a significant share of the second officers (42%) did not agree with the PNCs withdrawal from the service. Although represented in a relatively small share, the results indicated that 100% of the third officers would like to withdraw the PNCs. The general percentage of answers on _Q2 HMI_ regarding the navigational rank is shown in Figure 10. The relative share of two possible answers (yes/no) has been provided by each participant's rank. Approximately 60% of masters, staff captains, and third officers would like to withdraw PNCs from the service after the mandatory system implementation. The majority of the second officers (78%) and chief officers (86%), as well as all of the 1 st officers navigation share the same opinion. The exception have been unspecified participants (2%).
## 4 Experiments  
In this section, we mainly validate the effectiveness of our proposed method through three experiments. Firstly, we investigate the impact of different resolution hash encodings on pose estimation and verify the effectiveness of low-resolution grids for pose estimation.  
Secondly, we analyzed the impact of the number of layers in the low-resolution module on pose estimation to further understand its architecture and performance. Thirdly, based on the aforementioned experiments, we experimentally verify the performance of BiResNeRF. Lastly, we conducted an experiment to validate the adaptability and effectiveness of our method when faced with scenarios characterized by the absence of pose, low texture and reflection.  
**Dataset**  
Experiments in this paper were conducted on the Realistic Synthetic 360\({}^{\circ}\) dataset [17]. This dataset, synthesized via Blender, encompasses eight objects with intricate geometric shapes and authentic non-Lambertian materials, namely Chair, Drums, Ficus, Hotdog, Lego, Materials, Mic and Ship. Images were generated by sampling and rendering as the camera orbited around these objects. Each object is represented with 100 training images and 200 test images, all accompanied by accurate pose data and rendered at a resolution of [800, 800] pixels. For the purposes of our experiment, the image size is reduced to half, resulting in a resolution of [400, 400] pixels.  
**Evaluation Criteria**  
We primarily evaluate the synthesis quality of new viewpoints and the accuracy of pose estimation. For the synthesis of new viewpoints, the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Learned Perceptual Image Patch Similarity (LPIPS) [34] are employed as assessment metrics. These are commonly used image quality assessment indicators, capable of comprehensively reflecting the image's performance in pixel differences, structural information, and perceptual quality. For pose estimation, the Procrustes analysis [24] is used to align the estimated pose with the real pose, and subsequently, the rotation and translation errors are calculated.
## 3 Influence of Inherent Anisotropy
### Microscopic Results
#### 3.2.2 Evolution of Coordination Number  
Contact number is one of the most important characteristics of granular materials and is often represented by the coordination number \(CN\), which is defined as the average number of contacts per particle. In the definition of the mechanical coordination number, only particles with no less than two contacts are used to calculate \(CN\) value [40]. Previous studies have shown that void ratio is a macro quantity closely related to \(CN\). [PERSON] and [PERSON] [41] discussed the relation between \(CN\) and void ratio in the biaxial test simulated by DEM. They pointed out that anisotropy must be considered when establishing a relationship between void ratios and \(CN\).  
The evolution of \(CN\) under growing stress is shown in Figure 9. Before loading, the \(CN\) values of all specimens were very close to each other. We found that the \(CN\) value of all samples decreased slightly at the beginning and then increased steadily. This is the same as [PERSON]'s simulation results [31]. Based on [PERSON] and [PERSON]'s [41] theory, the decrease of \(CN\) value in the initial stage is induced by the rearrangement of particle contact, producing fabric anisotropy to bear the applied stress. After the completion of rearrangement, \(CN\) increases steadily with the densification of the specimen. For specimens with large \(\delta\) (\(\delta=60^{\circ}\) and \(90^{\circ}\)), we can find that the decrease of \(CN\) is greater than that of other specimens.
# Optimizing Routing Protocol Design for Long-Range Distributed Multi-Hop Networks
## 4 Load-Balancing Routing Optimization Scheme Design
### Load-Aware MPR Selection Algorithm Improvement  
When a node no longer meets the load rate and occupancy rate constraints, yet is still selected as an MPR node, this can lead to the congestion of topology messages, which is obviously inappropriate. Therefore, in selecting MPR nodes, it is essential to prioritize nodes with low occupancy rates and low load rates to avoid causing topology information congestion. In the OLSR protocol, nodes express their willingness to undertake network traffic through the \"willingness\" option in the HELLO packet. This willingness ranges from 0 to 7, representing different levels of willingness. If the willingness option is \"willingnever\", the node will never be selected as an MPR by other nodes; if the willingness option is \"willing always\", the node will always serve as an MPR. By default, the value is set to \"willing default\".  
This paper proposes adjusting the willingness value of nodes by considering both the load rate and occupancy rate comprehensively, as shown in Table 2. Based on different combinations, the settings are categorized into WILL_LOW, WILL_HIGH, and WILL_DEFAULTULT [30].
## 2 Materials and Methods
### Equipment and Experimental Procedures  
An AUTOCLAVE ENGINEERS (Erie, PA, USA) stirred tank batch reactor (Figure 1a), made of 316 stainless steel and with a capacity of 284 mL, was used for the hydrothermal treatment of the CFRPs under subcritical conditions. The reactor was equipped with a model TC21 PID ICP controller (3) with the capacity to maintain a constant temperature at \(\pm\)2 \({}^{\circ}\)C accuracy, connected to a type K thermocouple (1) installed within the reactor, which operated a 1.2 kW cylindrical electric heater (4). The system was fitted with an inlet and outlet purging valve system that allowed the implementation of an initial N\({}_{2}\) pressure and the collection of the samples (5). A pressure gauge allowed us to monitor the pressure inside the reactor for a range of 0-550 bar (2). The mechanical stirrer, \"0.7502 Magnetdrive\", featured a belt-driven head and a magnetically driven propeller (6).  
The hydrothermal treatment of the CFRPs under supercritical conditions was conducted using a PARR 4570 Series non-stirred tank batch reactor (Figure 1b), which is made of 316 stainless steel, has a capacity of 1084 mL, and can operate at 570 \({}^{\circ}\)C and 277 bar maximum temperature and pressure. The reactor was equipped with temperature (1) and pressure (2) sensors linked to the ParrCom application to allow real-time data logging and temperature adjustments by means of a PID controller (3) that operated a 2.3 kW cylinder electric heater (4). The reactor was also equipped with a purge and gaseous sampling valve system (5).  
The experimental procedure described below was applied to both reactors. First of all, the composite sample was placed on a coiled tubing support made of 316 stainless steel. This supporting accessory ensured that the entire surface of the composite samples remained in direct contact with the solvent but not with the reactor walls. The solvent, consisting of either pure water or an aqueous solution of IPA 5 wt.%, was added together with the corresponding catalyst at 0.1 M concentration.  
As a first step, the reactor was closed and purged with N\({}_{2}\) for 15 min in order to remove the oxygen from inside the reactor. For the tests under subcritical conditions, the AUTOLAVE ENGINEERS reactor was pressurized with N\({}_{2}\) up to 35-40 bar to ensure that the solvent remained liquid at the setpoint temperature. Also, the stirring of the reactor was set at 60 rpm.  
Then, a 30 min heating phase was started until 300 \({}^{\circ}\)C was reached in the AUTOLAVE ENGINEERS reactor. In the PARR 4570 reactor, the heating phase took 100-105 min and 400 \({}^{\circ}\)C was reached. A reaction time (rt) was then allowed, and then the oven was turned off and allowed to cool down to room temperature. The gas was sampled and the reactor was opened to extract the coiled tubing support that held the recycled fibers and to collect the liquid effluent containing the degraded resin. Triplicate tests were carried out to confirm the repeatability of the experimental procedure, and deviations lower than 2% in DR were registered.
## 3 Temperature-Based ET Models: Advantages, Drawbacks, and Evolution of Research
### Single-Source Surface Energy Balance Models
#### 3.1.3 The Simplified Surface Energy Balance Operational Application (SSEBop)  
Building upon the SSEB model, SSEBop was developed by incorporating elevation and latitude effects on surface temperature. It has been parameterized for operational applications and utilized in estimating ET in the Colorado River Basin, showing promising outcomes [35; 36; 37].  
Further assessments demonstrated SSEBop reliability for large-scale ET estimation, showcasing an R2 of 0.86 between estimated and measured ET with acceptable uncertainties [38]. The model's performance was further enhanced by combining long-term ET estimates with SSEBop products, resulting in improved accuracy, especially in non-irrigated areas [39]. SSEBop was also successfully applied in estimating ET for irrigated wheat in the Cerrado region of Brazil, showing reliable results compared to the Bowen ratio method [40].  
In China, SSEBop accuracy was validated, showing reliable estimations at different scales (site and basin) compared to eddy covariance data from ChinaFLUX stations. Moreover, the models performed well in simulating the spatiotemporal variation [41].  
Utilizing Landsat thermal imagery and SSEBop in Google Earth Engine, ET was estimated and mapped over the conterminous United States (CONUS). The model demonstrated mixed performance in accuracy evaluation over two woody savanna sites, with a stronger correlation over well-vegetated areas [42]. Later, SSEBop was enhanced by relying on the Forcing and Normalizing Operation (FANO) algorithm, which improved parameterization and reduced biases in grassland and cropland ET estimations. The implementation on the two computing platforms, Google Earth Engine and Earth Resources Observation and Science Center, further improved the model accuracy, expanding its coverage for ET modeling [43].  
The SSEBop analysis revealed more sensitivity to specific input variables, notably LST and ET\({}_{0}\), as well as specific parameters, including differential temperature (dT) and maximum ET scalar (K-max) [38]. To further enhance the precision of SSEBop model estimates, it is crucial to address inaccuracies associated with these input variables and parameter refinement.